GKD-V Cercos Chaos vs Movement [Loxx]Giga Kaleidoscope GKD-V Cercos Chaos vs Movement is a Volatility/Volume module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ GKD-V Cercos Chaos vs Movement
The following aims to provide a detailed explanation of Cercos Chaos vs Movement that helps traders determine market volatility by comparing two different measures: Buffer Move and Buffer Chaos. This indicator is non-directional and should be paired with a directional indicator to provide trading signals.
The first step in the process is defining a custom function that implements a variant of the sigmoid function. This function has a parameter that allows the output to be limited to the range of if desired. The sigmoid function will later be used to normalize the Buffer Chaos value.
Next, several input parameters are introduced, which can be adjusted by the user. These parameters include the period, chaos strength, chaos width, and movement strength. These values are essential to customizing the behavior of the indicator and adapting it to different market conditions and trading styles.
The wicks of the candles in the given time series are then calculated by subtracting the absolute difference between the open and close prices from the difference between the high and low prices. This step is crucial in determining the level of volatility in the market.
Subsequently, the highest high and lowest low over the defined period are identified by examining the maximum and minimum values of the open and close prices. This information is essential for calculating the total movement in the market over the period being analyzed.
Once the highest high and lowest low are found, the Buffer Move and Buffer Chaos values are calculated. The Buffer Move is the sum of the differences between the high and low prices for each candle in the period. This measure helps to identify the overall price movement in the market during the period.
On the other hand, the Buffer Chaos represents the sum of the wicks' lengths for each candle in the period. This measure is used to identify the level of uncertainty and disorder in the market during the period.
In the next step, the total movement in the market is calculated by subtracting the lowest low from the highest high. This value is then used to normalize the Buffer Move and Buffer Chaos values, ensuring they are on a comparable scale.
A comparison is made between the normalized Buffer Move and Buffer Chaos values. If the Buffer Move value is greater than the Buffer Chaos value, it indicates that there is enough volatility in the market to trade long or short. In such a case, the indicator suggests that the market conditions are favorable for trading. However, as this indicator is non-directional, a directional indicator should be used in conjunction with it to provide trading signals.
In conclusion, this custom trading indicator provides valuable insights into market volatility by comparing the Buffer Move and Buffer Chaos values. By offering a non-directional perspective, traders can use this indicator to gauge the potential for profitable trades and make informed decisions by pairing it with a directional indicator.
Additional Features
This indicator allows you to select from 33 source types. They are as follows:
Close
Open
High
Low
Median
Typical
Weighted
Average
Average Median Body
Trend Biased
Trend Biased (Extreme)
HA Close
HA Open
HA High
HA Low
HA Median
HA Typical
HA Weighted
HA Average
HA Average Median Body
HA Trend Biased
HA Trend Biased (Extreme)
HAB Close
HAB Open
HAB High
HAB Low
HAB Median
HAB Typical
HAB Weighted
HAB Average
HAB Average Median Body
HAB Trend Biased
HAB Trend Biased (Extreme)
What are Heiken Ashi "better" candles?
Heiken Ashi "better" candles are a modified version of the standard Heiken Ashi candles, which are a popular charting technique used in technical analysis. Heiken Ashi candles help traders identify trends and potential reversal points by smoothing out price data and reducing market noise. The "better formula" was proposed by Sebastian Schmidt in an article published by BNP Paribas in Warrants & Zertifikate, a German magazine, in August 2004. The aim of this formula is to further improve the smoothing of the Heiken Ashi chart and enhance its effectiveness in identifying trends and reversals.
Standard Heiken Ashi candles are calculated using the following formulas:
Heiken Ashi Close = (Open + High + Low + Close) / 4
Heiken Ashi Open = (Previous Heiken Ashi Open + Previous Heiken Ashi Close) / 2
Heiken Ashi High = Max (High, Heiken Ashi Open, Heiken Ashi Close)
Heiken Ashi Low = Min (Low, Heiken Ashi Open, Heiken Ashi Close)
The "better formula" modifies the standard Heiken Ashi calculation by incorporating additional smoothing, which can help reduce noise and make it easier to identify trends and reversals. The modified formulas for Heiken Ashi "better" candles are as follows:
Better Heiken Ashi Close = (Open + High + Low + Close) / 4
Better Heiken Ashi Open = (Previous Better Heiken Ashi Open + Previous Better Heiken Ashi Close) / 2
Better Heiken Ashi High = Max (High, Better Heiken Ashi Open, Better Heiken Ashi Close)
Better Heiken Ashi Low = Min (Low, Better Heiken Ashi Open, Better Heiken Ashi Close)
Smoothing Factor = 2 / (N + 1), where N is the chosen period for smoothing
Smoothed Better Heiken Ashi Open = (Better Heiken Ashi Open * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Open * (1 - Smoothing Factor))
Smoothed Better Heiken Ashi Close = (Better Heiken Ashi Close * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Close * (1 - Smoothing Factor))
The smoothed Better Heiken Ashi Open and Close values are then used to calculate the smoothed Better Heiken Ashi High and Low values, resulting in "better" candles that provide a clearer representation of the market trend and potential reversal points.
It's important to note that, like any other technical analysis tool, Heiken Ashi "better" candles are not foolproof and should be used in conjunction with other indicators and analysis techniques to make well-informed trading decisions.
Heiken Ashi "better" candles, as mentioned previously, provide a clearer representation of market trends and potential reversal points by reducing noise and smoothing out price data. When using these candles in conjunction with other technical analysis tools and indicators, traders can gain valuable insights into market behavior and make more informed decisions.
To effectively use Heiken Ashi "better" candles in your trading strategy, consider the following tips:
Trend Identification: Heiken Ashi "better" candles can help you identify the prevailing trend in the market. When the majority of the candles are green (or another color, depending on your chart settings) and there are no or few lower wicks, it may indicate a strong uptrend. Conversely, when the majority of the candles are red (or another color) and there are no or few upper wicks, it may signal a strong downtrend.
Trend Reversals: Look for potential trend reversals when a change in the color of the candles occurs, especially when accompanied by longer wicks. For example, if a green candle with a long lower wick is followed by a red candle, it could indicate a bearish reversal. Similarly, a red candle with a long upper wick followed by a green candle may suggest a bullish reversal.
Support and Resistance: You can use Heiken Ashi "better" candles to identify potential support and resistance levels. When the candles are consistently moving in one direction and then suddenly change color with longer wicks, it could indicate the presence of a support or resistance level.
Stop-Loss and Take-Profit: Using Heiken Ashi "better" candles can help you manage risk by determining optimal stop-loss and take-profit levels. For instance, you can place your stop-loss below the low of the most recent green candle in an uptrend or above the high of the most recent red candle in a downtrend.
Confirming Signals: Heiken Ashi "better" candles should be used in conjunction with other technical indicators, such as moving averages, oscillators, or chart patterns, to confirm signals and improve the accuracy of your analysis.
In this implementation, you have the choice of AMA, KAMA, or T3 smoothing. These are as follows:
Kaufman Adaptive Moving Average (KAMA)
The Kaufman Adaptive Moving Average (KAMA) is a type of adaptive moving average used in technical analysis to smooth out price fluctuations and identify trends. The KAMA adjusts its smoothing factor based on the market's volatility, making it more responsive in volatile markets and smoother in calm markets. The KAMA is calculated using three different efficiency ratios that determine the appropriate smoothing factor for the current market conditions. These ratios are based on the noise level of the market, the speed at which the market is moving, and the length of the moving average. The KAMA is a popular choice among traders who prefer to use adaptive indicators to identify trends and potential reversals.
Adaptive Moving Average
The Adaptive Moving Average (AMA) is a type of moving average that adjusts its sensitivity to price movements based on market conditions. It uses a ratio between the current price and the highest and lowest prices over a certain lookback period to determine its level of smoothing. The AMA can help reduce lag and increase responsiveness to changes in trend direction, making it useful for traders who want to follow trends while avoiding false signals. The AMA is calculated by multiplying a smoothing constant with the difference between the current price and the previous AMA value, then adding the result to the previous AMA value.
T3
The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm.
The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction.
The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Cercos Chaos vs Movement as shown on the chart above
Confirmation 1: Fisher Transform
Confirmation 2: Williams Percent Range
Continuation: Cercos Chaos vs Movement
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
1-Candle Rule Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close)
2. GKD-B Volatility/Volume agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
2. GKD-C Confirmation 1 agrees
3. GKD-C Confirmation 2 agrees
4. GKD-V Volatility/Volume Agrees
]█ Setting up the GKD
The GKD system involves chaining indicators together. These are the steps to set this up.
Use a GKD-C indicator alone on a chart
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
Use a GKD-V indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Use a GKD-B indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Baseline (Baseline, Backtest)
1. Import the GKD-B Baseline into the GKD-BT Backtest: "Input into Volatility/Volume or Backtest (Baseline testing)"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline"
Volatility/Volume (Volatility/Volume, Backte st)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Solo"
2. Inside the GKD-V indicator, change the "Signal Type" setting to "Crossing" (neither traditional nor both can be backtested)
3. Import the GKD-V indicator into the GKD-BT Backtest: "Input into C1 or Backtest"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Volatility/Volume"
5. Inside the GKD-BT Backtest, a) change the setting "Backtest Type" to "Trading" if using a directional GKD-V indicator; or, b) change the setting "Backtest Type" to "Full" if using a directional or non-directional GKD-V indicator (non-directional GKD-V can only test Longs and Shorts separately)
6. If "Backtest Type" is set to "Full": Inside the GKD-BT Backtest, change the setting "Backtest Side" to "Long" or "Short
7. If "Backtest Type" is set to "Full": To allow the system to open multiple orders at one time so you test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Solo Confirmation Simple (Confirmation, Backtest)
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
1. Import the GKD-C indicator into the GKD-BT Backtest: "Input into Backtest"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Solo Confirmation Simple"
Solo Confirmation Complex without Exits (Baseline, Volatility/Volume, Confirmation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
6. Import the GKD-C into the GKD-BT Backtest: "Input into Exit or Backtest"
Solo Confirmation Complex with Exits (Baseline, Volatility/Volume, Confirmation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Import the GKD-C indicator into the GKD-E indicator: "Input into Exit"
6. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
7. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Full GKD without Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
9. Import the GKD-E into the GKD-BT Backtest: "Input into Exit or Backtest"
Full GKD with Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Import the GKD-C Continuation indicator into the GKD-E indicator: "Input into Exit"
9. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
10. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Baseline + Volatility/Volume (Baseline, Volatility/Volume, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Baseline + Volatility/Volume"
2. Inside the GKD-V indicator, make sure the "Signal Type" setting is set to "Traditional"
3. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline + Volatility/Volume"
5. Import the GKD-V into the GKD-BT Backtest: "Input into C1 or Backtest"
6. Inside the GKD-BT Backtest, change the setting "Backtest Type" to "Full". For this backtest, you must test Longs and Shorts separately
7. To allow the system to open multiple orders at one time so you can test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Requirements
Inputs
Chained: GKD-B Baseline
Solo: NA, no inputs
Baseline + Volatility/Volume: GKD-B Baseline
Outputs
Chained: GKD-C indicators Confirmation 1 or Solo Confirmation Complex
Solo: GKD-BT Backtest
Baseline + Volatility/Volume: GKD-BT Backtest
Additional features will be added in future releases.
Tìm kiếm tập lệnh với "high low"
GKD-C CCI Adaptive Smoother [Loxx]Giga Kaleidoscope GKD-C CCI Adaptive Smoother is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ GKD-C CCI Adaptive Smoother
Commodity Channel Index: History, Calculation, and Advantages
The Commodity Channel Index (CCI) is a versatile technical analysis indicator widely used by traders and analysts to identify potential trends, reversals, and trading opportunities in various financial markets. Developed by Donald Lambert in 1980, the CCI was initially designed to analyze the cyclical behavior of commodities. However, its applications have expanded over time to include stocks, currencies, and other financial instruments. The following provides an overview of the CCI's history, explain its calculation, and discuss its advantages compared to other indicators.
History
Donald Lambert, a commodities trader and technical analyst, created the Commodity Channel Index in response to the unique challenges posed by the cyclical nature of the commodities markets. Lambert aimed to develop an indicator that could help traders identify potential turning points in the market, allowing them to capitalize on price trends and reversals. The CCI quickly gained popularity among traders and analysts due to its ability to adapt to various market conditions and provide valuable insights into price movements.
Calculation
The CCI is calculated through the following steps:
1. Determine the typical price for each period: The typical price is calculated as the average of the high, low, and closing prices for each period.
Typical Price = (High + Low + Close) / 3
2. Calculate the moving average of the typical price: The moving average is computed over a specified period, typically 14 or 20 days.
3. Calculate the mean deviation: For each period, subtract the moving average from the typical price, and take the absolute value of the result. Then, compute the average of these absolute values over the specified period.
4. Calculate the CCI: Divide the difference between the typical price and its moving average by the product of the mean deviation and a constant, typically 0.015.
CCI = (Typical Price - Moving Average) / (0.015 * Mean Deviation)
Why CCI is Used and Its Advantages over Other Indicators
The CCI offers several advantages over other technical indicators, making it a popular choice among traders and analysts:
1. Versatility: Although initially developed for commodities, the CCI has proven to be effective in analyzing a wide range of financial instruments, including stocks, currencies, and indices. Its adaptability to different markets and timeframes makes it a valuable tool for various trading strategies.
2. Identification of overbought and oversold conditions: The CCI measures the strength of the price movement relative to its historical average. When the CCI reaches extreme values, it can signal overbought or oversold conditions, indicating potential trend reversals or price corrections.
3. Confirmation of price trends: The CCI can help traders confirm the presence of a price trend by identifying periods of strong momentum. A rising CCI indicates increasing positive momentum, while a falling CCI suggests increasing negative momentum.
4. Divergence analysis: Traders can use the CCI to identify divergences between the indicator and price action. For example, if the price reaches a new high, but the CCI fails to reach a corresponding high, it can signal a weakening trend and potential reversal.
5. Independent of price scale: Unlike some other technical indicators, the CCI is not affected by the price scale of the asset being analyzed. This characteristic allows traders to apply the CCI consistently across various instruments and markets.
The Commodity Channel Index is a powerful and versatile technical analysis tool that has stood the test of time. Developed to address the unique challenges of the commodities markets, the CCI has evolved into an essential tool for traders and analysts in various financial markets. Its ability to identify trends, reversals, and trading opportunities, as well as its versatility and adaptability, sets it apart from other technical indicators. By incorporating the CCI into their analytical toolkit, traders can gain valuable insights into market conditions, enabling them to make more informed decisions and improve their overall trading performance.
As financial markets continue to evolve and grow more complex, the importance of reliable and versatile technical analysis tools like the CCI cannot be overstated. In an environment characterized by rapidly changing market conditions, the ability to quickly identify trends, reversals, and potential trading opportunities is crucial for success. The CCI's adaptability to different markets, timeframes, and instruments makes it an indispensable resource for traders seeking to navigate the increasingly dynamic financial landscape.
Additionally, the CCI can be effectively combined with other technical analysis tools, such as moving averages, trend lines, and candlestick patterns, to create a more comprehensive and robust trading strategy. By using the CCI in conjunction with these complementary techniques, traders can develop a more nuanced understanding of market behavior and enhance their ability to identify high-probability trading opportunities.
In conclusion, the Commodity Channel Index is a valuable and versatile tool in the world of technical analysis. Its ability to adapt to various market conditions and provide insights into price trends, reversals, and trading opportunities make it an essential resource for traders and analysts alike. As the financial markets continue to evolve, the CCI's proven track record and adaptability ensure that it will remain a cornerstone of technical analysis for years to come.
What is the Smoother Moving Average?
The smoother function is a custom algorithm designed to smooth the price data of a financial asset using a moving average technique. It takes the price (src) and the period of the rolling window sample (len) to reduce noise in the data and reveal underlying trends.
smoother(float src, int len)=>
wrk = src, wrk2 = src, wrk4 = src
wrk0 = 0., wrk1 = 0., wrk3 = 0.
alpha = 0.45 * (len - 1.0) / (0.45 * (len - 1.0) + 2.0)
wrk0 := src + alpha * (nz(wrk ) - src)
wrk1 := (src - wrk) * (1 - alpha) + alpha * nz(wrk1 )
wrk2 := wrk0 + wrk1
wrk3 := (wrk2 - nz(wrk4 )) * math.pow(1.0 - alpha, 2) + math.pow(alpha, 2) * nz(wrk3 )
wrk4 := wrk3 + nz(wrk4 )
wrk4
Here's a detailed breakdown of the code, explaining each step and its purpose:
1. wrk, wrk2, and wrk4: These variables are assigned the value of src, which represents the source price of the asset. This step initializes the variables with the current price data, serving as a starting point for the smoothing calculations.
wrk0, wrk1, and wrk3: These variables are initialized to 0. They will be used as temporary variables to hold intermediate results during the calculations.
Calculation of the alpha parameter:
2. The alpha parameter is calculated using the formula: 0.45 * (len - 1.0) / (0.45 * (len - 1.0) + 2.0). The purpose of this calculation is to determine the smoothing factor that will be used in the subsequent calculations. This factor will influence the balance between responsiveness to recent price changes and smoothness of the resulting moving average. A higher value of alpha will result in a more responsive moving average, while a lower value will produce a smoother curve.
Calculation of wrk0:
3. wrk0 is updated with the expression: src + alpha * (nz(wrk ) - src). This step calculates the first component of the moving average, which is based on the current price (src) and the previous value of wrk (if it exists, otherwise 0 is used). This calculation applies the alpha parameter to weight the contribution of the previous wrk value, effectively making the moving average more responsive to recent price changes.
Calculation of wrk1:
4. wrk1 is updated with the expression: (src - wrk) * (1 - alpha) + alpha * nz(wrk1 ). This step calculates the second component of the moving average, which is based on the difference between the current price (src) and the current value of wrk. The alpha parameter is used to weight the contribution of the previous wrk1 value, allowing the moving average to be even more responsive to recent price changes.
Calculation of wrk2:
5. wrk2 is updated with the expression: wrk0 + wrk1. This step combines the first and second components of the moving average (wrk0 and wrk1) to produce a preliminary smoothed value.
Calculation of wrk3:
6. wrk3 is updated with the expression: (wrk2 - nz(wrk4 )) * math.pow(1.0 - alpha, 2) + math.pow(alpha, 2) * nz(wrk3 ). This step refines the preliminary smoothed value (wrk2) by accounting for the differences between the current smoothed value and the previous smoothed values (wrk4 and wrk3 ). The alpha parameter is used to weight the contributions of the previous smoothed values, providing a balance between smoothness and responsiveness.
Calculation of wrk4:
7. Calculation of wrk4:
wrk4 is updated with the expression: wrk3 + nz(wrk4 ). This step combines the refined smoothed value (wrk3) with the previous smoothed value (wrk4 , or 0 if it doesn't exist) to produce the final smoothed value. The purpose of this step is to ensure that the resulting moving average incorporates information from past values, making it smoother and more representative of the underlying trend.
8. Return wrk4:
The function returns the final smoothed value wrk4. This value represents the Smoother Moving Average for the given data point in the price series.
In summary, the smoother function calculates a custom moving average by using a series of steps to weight and combine recent price data with past smoothed values. The resulting moving average is more responsive to recent price changes while still maintaining a smooth curve, which helps reveal underlying trends and reduce noise in the data. The alpha parameter plays a key role in balancing the responsiveness and smoothness of the moving average, allowing users to customize the behavior of the algorithm based on their specific needs and preferences.
What is the CCI Adaptive Smoother?
The Commodity Channel Index (CCI) Adaptive Smoother is an innovative technical analysis tool that combines the benefits of the CCI indicator with a Smoother Moving Average. By adapting the CCI calculation based on the current market volatility, this method offers a more responsive and flexible approach to identifying potential trends and trading signals in financial markets.
The CCI is a momentum-based oscillator designed to determine whether an asset is overbought or oversold. It measures the difference between the typical price of an asset and its moving average, divided by the mean absolute deviation of the typical price. The traditional CCI calculation relies on a fixed period, which may not be suitable for all market conditions, as volatility can change over time.
The introduction of the Smoother Moving Average to the CCI calculation addresses this limitation. The Smoother Moving Average is a custom smoothing algorithm that combines elements of exponential moving averages with additional calculations to fine-tune the smoothing effect based on a given parameter. This algorithm assigns more importance to recent data points, making it more sensitive to recent changes in the data.
The CCI Adaptive Smoother dynamically adjusts the period of the Smoother Moving Average based on the current market volatility. This is accomplished by calculating the standard deviation of the close prices over a specified period and then computing the simple moving average of the standard deviation. By comparing the average standard deviation with the current standard deviation, the adaptive period for the Smoother Moving Average can be determined.
This adaptive approach allows the CCI Adaptive Smoother to be more responsive to changing market conditions. In periods of high volatility, the adaptive period will be shorter, resulting in a more responsive moving average. Conversely, in periods of low volatility, the adaptive period will be longer, producing a smoother moving average. This flexibility enables the CCI Adaptive Smoother to better identify trends and potential trading signals in a variety of market environments.
Furthermore, the CCI Adaptive Smoother is a prime example of the evolution of technical analysis methodologies. As markets continue to become more complex and dynamic, it is crucial for analysts and traders to adapt and improve their techniques to stay competitive. The incorporation of adaptive algorithms, like the Smoother Moving Average, demonstrates the potential for blending traditional indicators with cutting-edge methods to create more powerful and versatile tools for market analysis.
The versatility of the CCI Adaptive Smoother makes it suitable for various trading strategies, including trend-following, mean-reversion, and breakout systems. By providing a more precise measurement of overbought and oversold conditions, the CCI Adaptive Smoother can help traders identify potential entry and exit points with greater accuracy. Additionally, its responsiveness to changing market conditions allows for more timely adjustments in trading positions, reducing the risk of holding onto losing trades.
While the CCI Adaptive Smoother is a valuable tool, it is essential to remember that no single indicator can provide a complete picture of the market. As seasoned analysts and traders, we must always consider a holistic approach, incorporating multiple indicators and techniques to confirm signals and validate our trading decisions. By combining the CCI Adaptive Smoother with other technical analysis tools, such as trend lines, support and resistance levels, and candlestick patterns, traders can develop a more comprehensive understanding of the market and make more informed decisions.
The development of the CCI Adaptive Smoother also highlights the increasing importance of computational power and advanced algorithms in the field of technical analysis. As financial markets become more interconnected and influenced by various factors, including macroeconomic events, geopolitical developments, and technological innovations, the need for sophisticated tools to analyze and interpret complex data sets becomes even more critical.
Machine learning and artificial intelligence (AI) are becoming increasingly relevant in the world of trading and investing. These technologies have the potential to revolutionize how technical analysis is performed, by automating the discovery of patterns, relationships, and trends in the data. By leveraging machine learning algorithms and AI-driven techniques, traders can uncover hidden insights, improve decision-making processes, and optimize trading strategies.
The CCI Adaptive Smoother is just one example of how advanced algorithms can enhance traditional technical indicators. As the adoption of machine learning and AI continues to grow in the financial sector, we can expect to see the emergence of even more sophisticated and powerful analysis tools. These innovations will undoubtedly lead to a new era of technical analysis, where the ability to quickly adapt to changing market conditions and extract meaningful insights from complex data becomes increasingly critical for success.
In conclusion, the CCI Adaptive Smoother is an essential step forward in the evolution of technical analysis. It demonstrates the potential for combining traditional indicators with advanced algorithms to create more responsive and versatile tools for market analysis. As technology continues to advance and reshape the financial landscape, it is crucial for traders and analysts to stay informed and embrace innovation. By integrating cutting-edge tools like the CCI Adaptive Smoother into their arsenal, traders can gain a competitive edge and enhance their ability to navigate the increasingly complex world of financial markets.
Additional Features
This indicator allows you to select from 33 source types. They are as follows:
Close
Open
High
Low
Median
Typical
Weighted
Average
Average Median Body
Trend Biased
Trend Biased (Extreme)
HA Close
HA Open
HA High
HA Low
HA Median
HA Typical
HA Weighted
HA Average
HA Average Median Body
HA Trend Biased
HA Trend Biased (Extreme)
HAB Close
HAB Open
HAB High
HAB Low
HAB Median
HAB Typical
HAB Weighted
HAB Average
HAB Average Median Body
HAB Trend Biased
HAB Trend Biased (Extreme)
What are Heiken Ashi "better" candles?
Heiken Ashi "better" candles are a modified version of the standard Heiken Ashi candles, which are a popular charting technique used in technical analysis. Heiken Ashi candles help traders identify trends and potential reversal points by smoothing out price data and reducing market noise. The "better formula" was proposed by Sebastian Schmidt in an article published by BNP Paribas in Warrants & Zertifikate, a German magazine, in August 2004. The aim of this formula is to further improve the smoothing of the Heiken Ashi chart and enhance its effectiveness in identifying trends and reversals.
Standard Heiken Ashi candles are calculated using the following formulas:
Heiken Ashi Close = (Open + High + Low + Close) / 4
Heiken Ashi Open = (Previous Heiken Ashi Open + Previous Heiken Ashi Close) / 2
Heiken Ashi High = Max (High, Heiken Ashi Open, Heiken Ashi Close)
Heiken Ashi Low = Min (Low, Heiken Ashi Open, Heiken Ashi Close)
The "better formula" modifies the standard Heiken Ashi calculation by incorporating additional smoothing, which can help reduce noise and make it easier to identify trends and reversals. The modified formulas for Heiken Ashi "better" candles are as follows:
Better Heiken Ashi Close = (Open + High + Low + Close) / 4
Better Heiken Ashi Open = (Previous Better Heiken Ashi Open + Previous Better Heiken Ashi Close) / 2
Better Heiken Ashi High = Max (High, Better Heiken Ashi Open, Better Heiken Ashi Close)
Better Heiken Ashi Low = Min (Low, Better Heiken Ashi Open, Better Heiken Ashi Close)
Smoothing Factor = 2 / (N + 1), where N is the chosen period for smoothing
Smoothed Better Heiken Ashi Open = (Better Heiken Ashi Open * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Open * (1 - Smoothing Factor))
Smoothed Better Heiken Ashi Close = (Better Heiken Ashi Close * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Close * (1 - Smoothing Factor))
The smoothed Better Heiken Ashi Open and Close values are then used to calculate the smoothed Better Heiken Ashi High and Low values, resulting in "better" candles that provide a clearer representation of the market trend and potential reversal points.
It's important to note that, like any other technical analysis tool, Heiken Ashi "better" candles are not foolproof and should be used in conjunction with other indicators and analysis techniques to make well-informed trading decisions.
Heiken Ashi "better" candles, as mentioned previously, provide a clearer representation of market trends and potential reversal points by reducing noise and smoothing out price data. When using these candles in conjunction with other technical analysis tools and indicators, traders can gain valuable insights into market behavior and make more informed decisions.
To effectively use Heiken Ashi "better" candles in your trading strategy, consider the following tips:
Trend Identification: Heiken Ashi "better" candles can help you identify the prevailing trend in the market. When the majority of the candles are green (or another color, depending on your chart settings) and there are no or few lower wicks, it may indicate a strong uptrend. Conversely, when the majority of the candles are red (or another color) and there are no or few upper wicks, it may signal a strong downtrend.
Trend Reversals: Look for potential trend reversals when a change in the color of the candles occurs, especially when accompanied by longer wicks. For example, if a green candle with a long lower wick is followed by a red candle, it could indicate a bearish reversal. Similarly, a red candle with a long upper wick followed by a green candle may suggest a bullish reversal.
Support and Resistance: You can use Heiken Ashi "better" candles to identify potential support and resistance levels. When the candles are consistently moving in one direction and then suddenly change color with longer wicks, it could indicate the presence of a support or resistance level.
Stop-Loss and Take-Profit: Using Heiken Ashi "better" candles can help you manage risk by determining optimal stop-loss and take-profit levels. For instance, you can place your stop-loss below the low of the most recent green candle in an uptrend or above the high of the most recent red candle in a downtrend.
Confirming Signals: Heiken Ashi "better" candles should be used in conjunction with other technical indicators, such as moving averages, oscillators, or chart patterns, to confirm signals and improve the accuracy of your analysis.
In this implementation, you have the choice of AMA, KAMA, or T3 smoothing. These are as follows:
Kaufman Adaptive Moving Average (KAMA)
The Kaufman Adaptive Moving Average (KAMA) is a type of adaptive moving average used in technical analysis to smooth out price fluctuations and identify trends. The KAMA adjusts its smoothing factor based on the market's volatility, making it more responsive in volatile markets and smoother in calm markets. The KAMA is calculated using three different efficiency ratios that determine the appropriate smoothing factor for the current market conditions. These ratios are based on the noise level of the market, the speed at which the market is moving, and the length of the moving average. The KAMA is a popular choice among traders who prefer to use adaptive indicators to identify trends and potential reversals.
Adaptive Moving Average
The Adaptive Moving Average (AMA) is a type of moving average that adjusts its sensitivity to price movements based on market conditions. It uses a ratio between the current price and the highest and lowest prices over a certain lookback period to determine its level of smoothing. The AMA can help reduce lag and increase responsiveness to changes in trend direction, making it useful for traders who want to follow trends while avoiding false signals. The AMA is calculated by multiplying a smoothing constant with the difference between the current price and the previous AMA value, then adding the result to the previous AMA value.
T3
The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm.
The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction.
The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: CCI Adaptive Smoother as shown on the chart above
Confirmation 2: Williams Percent Range
Continuation: CCI Adaptive Smoother
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
1-Candle Rule Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close)
2. GKD-B Volatility/Volume agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
2. GKD-C Confirmation 1 agrees
3. GKD-C Confirmation 2 agrees
4. GKD-V Volatility/Volume Agrees
]█ Setting up the GKD
The GKD system involves chaining indicators together. These are the steps to set this up.
Use a GKD-C indicator alone on a chart
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
Use a GKD-V indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Use a GKD-B indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Baseline (Baseline, Backtest)
1. Import the GKD-B Baseline into the GKD-BT Backtest: "Input into Volatility/Volume or Backtest (Baseline testing)"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline"
Volatility/Volume (Volatility/Volume, Backte st)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Solo"
2. Inside the GKD-V indicator, change the "Signal Type" setting to "Crossing" (neither traditional nor both can be backtested)
3. Import the GKD-V indicator into the GKD-BT Backtest: "Input into C1 or Backtest"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Volatility/Volume"
5. Inside the GKD-BT Backtest, a) change the setting "Backtest Type" to "Trading" if using a directional GKD-V indicator; or, b) change the setting "Backtest Type" to "Full" if using a directional or non-directional GKD-V indicator (non-directional GKD-V can only test Longs and Shorts separately)
6. If "Backtest Type" is set to "Full": Inside the GKD-BT Backtest, change the setting "Backtest Side" to "Long" or "Short
7. If "Backtest Type" is set to "Full": To allow the system to open multiple orders at one time so you test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Solo Confirmation Simple (Confirmation, Backtest)
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
1. Import the GKD-C indicator into the GKD-BT Backtest: "Input into Backtest"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Solo Confirmation Simple"
Solo Confirmation Complex without Exits (Baseline, Volatility/Volume, Confirmation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
6. Import the GKD-C into the GKD-BT Backtest: "Input into Exit or Backtest"
Solo Confirmation Complex with Exits (Baseline, Volatility/Volume, Confirmation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Import the GKD-C indicator into the GKD-E indicator: "Input into Exit"
6. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
7. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Full GKD without Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
9. Import the GKD-E into the GKD-BT Backtest: "Input into Exit or Backtest"
Full GKD with Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Import the GKD-C Continuation indicator into the GKD-E indicator: "Input into Exit"
9. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
10. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Baseline + Volatility/Volume (Baseline, Volatility/Volume, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Baseline + Volatility/Volume"
2. Inside the GKD-V indicator, make sure the "Signal Type" setting is set to "Traditional"
3. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline + Volatility/Volume"
5. Import the GKD-V into the GKD-BT Backtest: "Input into C1 or Backtest"
6. Inside the GKD-BT Backtest, change the setting "Backtest Type" to "Full". For this backtest, you must test Longs and Shorts separately
7. To allow the system to open multiple orders at one time so you can test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Requirements
Inputs
Confirmation 1: GKD-V Volatility / Volume indicator
Confirmation 2: GKD-C Confirmation indicator
Continuation: GKD-C Confirmation indicator
Solo Confirmation Simple: GKD-B Baseline
Solo Confirmation Complex: GKD-V Volatility / Volume indicator
Solo Confirmation Super Complex: GKD-V Volatility / Volume indicator
Stacked 1: None
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 1
Outputs
Confirmation 1: GKD-C Confirmation 2 indicator
Confirmation 2: GKD-C Continuation indicator
Continuation: GKD-E Exit indicator
Solo Confirmation Simple: GKD-BT Backtest
Solo Confirmation Complex: GKD-BT Backtest or GKD-E Exit indicator
Solo Confirmation Super Complex: GKD-C Continuation indicator
Stacked 1: GKD-C, GKD-V, or GKD-B Stacked 2+
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 2+ or GKD-BT Backtest
Additional features will be added in future releases.
GKD-C Adaptive-Lookback Phase Change Index [Loxx]Giga Kaleidoscope GKD-C Adaptive-Lookback Phase Change Index is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ GKD-C Adaptive-Lookback Phase Change Index
What is the Phase Change Index?
The Phase Change Index (PCI) is a technical indicator that has gained popularity among traders in recent years. It is used to identify market phases and make profitable trades based on momentum and price data. The PCI was developed by M.H. Pee and first introduced in the Stocks & Commodities magazine in 2004.
The PCI is calculated using the 35-day momentum and the 35-day price channel index (PCI). The momentum is the difference between the current day's close and the close 35 days ago, while the PCI measures the distance between the highest high and lowest low over a period of 35 days. By combining these two indicators, traders can identify six possible market phases, each with its own trading strategy.
The formula for calculating the Phase Change Index (PCI) is as follows:
PCI = 100 * (C - L) / (H - L)
Where:
- C is the closing price of the current day
- L is the lowest low over a period of 35 days
- H is the highest high over a period of 35 days
The formula for calculating momentum is as follows:
Momentum = C - Cn
Where:
- C is the closing price of the current day
- Cn is the closing price n days ago, where n = 35 in this case.
The first two phases are characterized by negative momentum, with phase one having a low PCI value (less than 20) and phase two having a high PCI value (greater than 80). In these phases, traders should enter short positions. The next two phases have positive momentum, with phase three having a low PCI value and phase four having a high PCI value. In these phases, traders should enter long positions.
The final two phases are characterized by neutral momentum, with phase five having a low PCI value and phase six having a high PCI value. In these phases, traders should maintain their previous positions until there is a clear signal to enter or exit.
Traders can also use other technical indicators in conjunction with the PCI to confirm signals or filter out false signals. For example, some traders use moving averages or trendlines to confirm trend direction before entering a trade based on the PCI.
In conclusion, the Phase Change Index is a powerful technical indicator that can help traders identify market phases and make profitable trades. By combining momentum and price data, traders can enter long or short positions based on the six possible market phases. Backtesting results have shown that the PCI is robust across parameters, markets, and years. However, it is important to use proper risk management and not rely solely on past profitability when making trading decisions.
What is the Jurik Filter?
The Jurik Filter is a technical analysis tool that is used to filter out market noise and identify trends in financial markets. It was developed by Mark Jurik in the 1990s and is based on a non-linear smoothing algorithm that provides a more accurate representation of price movements.
Traditional moving averages, such as the Simple Moving Average ( SMA ) or Exponential Moving Average ( EMA ), are linear filters that produce a lag between price and the moving average line. This can cause false signals during periods of market volatility , which can result in losses for traders and investors.
The Jurik Filter is designed to address this issue by incorporating a damping factor into the smoothing algorithm. This damping factor adjusts the filter's responsiveness to the changes in price, allowing it to filter out market noise without overshooting price peaks and valleys.
The Jurik Filter is calculated using a mathematical formula that takes into account the current and past prices of an asset, as well as the volatility of the market. This formula incorporates the damping factor and produces a smoother price curve than traditional moving average filters.
One of the advantages of the Jurik Filter is its ability to adjust to changing market conditions. The damping factor can be adjusted to suit different securities and time frames, making it a versatile tool for traders and investors.
Traders and investors often use the Jurik Filter in conjunction with other technical analysis tools, such as the MACD or RSI , to confirm or complement their trading strategies. By filtering out market noise and identifying trends in the financial markets, the Jurik Filter can help improve the accuracy of trading signals and reduce the risks of false signals during periods of market volatility .
Overall, the Jurik Filter is a powerful technical analysis tool that can help traders and investors make more informed decisions about buying and selling securities. By providing a smoother price curve and reducing false signals, it can help improve trading performance and reduce risk in volatile markets.
What is the Adaptive Lookback Period?
The adaptive lookback period is a technique used in technical analysis to adjust the period of an indicator based on changes in market conditions. This technique is particularly useful in volatile or rapidly changing markets where a fixed period may not be optimal for detecting trends or signals.
The concept of the adaptive lookback period is relatively simple. By adjusting the lookback period based on changes in market conditions, traders can more accurately identify trends and signals. This can help traders to enter and exit trades at the right time and improve the profitability of their trading strategies.
The adaptive lookback period works by identifying potential swing points in the market. Once these points are identified, the lookback period is calculated based on the number of swings and a speed parameter. The swing count parameter determines the number of swings that must occur before the lookback period is adjusted. The speed parameter controls the rate at which the lookback period is adjusted, with higher values indicating a more rapid adjustment.
The adaptive lookback period can be applied to a wide range of technical indicators, including moving averages, oscillators, and trendlines. By adjusting the period of these indicators based on changes in market conditions, traders can reduce the impact of noise and false signals, leading to more profitable trades.
In summary, the adaptive lookback period is a powerful technique for traders and analysts looking to optimize their technical indicators. By adjusting the period based on changes in market conditions, traders can more accurately identify trends and signals, leading to more profitable trades. While there are various ways to implement the adaptive lookback period, the basic concept remains the same, and traders can adapt and customize the technique to suit their individual needs and trading styles.
What is the Adaptive-Lookback Phase Change Index?
The combination of adaptive lookback and Jurik filtering is an effective technique used in technical analysis to filter out market noise and improve the accuracy of trading signals. When applied to the Phase Change Index (PCI) indicator, the adaptive lookback period can be used to adjust the period of the indicator based on changes in market conditions. Jurik filtering can then be used to filter out market noise and improve the accuracy of the signals produced by the PCI indicator.
The adaptive lookback period is particularly useful in volatile or rapidly changing markets where a fixed period may not be optimal for detecting trends or signals. By adjusting the lookback period based on changes in market conditions, traders can more accurately identify trends and signals, leading to more profitable trades.
Jurik filtering is a more advanced filtering technique that uses a combination of smoothing and phase shift to produce a more accurate signal. This technique is particularly useful in filtering out market noise and improving the accuracy of trading signals. Jurik filtering can be applied to various indicators, including moving averages, oscillators, and trendlines.
Overall, the combination of adaptive lookback and Jurik filtering is a powerful technique used in technical analysis to filter out market noise and improve the accuracy of trading signals. When applied to the Phase Change Index (PCI) indicator, this technique is particularly effective in identifying trend changes and producing more accurate signals for entry and exit points in trading strategies.
Keep in mind, this is an inverse indicator meaning that above the middle-line/signal is short, below is long.
Additional Features
This indicator allows you to select from 33 source types. They are as follows:
Close
Open
High
Low
Median
Typical
Weighted
Average
Average Median Body
Trend Biased
Trend Biased (Extreme)
HA Close
HA Open
HA High
HA Low
HA Median
HA Typical
HA Weighted
HA Average
HA Average Median Body
HA Trend Biased
HA Trend Biased (Extreme)
HAB Close
HAB Open
HAB High
HAB Low
HAB Median
HAB Typical
HAB Weighted
HAB Average
HAB Average Median Body
HAB Trend Biased
HAB Trend Biased (Extreme)
What are Heiken Ashi "better" candles?
Heiken Ashi "better" candles are a modified version of the standard Heiken Ashi candles, which are a popular charting technique used in technical analysis. Heiken Ashi candles help traders identify trends and potential reversal points by smoothing out price data and reducing market noise. The "better formula" was proposed by Sebastian Schmidt in an article published by BNP Paribas in Warrants & Zertifikate, a German magazine, in August 2004. The aim of this formula is to further improve the smoothing of the Heiken Ashi chart and enhance its effectiveness in identifying trends and reversals.
Standard Heiken Ashi candles are calculated using the following formulas:
Heiken Ashi Close = (Open + High + Low + Close) / 4
Heiken Ashi Open = (Previous Heiken Ashi Open + Previous Heiken Ashi Close) / 2
Heiken Ashi High = Max (High, Heiken Ashi Open, Heiken Ashi Close)
Heiken Ashi Low = Min (Low, Heiken Ashi Open, Heiken Ashi Close)
The "better formula" modifies the standard Heiken Ashi calculation by incorporating additional smoothing, which can help reduce noise and make it easier to identify trends and reversals. The modified formulas for Heiken Ashi "better" candles are as follows:
Better Heiken Ashi Close = (Open + High + Low + Close) / 4
Better Heiken Ashi Open = (Previous Better Heiken Ashi Open + Previous Better Heiken Ashi Close) / 2
Better Heiken Ashi High = Max (High, Better Heiken Ashi Open, Better Heiken Ashi Close)
Better Heiken Ashi Low = Min (Low, Better Heiken Ashi Open, Better Heiken Ashi Close)
Smoothing Factor = 2 / (N + 1), where N is the chosen period for smoothing
Smoothed Better Heiken Ashi Open = (Better Heiken Ashi Open * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Open * (1 - Smoothing Factor))
Smoothed Better Heiken Ashi Close = (Better Heiken Ashi Close * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Close * (1 - Smoothing Factor))
The smoothed Better Heiken Ashi Open and Close values are then used to calculate the smoothed Better Heiken Ashi High and Low values, resulting in "better" candles that provide a clearer representation of the market trend and potential reversal points.
It's important to note that, like any other technical analysis tool, Heiken Ashi "better" candles are not foolproof and should be used in conjunction with other indicators and analysis techniques to make well-informed trading decisions.
Heiken Ashi "better" candles, as mentioned previously, provide a clearer representation of market trends and potential reversal points by reducing noise and smoothing out price data. When using these candles in conjunction with other technical analysis tools and indicators, traders can gain valuable insights into market behavior and make more informed decisions.
To effectively use Heiken Ashi "better" candles in your trading strategy, consider the following tips:
Trend Identification: Heiken Ashi "better" candles can help you identify the prevailing trend in the market. When the majority of the candles are green (or another color, depending on your chart settings) and there are no or few lower wicks, it may indicate a strong uptrend. Conversely, when the majority of the candles are red (or another color) and there are no or few upper wicks, it may signal a strong downtrend.
Trend Reversals: Look for potential trend reversals when a change in the color of the candles occurs, especially when accompanied by longer wicks. For example, if a green candle with a long lower wick is followed by a red candle, it could indicate a bearish reversal. Similarly, a red candle with a long upper wick followed by a green candle may suggest a bullish reversal.
Support and Resistance: You can use Heiken Ashi "better" candles to identify potential support and resistance levels. When the candles are consistently moving in one direction and then suddenly change color with longer wicks, it could indicate the presence of a support or resistance level.
Stop-Loss and Take-Profit: Using Heiken Ashi "better" candles can help you manage risk by determining optimal stop-loss and take-profit levels. For instance, you can place your stop-loss below the low of the most recent green candle in an uptrend or above the high of the most recent red candle in a downtrend.
Confirming Signals: Heiken Ashi "better" candles should be used in conjunction with other technical indicators, such as moving averages, oscillators, or chart patterns, to confirm signals and improve the accuracy of your analysis.
In this implementation, you have the choice of AMA, KAMA, or T3 smoothing. These are as follows:
Kaufman Adaptive Moving Average (KAMA)
The Kaufman Adaptive Moving Average (KAMA) is a type of adaptive moving average used in technical analysis to smooth out price fluctuations and identify trends. The KAMA adjusts its smoothing factor based on the market's volatility, making it more responsive in volatile markets and smoother in calm markets. The KAMA is calculated using three different efficiency ratios that determine the appropriate smoothing factor for the current market conditions. These ratios are based on the noise level of the market, the speed at which the market is moving, and the length of the moving average. The KAMA is a popular choice among traders who prefer to use adaptive indicators to identify trends and potential reversals.
Adaptive Moving Average
The Adaptive Moving Average (AMA) is a type of moving average that adjusts its sensitivity to price movements based on market conditions. It uses a ratio between the current price and the highest and lowest prices over a certain lookback period to determine its level of smoothing. The AMA can help reduce lag and increase responsiveness to changes in trend direction, making it useful for traders who want to follow trends while avoiding false signals. The AMA is calculated by multiplying a smoothing constant with the difference between the current price and the previous AMA value, then adding the result to the previous AMA value.
T3
The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm.
The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction.
The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Adaptive-Lookback Phase Change Index as shown on the chart above
Confirmation 2: Williams Percent Range
Continuation: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
1-Candle Rule Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close)
2. GKD-B Volatility/Volume agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
2. GKD-C Confirmation 1 agrees
3. GKD-C Confirmation 2 agrees
4. GKD-V Volatility/Volume Agrees
]█ Setting up the GKD
The GKD system involves chaining indicators together. These are the steps to set this up.
Use a GKD-C indicator alone on a chart
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
Use a GKD-V indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Use a GKD-B indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Baseline (Baseline, Backtest)
1. Import the GKD-B Baseline into the GKD-BT Backtest: "Input into Volatility/Volume or Backtest (Baseline testing)"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline"
Volatility/Volume (Volatility/Volume, Backte st)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Solo"
2. Inside the GKD-V indicator, change the "Signal Type" setting to "Crossing" (neither traditional nor both can be backtested)
3. Import the GKD-V indicator into the GKD-BT Backtest: "Input into C1 or Backtest"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Volatility/Volume"
5. Inside the GKD-BT Backtest, a) change the setting "Backtest Type" to "Trading" if using a directional GKD-V indicator; or, b) change the setting "Backtest Type" to "Full" if using a directional or non-directional GKD-V indicator (non-directional GKD-V can only test Longs and Shorts separately)
6. If "Backtest Type" is set to "Full": Inside the GKD-BT Backtest, change the setting "Backtest Side" to "Long" or "Short
7. If "Backtest Type" is set to "Full": To allow the system to open multiple orders at one time so you test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Solo Confirmation Simple (Confirmation, Backtest)
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
1. Import the GKD-C indicator into the GKD-BT Backtest: "Input into Backtest"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Solo Confirmation Simple"
Solo Confirmation Complex without Exits (Baseline, Volatility/Volume, Confirmation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
6. Import the GKD-C into the GKD-BT Backtest: "Input into Exit or Backtest"
Solo Confirmation Complex with Exits (Baseline, Volatility/Volume, Confirmation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Import the GKD-C indicator into the GKD-E indicator: "Input into Exit"
6. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
7. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Full GKD without Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
9. Import the GKD-E into the GKD-BT Backtest: "Input into Exit or Backtest"
Full GKD with Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Import the GKD-C Continuation indicator into the GKD-E indicator: "Input into Exit"
9. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
10. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Baseline + Volatility/Volume (Baseline, Volatility/Volume, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Baseline + Volatility/Volume"
2. Inside the GKD-V indicator, make sure the "Signal Type" setting is set to "Traditional"
3. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline + Volatility/Volume"
5. Import the GKD-V into the GKD-BT Backtest: "Input into C1 or Backtest"
6. Inside the GKD-BT Backtest, change the setting "Backtest Type" to "Full". For this backtest, you must test Longs and Shorts separately
7. To allow the system to open multiple orders at one time so you can test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Requirements
Inputs
Confirmation 1: GKD-V Volatility / Volume indicator
Confirmation 2: GKD-C Confirmation indicator
Continuation: GKD-C Confirmation indicator
Solo Confirmation Simple: GKD-B Baseline
Solo Confirmation Complex: GKD-V Volatility / Volume indicator
Solo Confirmation Super Complex: GKD-V Volatility / Volume indicator
Stacked 1: None
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 1
Outputs
Confirmation 1: GKD-C Confirmation 2 indicator
Confirmation 2: GKD-C Continuation indicator
Continuation: GKD-E Exit indicator
Solo Confirmation Simple: GKD-BT Backtest
Solo Confirmation Complex: GKD-BT Backtest or GKD-E Exit indicator
Solo Confirmation Super Complex: GKD-C Continuation indicator
Stacked 1: GKD-C, GKD-V, or GKD-B Stacked 2+
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 2+ or GKD-BT Backtest
Additional features will be added in future releases.
GKD-C Super 6x [Loxx]Giga Kaleidoscope GKD-C Super 6x: RSI, MACD, Stochastic, Loxxer, CCI, & Velocity is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ Giga Kaleidoscope Modularized Trading System
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is the NNFX algorithmic trading strategy?
The NNFX (No-Nonsense Forex) trading system is a comprehensive approach to Forex trading that is designed to simplify the process and remove the confusion and complexity that often surrounds trading. The system was developed by a Forex trader who goes by the pseudonym "VP" and has gained a significant following in the Forex community.
The NNFX trading system is based on a set of rules and guidelines that help traders make objective and informed decisions. These rules cover all aspects of trading, including market analysis, trade entry, stop loss placement, and trade management.
Here are the main components of the NNFX trading system:
1. Trading Philosophy: The NNFX trading system is based on the idea that successful trading requires a comprehensive understanding of the market, objective analysis, and strict risk management. The system aims to remove subjective elements from trading and focuses on objective rules and guidelines.
2. Technical Analysis: The NNFX trading system relies heavily on technical analysis and uses a range of indicators to identify high-probability trading opportunities. The system uses a combination of trend-following and mean-reverting strategies to identify trades.
3. Market Structure: The NNFX trading system emphasizes the importance of understanding the market structure, including price action, support and resistance levels, and market cycles. The system uses a range of tools to identify the market structure, including trend lines, channels, and moving averages.
4. Trade Entry: The NNFX trading system has strict rules for trade entry. The system uses a combination of technical indicators to identify high-probability trades, and traders must meet specific criteria to enter a trade.
5. Stop Loss Placement: The NNFX trading system places a significant emphasis on risk management and requires traders to place a stop loss order on every trade. The system uses a combination of technical analysis and market structure to determine the appropriate stop loss level.
6. Trade Management: The NNFX trading system has specific rules for managing open trades. The system aims to minimize risk and maximize profit by using a combination of trailing stops, take profit levels, and position sizing.
Overall, the NNFX trading system is designed to be a straightforward and easy-to-follow approach to Forex trading that can be applied by traders of all skill levels.
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Super 6x: RSI, MACD, Stochastic, Loxxer, CCI, & Velocity as shown on the chart above
Confirmation 2: Williams Percent Range
Continuation: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
█ GKD-C Super 6x: RSI, MACD, Stochastic, Loxxer, CCI, & Velocity
What is MACD?
MACD stands for Moving Average Convergence Divergence. It is a technical indicator used in financial analysis to track the trend and momentum of a security or market index. The MACD indicator consists of two lines, a faster-moving average called the MACD line, and a slower-moving average called the signal line.
The MACD line is calculated by subtracting the 26-period exponential moving average (EMA) from the 12-period EMA. The signal line is a 9-period EMA of the MACD line. The MACD line oscillates above and below the zero line, which represents the equilibrium point between the bullish and bearish forces.
Traders use the MACD indicator to identify changes in trend and momentum. When the MACD line crosses above the signal line, it is considered a bullish signal, indicating that the momentum is shifting towards the upside. Conversely, when the MACD line crosses below the signal line, it is considered a bearish signal, indicating that the momentum is shifting towards the downside.
The MACD indicator can also be used to identify divergences between the MACD line and the price action. A bullish divergence occurs when the price is making lower lows, but the MACD line is making higher lows. This could indicate that the downward momentum is weakening, and a potential trend reversal could be imminent. A bearish divergence occurs when the price is making higher highs, but the MACD line is making lower highs, indicating that the upward momentum is weakening, and a potential trend reversal could be imminent.
Overall, the MACD indicator is a versatile tool that can be used in conjunction with other technical indicators and chart patterns to make informed trading decisions.
What is CCI?
The Commodity Channel Index ( CCI ) is a technical analysis indicator that was developed by Donald Lambert in 1980. It's primarily used to identify overbought and oversold conditions in the market, as well as trend direction and potential price reversals.
The CCI is calculated by taking the difference between the typical price (the average of the high, low, and close prices) and a moving average of the typical price over a certain period of time. This difference is then divided by a factor based on the average deviation of the typical price from the moving average.
The formula for the CCI is:
CCI = (Typical Price - 20-period SMA of Typical Price) / (0.015 x Mean Deviation)
Where:
Typical Price = (High + Low + Close) / 3
SMA = Simple Moving Average
Mean Deviation = Average of the absolute value of the difference between the Typical Price and the SMA over the last 20 periods.
The CCI is usually displayed as a line chart that oscillates around a centerline of zero. Readings above zero indicate that the typical price is above the moving average, while readings below zero indicate that the typical price is below the moving average.
Traders typically use the CCI to identify overbought and oversold conditions in the market. When the CCI rises above a certain level (e.g., +100), it's considered overbought, indicating that the price may be due for a correction or reversal. When the CCI falls below a certain level (e.g., -100), it's considered oversold, indicating that the price may be due for a bounce or reversal.
The CCI can also be used to identify potential trend reversals. When the CCI crosses above or below the zero line, it can signal a potential change in trend. For example, if the CCI crosses above the zero line, it could indicate that a bullish trend is emerging, while a cross below the zero line could indicate that a bearish trend is emerging.
Overall, the Commodity Channel Index is a useful technical analysis tool for identifying overbought and oversold conditions, as well as potential trend reversals in the market. However, like all technical indicators, it should be used in conjunction with other forms of analysis and risk management techniques to make informed trading decisions.
What is RSI?
The RSI, or Relative Strength Index, is a popular technical analysis tool used to measure the strength of a security's price action and identify potential trend reversals. It was developed by J. Welles Wilder and is based on the concept that price action tends to follow a momentum pattern.
The RSI is calculated based on the average gain and loss of a security's price over a specified period, usually 14 periods. It oscillates between 0 and 100 and is represented as a single line on a chart.
The RSI is calculated as follows:
RS = Average Gain / Average Loss
RSI = 100 - (100 / (1 + RS))
Where the Average Gain is the sum of all gains divided by the number of periods, and the Average Loss is the sum of all losses divided by the number of periods.
The RSI is used to identify overbought and oversold conditions in a security or market index. When the RSI rises above 70, it is considered overbought, indicating that the security may be overvalued and due for a price correction. Conversely, when the RSI falls below 30, it is considered oversold, indicating that the security may be undervalued and due for a price rebound.
Traders can also use the RSI to identify potential trend reversals. When the RSI forms a divergent pattern with the price action, it could indicate that the security is losing momentum and may be reversing to the upside or downside.
Overall, the RSI is a useful tool for traders to identify potential buy and sell signals, as well as to confirm trends and reversals. However, it should not be used in isolation, and traders should consider using other technical indicators and fundamental analysis to make informed trading decisions.
What is Stochastic?
The stochastic oscillator is a momentum indicator used in technical analysis to measure the current closing price of a security or market index relative to its price range over a specified period. The indicator consists of two lines, the %K line and the %D line, which oscillate between 0 and 100.
The %K line is calculated as follows:
%K = 100 x (Closing Price - Lowest Low) / (Highest High - Lowest Low)
Where:
Closing Price is the most recent closing price of the security.
Lowest Low is the lowest low of the security over a specified period (usually 14 periods).
Highest High is the highest high of the security over the same specified period.
The %D line is a 3-period simple moving average of the %K line. The %D line is slower than the %K line and is used to smooth out the volatility of the %K line.
The stochastic oscillator is used to identify overbought and oversold conditions in a security or market index. When the %K line rises above 80, it is considered overbought, indicating that the security may be overvalued and due for a price correction. Conversely, when the %K line falls below 20, it is considered oversold, indicating that the security may be undervalued and due for a price rebound.
Traders can also use the stochastic oscillator to identify bullish and bearish divergences between the %K line and the price action. A bullish divergence occurs when the %K line is making higher lows while the price action is making lower lows, indicating that the momentum is shifting towards the upside. A bearish divergence occurs when the %K line is making lower highs while the price action is making higher highs, indicating that the momentum is shifting towards the downside.
Overall, the stochastic oscillator is a useful tool for traders to identify potential buy and sell signals, as well as to confirm trends and reversals. However, it should not be used in isolation, and traders should consider using other technical indicators and fundamental analysis to make informed trading decisions.
What is Loxxer?
The Loxxer Index is a technical indicator used in financial analysis to identify potential trend reversals and overbought/oversold conditions in a security or market index. It was developed by Loxx and is also known as the Loxx Indicator.
The Loxxer Index is calculated based on the high, low, and closing prices of a security over a specified period. It measures the demand for the security by comparing the current high and low prices with the previous high and low prices. The indicator oscillates between 0 and 1 and is represented as a single line on a chart.
The Loxxer Index is calculated as follows:
LoxxMax = Current High - Previous High
LoxxMin = Previous Low - Current Low
If LoxxMax is greater than LoxxMin, then the Loxxer Index is calculated as follows:
Loxxer = LoxxMax / (LoxxMax + Current Close - Previous Close)
If LoxxMax is less than or equal to LoxxMin, then the Loxxer Index is calculated as follows:
Loxxer = 0
The Loxxer Index is used to identify overbought and oversold conditions in a security or market index. When the Loxxer Index rises above 0.7, it is considered overbought, indicating that the security may be overvalued and due for a price correction. Conversely, when the Loxxer Index falls below 0.3, it is considered oversold, indicating that the security may be undervalued and due for a price rebound.
Traders can also use the Loxxer Index to identify potential trend reversals. When the Loxxer Index forms a higher low while the price action forms a lower low, it could indicate that the security is losing momentum and may be reversing to the upside. Conversely, when the Loxxer Index forms a lower high while the price action forms a higher high, it could indicate that the security is losing momentum and may be reversing to the downside.
Overall, the Loxxer Index is a useful tool for traders to identify potential buy and sell signals, as well as to confirm trends and reversals. However, it should not be used in isolation, and traders should consider using other technical indicators and fundamental analysis to make informed trading decisions.
What is Velocity?
The Velocity Indicator is a technical analysis tool used to measure the speed and momentum of price movements in a security or market index. It is a type of oscillator that is used to identify potential trend reversals and overbought/oversold conditions.
The Velocity Indicator is calculated based on the difference between the current price and the price from a specified number of periods ago. It measures the rate of change of the price movement over time and is represented as a single line on a chart.
The Velocity Indicator is calculated as follows:
Velocity = (Current Price - Price from N periods ago) / Price from N periods ago x 100
Where N is the number of periods used in the calculation.
The Velocity Indicator is used to identify overbought and oversold conditions in a security or market index. When the Velocity Indicator rises above 1, it is considered overbought, indicating that the security may be overvalued and due for a price correction. Conversely, when the Velocity Indicator falls below -1, it is considered oversold, indicating that the security may be undervalued and due for a price rebound.
Traders can also use the Velocity Indicator to identify potential trend reversals. When the Velocity Indicator crosses above its moving average, it could indicate that the security is gaining momentum and may be reversing to the upside. Conversely, when the Velocity Indicator crosses below its moving average, it could indicate that the security is losing momentum and may be reversing to the downside.
Overall, the Velocity Indicator is a useful tool for traders to identify potential buy and sell signals, as well as to confirm trends and reversals. However, it should not be used in isolation, and traders should consider using other technical indicators and fundamental analysis to make informed trading decisions.
What is Super 6x: RSI, MACD, Stochastic, Loxxer, CCI, & Velocity?
Super 6x combines all 6 indicators into one signal, long or short
Requirements
Inputs
Confirmation 1 and Solo Confirmation: GKD-V Volatility / Volume indicator
Confirmation 2: GKD-C Confirmation indicator
Outputs
Confirmation 2 and Solo Confirmation Complex: GKD-E Exit indicator
Confirmation 1: GKD-C Confirmation indicator
Continuation: GKD-E Exit indicator
Solo Confirmation Simple: GKD-BT Backtest strategy
Additional features will be added in future releases.
Double Candle Trend Counter [theEccentricTrader]█ OVERVIEW
This indicator counts the number of confirmed double candle trend scenarios on any given candlestick chart and displays the statistics in a table, which can be repositioned and resized at the user's discretion.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a close price equal to or above the price it opened.
• A red candle is one that closes with a close price that is lower than the price it opened.
Upper Candle Trends
• A higher high candle is one that closes with a higher high price than the high price of the preceding candle.
• A lower high candle is one that closes with a lower high price than the high price of the preceding candle.
• A double-top candle is one that closes with a high price that is equal to the high price of the preceding candle.
Lower Candle Trends
• A higher low candle is one that closes with a higher low price than the low price of the preceding candle.
• A lower low candle is one that closes with a lower low price than the low price of the preceding candle.
• A double-bottom candle is one that closes with a low price that is equal to the low price of the preceding candle.
Muti-Part Upper and Lower Candle Trends
• A multi-part higher high trend begins with the formation of a new higher high and continues until a new lower high ends the trend.
• A multi-part lower high trend begins with the formation of a new lower high and continues until a new higher high ends the trend.
• A multi-part higher low trend begins with the formation of a new higher low and continues until a new lower low ends the trend.
• A multi-part lower low trend begins with the formation of a new lower low and continues until a new higher low ends the trend.
Double Candle Trends
• A double uptrend candle trend is formed when a candle closes with both a higher high and a higher low.
• A double downtrend candle trend is formed when a candle closes with both a lower high and a lower low.
Multi-Part Double Candle Trends
• A multi-part double uptrend candle trend begins with the formation of a new double uptrend candle trend and continues until a new lower high or lower low ends the trend.
• A multi-part double downtrend candle trend begins with the formation of a new double downtrend candle trend and continues until a new higher high or higher low ends the trend.
█ FEATURES
Inputs
• Start Date
• End Date
• Position
• Text Size
• Show Plots
Table
The table is colour coded, consists of seven columns and, as many as, thirty-two rows. Blue cells denote the multi-part trend scenarios, green cells denote the corresponding double uptrend candle trend scenarios and red cells denote the corresponding double downtrend candle trend scenarios.
The multi-part double candle trend scenarios are listed in the first column with their corresponding total counts to the right, in the second and fifth columns. The last row in column one, displays the sample period which can be adjusted or hidden via indicator settings.
The third and sixth columns display the double candle trend scenarios as percentages of total 1-part double candle trends. And columns four and seven display the total double candle trend scenarios as percentages of the last, or preceding double candle trend part. For example 4-part double uptrend candle trends as percentages of 3-part double uptrend candle trends.
Plots
I have added plots as a visual aid to the double candle trend scenarios. Green up-arrows, with the number of the trend part, denote double uptrend candle trends. Red down-arrows, with the number of the trend part, denote double downtrend candle trends.
█ HOW TO USE
This indicator is intended for research purposes, strategy development and strategy optimisation. I hope it will be useful in helping to gain a better understanding of the underlying dynamics at play on any given market and timeframe.
It can, for example, give you an idea of whether the current double candle trend will continue or fail, based on the current trend scenario and what has happened in the past under similar circumstances. Such information can be useful when conducting top down analysis across multiple timeframes and making strategic decisions.
What you do with these statistics and how far you decide to take your research is entirely up to you, the possibilities are endless.
█ LIMITATIONS
Some higher timeframe candles on tickers with larger lookbacks such as the DXY , do not actually contain all the open, high, low and close (OHLC) data at the beginning of the chart. Instead, they use the close price for open, high and low prices. So, while we can determine whether the close price is higher or lower than the preceding close price, there is no way of knowing what actually happened intra-bar for these candles. And by default candles that close at the same price as the open price, will be counted as green. You can avoid this problem by utilising the sample period filter.
It is also worth noting that the sample size will be limited to your Trading View subscription plan. Premium users get 20,000 candles worth of data, pro+ and pro users get 10,000, and basic users get 5,000. If upgrading is currently not an option, you can always keep a rolling tally of the statistics in an excel spreadsheet or something of the like.
Upper Candle Trends [theEccentricTrader]█ OVERVIEW
This indicator simply plots upper candle trends and should be used in conjunction with my Lower Candle Trends indicator as a visual aid to my Upper and Lower Candle Trend Counter indicator.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a close price equal to or above the price it opened.
• A red candle is one that closes with a close price that is lower than the price it opened.
Upper Candle Trends
• A higher high candle is one that closes with a higher high price than the high price of the preceding candle.
• A lower high candle is one that closes with a lower high price than the high price of the preceding candle.
• A double-top candle is one that closes with a high price that is equal to the high price of the preceding candle.
Lower Candle Trends
• A higher low candle is one that closes with a higher low price than the low price of the preceding candle.
• A lower low candle is one that closes with a lower low price than the low price of the preceding candle.
• A double-bottom candle is one that closes with a low price that is equal to the low price of the preceding candle.
Muti-Part Upper and Lower Candle Trends
• A multi-part higher high trend begins with the formation of a new higher high and continues until a new lower high ends the trend.
• A multi-part lower high trend begins with the formation of a new lower high and continues until a new higher high ends the trend.
• A multi-part higher low trend begins with the formation of a new higher low and continues until a new lower low ends the trend.
• A multi-part lower low trend begins with the formation of a new lower low and continues until a new higher low ends the trend.
█ FEATURES
Plots
Green up-arrows, with the number of the trend part, denote higher high trends. Red down-arrows, with the number of the trend part, denote lower high trends.
█ LIMITATIONS
Some higher timeframe candles on tickers with larger lookbacks such as the DXY , do not actually contain all the open, high, low and close (OHLC) data at the beginning of the chart. Instead, they use the close price for open, high and low prices. So, while we can determine whether the close price is higher or lower than the preceding close price, there is no way of knowing what actually happened intra-bar for these candles. And by default candles that close at the same price as the open price, will be counted as green.
Lower Candle Trends [theEccentricTrader]█ OVERVIEW
This indicator simply plots lower candle trends and should be used in conjunction with my Upper Candle Trends indicator as a visual aid to my Upper and Lower Candle Trend Counter indicator.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a close price equal to or above the price it opened.
• A red candle is one that closes with a close price that is lower than the price it opened.
Upper Candle Trends
• A higher high candle is one that closes with a higher high price than the high price of the preceding candle.
• A lower high candle is one that closes with a lower high price than the high price of the preceding candle.
• A double-top candle is one that closes with a high price that is equal to the high price of the preceding candle.
Lower Candle Trends
• A higher low candle is one that closes with a higher low price than the low price of the preceding candle.
• A lower low candle is one that closes with a lower low price than the low price of the preceding candle.
• A double-bottom candle is one that closes with a low price that is equal to the low price of the preceding candle.
Muti-Part Upper and Lower Candle Trends
• A multi-part higher high trend begins with the formation of a new higher high and continues until a new lower high ends the trend.
• A multi-part lower high trend begins with the formation of a new lower high and continues until a new higher high ends the trend.
• A multi-part higher low trend begins with the formation of a new higher low and continues until a new lower low ends the trend.
• A multi-part lower low trend begins with the formation of a new lower low and continues until a new higher low ends the trend.
█ FEATURES
Plots
Green up-arrows, with the number of the trend part, denote higher low trends. Red down-arrows, with the number of the trend part, denote lower low trends.
█ LIMITATIONS
Some higher timeframe candles on tickers with larger lookbacks such as the DXY , do not actually contain all the open, high, low and close (OHLC) data at the beginning of the chart. Instead, they use the close price for open, high and low prices. So, while we can determine whether the close price is higher or lower than the preceding close price, there is no way of knowing what actually happened intra-bar for these candles. And by default candles that close at the same price as the open price, will be counted as green.
Upper and Lower Candle Trend Counter [theEccentricTrader]█ OVERVIEW
This indicator counts the number of confirmed upper and lower candle trend scenarios on any given candlestick chart and displays the statistics in a table, which can be repositioned and resized at the user's discretion.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a close price equal to or above the price it opened.
• A red candle is one that closes with a close price that is lower than the price it opened.
Upper Candle Trends
• A higher high candle is one that closes with a higher high price than the high price of the preceding candle.
• A lower high candle is one that closes with a lower high price than the high price of the preceding candle.
• A double-top candle is one that closes with a high price that is equal to the high price of the preceding candle.
Lower Candle Trends
• A higher low candle is one that closes with a higher low price than the low price of the preceding candle.
• A lower low candle is one that closes with a lower low price than the low price of the preceding candle.
• A double-bottom candle is one that closes with a low price that is equal to the low price of the preceding candle.
Muti-Part Upper and Lower Candle Trends
• A multi-part higher high trend begins with the formation of a new higher high and continues until a new lower high ends the trend.
• A multi-part lower high trend begins with the formation of a new lower high and continues until a new higher high ends the trend.
• A multi-part higher low trend begins with the formation of a new higher low and continues until a new lower low ends the trend.
• A multi-part lower low trend begins with the formation of a new lower low and continues until a new higher low ends the trend.
█ FEATURES
Inputs
• Start Date
• End Date
• Position
• Text Size
Table
The table is colour coded, consists of seven columns and, as many as, sixty-two rows. Blue cells denote the multi-part trend scenarios, green cells denote the corresponding upper candle trend scenarios and red cells denote the corresponding lower candle trend scenarios.
The multi-part candle trend scenarios are listed in the first column with their corresponding total counts to the right, in the second and fifth columns. The last row in column one, displays the sample period which can be adjusted or hidden via indicator settings.
The third and sixth columns display the candle trend scenarios as percentages of total 1-part candle trends. And columns four and seven display the total candle trend scenarios as percentages of the last, or preceding candle trend part. For example 4-part higher high trends as a percentages of 3-part higher high trends. This offers more insight into what might happen next at any given point in time.
Plots
For a visual aid to this indicator please use in conjunction with my Upper Candle Trends and Lower Candle Trends indicators which can both be found on my profile page under scripts, or in community scripts under the same names.
Green up-arrows, with the number of the trend part, denote higher high trends when above bar and higher low trends when below bar. Red down-arrows, with the number of the trend part, denote lower high trends when above bar and lower low trends when below bar.
█ HOW TO USE
This is intended for research purposes, strategy development and strategy optimisation. I hope it will be useful in helping to gain a better understanding of the underlying dynamics at play on any given market and timeframe.
It can, for example, give you an idea of whether the current upper or lower candle trend will continue or fail, based on the current trend scenario and what has happened in the past under similar circumstances. Such information can be useful when conducting top down analysis across multiple timeframes and making strategic decisions.
What you do with these statistics and how far you decide to take your research is entirely up to you, the possibilities are endless.
█ LIMITATIONS
Some higher timeframe candles on tickers with larger lookbacks such as the DXY , do not actually contain all the open, high, low and close (OHLC) data at the beginning of the chart. Instead, they use the close price for open, high and low prices. So, while we can determine whether the close price is higher or lower than the preceding close price, there is no way of knowing what actually happened intra-bar for these candles. And by default candles that close at the same price as the open price, will be counted as green. You can avoid this problem by utilising the sample period filter.
It is also worth noting that the sample size will be limited to your Trading View subscription plan. Premium users get 20,000 candles worth of data, pro+ and pro users get 10,000, and basic users get 5,000. If upgrading is currently not an option, you can always keep a rolling tally of the statistics in an excel spreadsheet or something of the like.
Buy / Sell Volume Header / NPR21📊 Buy / Sell Volume Header – NPR21
Overview
Buy / Sell Volume Header – NPR21 displays real-time Buy vs Sell volume dominance in a clean, Thinkorswim-style fixed header at the top of the chart.
Instead of cluttering candles with labels, this indicator presents volume information in a compact, side-by-side header, allowing traders to instantly gauge who is in control of the current bar—buyers or sellers—without losing focus on price action.
How It Works
Buy and Sell volume are estimated using candle structure:
Buy Volume is derived from the portion of the candle closing above the low
Sell Volume is derived from the portion of the candle closing below the high
Percentages show relative dominance for the most recently confirmed bar
This approach provides a fast, intuitive order-flow bias that works across futures, indices, crypto, and equities.
Key Features
✔ Thinkorswim-style fixed header
✔ Side-by-side Buy | Sell layout (no overlap)
✔ Bold green/red backgrounds with white text
✔ Compact font for intraday trading
✔ Updates only on confirmed bars (non-repainting)
✔ No candle clutter
✔ Optimized for scalping and intraday trading
Best Use Cases
Confirming buyer vs seller control
Adding confluence to:
Momentum indicators
VWAP / EMA strategies
Market structure & BOS setups
Quick decision support during:
Breakouts
Pullbacks
Range highs/lows
This tool is designed to be confirmation, not a standalone signal.
Notes
This is a volume estimation tool, not true bid/ask or footprint data
Best used alongside price action and structure
Power Bar SMA Directional (Trade Your Edge)GENERAL OVERVIEW:
The Power Bar SMA Directional (Trade Your Edge) indicator identifies high-momentum Power Bars and uses a structured SMA-based breakout model to generate Long and Short trading signals. Once a signal appears, the indicator automatically places a Stop-Loss and three Take-Profit levels, with an optional dynamic trailing stop-loss. Alerts are available for every trade event.
This indicator was developed by Flux Charts in collaboration with Steven Adams (Trade Your Edge).
What is the purpose of the indicator?:
The purpose of the Power Bar SMA Indicator is to turn an unusually strong candle (Power Bar) into a complete, rule-based trade setup. The indicator does three main things, very specifically:
It spots “power bars”. These are candles where the body is both large compared to the candle’s own range and large compared to nearby candles.
It only cares about power bars when they align with the trend’s direction: bullish or bearish.
When that happens, the indicator gives a buy or sell signal with an entry at the signal candle, a stop-loss at the low/high of the power bar, and three take-profit targets placed at fixed multiples of the entry to stop-loss distance. You can also have the stop move up/down after each target is hit with the trailing stop-loss feature.
What’s the theory behind the indicator?:
The theory behind this indicator is that large, one-sided candles often mark the start of directional strength. When a candle’s body takes up most of its total range and exceeds the average size of recent candlesticks, it shows clear control from either buyers or sellers. The indicator combines this concept with a simple moving average to confirm trend direction, ensuring signals only align with the current bias. It then checks if price breaks a recent swing high or low to confirm momentum is continuing rather than consolidating inside a range. By combining three core elements: trend bias, momentum identification, and confirmation that price has room for new discovery beyond prior ranges, the indicator can focus on finding trade setups that have multiple market factors in alignment.
POWER BAR SMA DIRECTIONAL FEATURES:
The Power Bar SMA Directional indicator includes 4 main features:
Power Bars
Trend Bias
Long / Short Signals + Risk Management
Alerts
POWER BARS:
🔹What are Power Bars?:
Power Bars are large, high-momentum candles that show strength in one direction of the market. They form when a candle’s body (the distance between open and close) dominates most of the candle’s total range (the distance between high and low), meaning price moved strongly in one direction with little to no pullback. To qualify, the candle must also be large relative to nearby candles. This size difference confirms that the candle is a burst of momentum.
🔹How to interpret and use Power Bars:
When a Power Bar forms, it signals that price has just made a strong directional move with little to no pullback. Traders can use these bars to identify momentum shifts and potential trade setups.
A bullish Power Bar means buyers controlled the entire candle, marking the start of upward momentum. A bearish Power Bar means sellers were in control of the entire candle, signaling the start of downwards momentum. In the Power Bar SMA Directional indicator, these candles are only used for signals when they align with the market trend and satisfy other entry requirements, mentioned later on.
Bullish Power Bars forming above the Simple Moving Average (SMA) can signal potential long opportunities.
Bullish Power Bars forming below the SMA can signal potential short opportunities.
🔹How are Power Bars identified:
Power Bars are detected and confirmed only after the candle closes, ensuring that the full candlestick body and range can be measured. The indicator does not repaint or change past bars. Once a Power Bar is confirmed, it stays fixed on the chart. Power Bars can be detected on any timeframe or symbol that produces standard candlestick data.
The indicator identifies Power Bars using two user-defined inputs: Sensitivity and Body %.
◇ Sensitivity:
The Sensitivity setting determines how large a candle’s body must be relative to nearby candles. It uses the Average True Range (ATR) to compare the current candle’s size with recent candles, and the Sensitivity value acts as a multiplier of that ATR. A higher Sensitivity value means the candle must be much larger than recent candles to qualify, so fewer Power Bars will form. A lower value makes the filter less strict, allowing more candles to qualify.
◇ Body %:
The Body % setting controls what percentage of the candle’s total range must be body rather than Wick. A higher value requires the body to take up more of the candle’s total range, so fewer candles pass the filter. A lower value allows candles with more wick to qualify, so more Power Bars will form.
Body % Example:
If Body % is set to 50, the candle body must cover at least half of the candle’s total range. For example, if a candle’s high is $11, its low is $10, its open is $10.20, and its close is $10.80, then the total range is $1 ($11 - $10) and the body is $0.60 ($10.80 - $10.20). Body % = (Body / Total Range) * 100 = (0.60 ÷ 1.00 × 100) = 60%. Since 60% is greater than the input of 50%, this candle passes the Body % criteria.
Once a candlestick closes and it meets both the Sensitivity and Body % requirements, it will be plotted in a different color, using barcolor() function. Users can adjust the bullish/bearish colors of Power Bars by adjusting the ‘Candle Coloring’ setting. The Power Bar candle coloring is purely visual and does not affect signal logic or strategy calculations.
TREND BIAS:
The indicator uses a Simple Moving Average (SMA) to determine overall trend direction and ensure that long/short signals align with the market bias.
When the SMA is sloping upward and price is trading above it, the market is considered to be in a bullish trend. In this case, only long setups are allowed. When the SMA is sloping downward and price is below it, the market is considered bearish, and only short setups are valid. This filtering ensures that every signal follows the current trend rather than fighting it.
Within the settings, the SMA length can be customized to match different trading styles. A shorter SMA period reacts more quickly to price changes, making it better suited for scalping or lower timeframes where traders want faster entries and exits. A longer SMA period responds more slowly, which smooths out smaller fluctuations and is more useful for day traders or swing traders who focus on larger trends. By default, the SMA length is set to 20.
Signals on SEED_ALEXDRAYM_SHORTINTEREST2:NQ 5-minute timeframe with a 10 SMA vs. 100 SMA:
🔹Why does the indicator include a trend filter?:
This indicator is built around the assumption that markets tend to continue moving in their current direction. Thus, if the trend is bullish, it’s assumed that price will continue moving higher. If the trend is bearish, it’s assumed that price will continue moving lower. By combining the SMA filter with the momentum logic of the power bars, the indicator avoids countertrend setups. This keeps signals focused on continuation setups where both the trend and short-term strength (momentum) are in agreement.
LONG/SHORT SIGNALS:
This indicator identifies potential trade setups by combining momentum, trend alignment, and structural confirmation. It detects when a Power Bar candle appears, and then looks for confirmation that the move is valid through trend alignment and a structure break.
There are three long setups and three short setups:
Momentum Breakout
Proximity Breakout
Delayed Breakout
All setups require:
A valid Power Bar forming in the correct context relative to the SMA.
A break of nearby structure (defined by the Swing Length setting).
🔹Signal Settings:
◇ SMA Distance:
This setting defines how close a Power Bar must be to the SMA to qualify for the proximity breakout setup type. It measures the maximum allowed distance between the Power Bar’s open price and the SMA, expressed as a multiple of the Average True Range (ATR).
This setting only affects Setup #2 (Proximity Breakout) and sometimes Setup #3 (Delayed Breakout). Setup #1 does not use this filter because its logic depends on price crossing the SMA or confirming later. In proximity setups, the power bar candle must both open and close on the same side of the SMA (bullish or bearish) while still being within the allowed SMA Distance range. This condition prevents signals when price is stretched too far away from the SMA, which could indicate exhaustion or a potential pullback rather than continuation.
A lower SMA Distance value tightens this filter, allowing only Power Bars that form very close to the SMA, resulting in fewer but more conservative signals. A higher SMA Distance value gives wiggle room and allows setups that form farther from the SMA, generating more frequent signals.
In the example below, when the SMA Distance is set to 0.5 (left chart), the bullish Power Bar does not trigger a long signal because its opening price is too far from the SMA. When the SMA Distance is increased to 1.0 (right chart), the same candle now falls within the allowed range, making the setup valid and displaying a long signal label.
◇ Swing Length:
The Swing Length setting defines how the indicator identifies recent structure levels used for breakout confirmation. These structure levels are swing highs and swing lows, which represent points where price reversed direction over a specified number of bars. The indicator uses these high/low levels to determine whether price has broken past a meaningful area of prior support or resistance before confirming a trade setup.
The Swing Length value determines how far back the indicator looks when calculating these points. Internally, it uses the Highest/Lowest method, scanning the last N bars (where N is the Swing Length input) to find the highest high and lowest low within that range.
The highest high becomes the immediate resistance level for potential long setups.
The lowest low becomes the immediate support level for potential short setups.
A lower Swing Length value makes the indicator reference closer levels. This increases the number of potential signals because nearby highs and lows are easier for price to reach.
A higher Swing Length value references farther structure levels, typically major swing points, which reduces signal frequency.
Every setup requires a structure break for confirmation. The Swing Length setting directly affects how strict or lenient the entire indicator behaves for each setup type.
In Setup #1 (Baseline Momentum Breakout) and Setup #2 (Trend-Aligned Proximity Breakout), the Power Bar must break the structure level during or immediately after its formation.
In Setup #3 (Delayed Breakout Confirmation), the same Swing Length level is referenced for a limited number of candles defined by the Candles Between Confirmation setting.
◇ Candles Between Confirmation:
The Candles Between Confirmation setting defines how long the indicator will wait for price to confirm a breakout after a qualifying Power Bar forms. It represents the maximum number of bars allowed between the Power Bar’s close and the moment when price breaks the nearby structure level, which is derived from the Swing Length setting. The structure level is defined as the most recent swing high (for long setups) or swing low (for short setups).
If a structure break occurs within the specified window, a valid signal is triggered, and the Long or Short label is plotted at the close of the breakout candle. If price fails to break through the level within a certain number of candles, the setup is invalidated. This ensures that signals only appear when momentum follows through promptly, and not when price stalls or consolidates for an extended period.
Lower values make confirmations stricter, capturing only quick momentum breakouts. Higher values allow more time for slower markets or higher timeframes to complete structure breaks. Adjust this setting based on market volatility and trading style.
In the example below, when Candles Between Confirmation is set to 10, no signal appears because price breaks the swing high after 15 bars, which is greater than the allowed limit. When the setting is increased to 15, the same move qualifies, and a long signal is triggered as price breaks the swing high 15 candles after the initial bullish Power Bar that crossed the SMA.
🔹Long Setups:
Long Setup #1: Momentum Breakout
A bullish Power Bar opens below the SMA, and closes above it, showing buyer strength.
A breakout must occur during this bullish Power Bar candle through a nearby resistance level derived from the Swing Length setting.
When this breakout occurs, a Long Signal appears at bar close.
After a signal appears, three take-profit levels and one stop-loss level are also plotted.
Stop-Loss: Placed at the Power Bar’s low.
Take-Profit 1: Set using a 1:1 risk distance from the Stop-Loss to entry.
Take-Profit 2: Extends to 1:1.5 risk-to-reward.
Take-Profit 3: Extends to 1:2 risk-to-reward.
(Power Bars are white in this image)
Long Setup #2: Proximity Breakout
A bullish Power Bar opens and closes above the SMA, but is still close enough to it to show price hasn’t extended too far. (Refer to SMA Distance setting). As long as the opening of that candle is within the SMA Distance threshold, the setup remains valid.
The bullish Power Bar candle must break through the recent swing high (refer to Swing Length setting).
A Long Signal triggers when that breakout is confirmed.
After a signal appears, three take-profit levels and one stop-loss level are also plotted, similar to Long Setup #1.
(Power Bars are white in this image)
Long Setup #3: Delayed Breakout
A bullish Power Bar appears in a valid location (Refer to Long Setup #1 or Long Setup #2), but structure is not broken immediately.
The indicator waits for confirmation within the maximum Candles Between Confirmation window. If price breaks structure within that time, a Long Signal appears. If price fails to break structure in time, the setup is discarded.
Risk Management:
Same Stop-Loss, TP 1, TP 2, and TP 3 logic as Long Setup #1
(Power Bars are white in this image)
🔹Short Setups:
Short Setup #1: Momentum Breakout
A bearish Power Bar opens above the SMA, and closes below it, showing seller strength.
A breakout must occur during this bearish Power Bar candle through a nearby support level derived from the Swing Length setting.
When this breakout occurs, a Short Signal appears at bar close.
After a signal appears, three take-profit levels and one stop-loss level are also plotted.
Stop-Loss: Placed at the Power Bar’s high.
Take-Profit 1: Set using a 1:1 risk distance from the Stop-Loss to entry.
Take-Profit 2: Extends to 1:1.5 risk-to-reward.
Take-Profit 3: Extends to 1:2 risk-to-reward.
(Power Bars are white in this image)
Short Setup #2: Proximity Breakout
A bearish Power Bar opens and closes below the SMA, but is still close enough to it to show price hasn’t extended too far. (Refer to SMA Distance setting). As long as the opening of that candle is within the SMA Distance threshold, the setup remains valid.
The bearish Power Bar candle must break through the recent swing low (refer to Swing Length setting).
A Short Signal triggers when that breakout is confirmed.
After a signal appears, three take-profit levels and one stop-loss level are also plotted, similar to Short Setup #1.
(Power Bars are white in this image)
Short Setup #3: Delayed Breakout
A bearish Power Bar appears in a valid location (Refer to Short Setup #1 or Short Setup #2), but structure is not broken immediately.
The indicator waits for confirmation within the maximum Candles Between Confirmation window. If price breaks structure within that time, a Short Signal appears. If price fails to break structure in time, the setup is discarded.
Risk Management:
Same Stop-Loss, TP 1, TP 2, and TP 3 logic as Long Setup #1
(Power Bars are white in this image)
🔹Trailing Stop-Loss Feature:
When the Trailing Stop-Loss setting is enabled, the Stop-Loss (SL) automatically adjusts as price reaches take-profit levels. This feature helps secure profits while keeping the trade logic completely rule-based and non-discretionary.
Here’s exactly how it works step-by-step:
Initial Stop-Loss placement:
For a Long trade, the initial SL is set at the low of the bullish Power Bar that triggered the setup.
For a Short trade, the initial SL is set at the high of the bearish Power Bar that triggered the setup.
This level stays fixed until one of the Take-Profit targets is reached.
After TP 1 is hit:
The SL automatically moves to the entry price (breakeven).
After TP2 is hit:
The SL automatically moves to TP 1
Final exit condition:
The trade is considered complete once either the trailing Stop-Loss or TP 3 is reached.
🔹Visualization:
Users can enable or disable:
Long Signals
Short Signals
Take-Profit Lines
Take-Profit Labels
Stop-Loss Lines
Stop-Loss Labels
Signal Line
SMA
◇ Signal Line:
The Signal Line is an optional visual feature that helps users see exactly which structure level the indicator is using to confirm a breakout. It does not change how signals are generated. It only displays the reference point on the chart.
Users can customize the Signal Line style (Dashed, Dotted, Solid) and choose different colors for bullish and bearish signal lines. The Signal Line can also be turned off completely. When disabled, signals will not be affected.
ALERTS:
The indicator supports alerts, so you never miss a key market move. You can choose to receive alerts for each of the following conditions:
Long Signal
Short Signal
TP 1 (Take-Profit 1)
TP 2 (Take-Profit 2)
TP 3 (Take-Profit 3)
SL (Stop-Loss)
UNIQUENESS:
This indicator automates a strategy that is normally managed manually using multiple steps: identifying large momentum candles, validating trend direction, confirming breakout strength through structure, and then projecting clean risk-based targets. The SMA Distance filter, confirmation window, and swing structure rules work together to ensure signals only trigger when momentum (Power Bars) aligns with technical levels. This indicator turns Power Bars into complete trade ideas with real-time SL/TP management and alerts.
Quasimodo (QML) Pattern [Kodexius]Quasimodo (QML) Pattern is a market structure indicator that automatically detects Bullish and Bearish Quasimodo formations using confirmed swing pivots, then visualizes the full structure directly on the chart. The script focuses on the classic liquidity-grab narrative of the QML: a sweep beyond a prior swing (the Head) followed by a decisive market structure break (MSB), leaving behind a clearly defined reaction zone between the Left Shoulder and the Head.
Detection is built on pivot highs and lows, so patterns are evaluated only after swing points are validated. Once a valid 4 pivot sequence is identified, the indicator draws the pattern legs, highlights the internal triangle area to emphasize the grab, marks the MSB leg, and projects a QML zone that can be used as a potential area of interest for retests.
This tool is designed for traders who work with structure, liquidity concepts, and reversal/continuation triggers, and who want a clean, repeatable QML visualization without manually marking swings.
🔹 Features
🔸 Confirmed Pivot Based Structure Mapping
The script uses classic built-in pivot logic to detect swing highs and swing lows.
🔸 Automatic Bullish and Bearish QML Detection
The indicator evaluates the most recent 4 pivots and checks for a valid alternating sequence (High-Low-High-Low or Low-High-Low-High). When the sequence matches QML requirements, the script classifies the setup as bullish or bearish:
Bullish logic (structure reversal up):
- Left Shoulder is a pivot Low
- Head is a lower Low than the Left Shoulder (liquidity sweep)
- MSB pivot exceeds the Reaction pivot
Bearish logic (structure reversal down):
- Left Shoulder is a pivot High
- Head is a higher High than the Left Shoulder (liquidity sweep)
- MSB pivot breaks below the Reaction pivot
🔸 Full Pattern Visualization (Legs + Highlighted Core)
When a pattern triggers, the script draws:
Three main legs: Left Shoulder to Reaction, Reaction to Head, Head to MSB
A shaded triangular highlight over the internal structure to make the liquidity-grab shape easy to spot at a glance
🔸 QML Zone Projection
A QML Zone box is drawn using the price range defined between the Left Shoulder and the Head, then extended to the right to remain visible as price develops. This zone is intended to act as a practical reference area for potential retests and reaction planning after MSB confirmation.
🔸 MSB Emphasis
A dotted MSB line is drawn between the Reaction point and the MSB point to visually emphasize the confirmation leg that completes the pattern logic.
🔸 Clean Point Tagging and Directional Labeling
Key points are labeled directly on the chart:
- “LS” at the Left Shoulder
- “Head” at the sweep pivot
- “MSB” at the break pivot
A directional label (“Bullish QML” or “Bearish QML”) is also printed to quickly identify the detected bias.
🔸 Configurable Visual Style
All main visual components are user configurable:
- Bullish and bearish colors
- Line width
- Label size
🔸 Efficient Update Logic
Pattern checks are only performed when a new pivot is confirmed, avoiding unnecessary repeated calculations on every bar. The most recent pattern’s projected elements (zone and label positioning) are updated as new bars print to keep the latest setup readable.
🔹 Calculations
This section summarizes the core logic used for detection and plotting.
1. Pivot Detection (Swing Highs and Lows)
The script relies on confirmed pivots using the user inputs:
Left Bars: how many bars must exist to the left of the pivot
Right Bars: how many bars must exist to the right to confirm it
float ph = ta.pivothigh(leftLen, rightLen)
float pl = ta.pivotlow(leftLen, rightLen)
When a pivot is confirmed, its true bar index is the pivot bar, not the current bar, so the script stores:
bar_index
2. Pivot Storage and History Window
Each pivot is stored as a structured object containing:
- price
- index
- isHigh (true for pivot high, false for pivot low)
A rolling history is maintained (up to 50 pivots) to keep processing stable and memory usage controlled.
3. Sequence Validation (Alternation Check)
The pattern evaluation always uses the latest 4 pivots:
p0: Left Shoulder candidate
p1: Reaction candidate
p2: Head candidate
p3: MSB candidate
Before checking bullish/bearish rules, the script enforces alternating pivot types:
bool correctSequence =
(p0.isHigh != p1.isHigh) and
(p1.isHigh != p2.isHigh) and
(p2.isHigh != p3.isHigh)
This prevents invalid structures like consecutive highs or consecutive lows from being interpreted as QML.
4. Bullish QML Conditions
A bullish QML is evaluated when the Left Shoulder is a Low:
Head must be lower than Left Shoulder (sweep)
MSB must be higher than Reaction (break)
if not p0.isHigh
if p2.price < p0.price and p3.price > p1.price
// Bullish QML confirmed
Interpretation:
p2 < p0 represents the liquidity grab below the prior swing low
p3 > p1 represents the market structure break above the reaction high
5. Bearish QML Conditions
A bearish QML is evaluated when the Left Shoulder is a High:
Head must be higher than Left Shoulder (sweep)
MSB must be lower than Reaction (break)
if p0.isHigh
if p2.price > p0.price and p3.price < p1.price
// Bearish QML confirmed
Interpretation:
p2 > p0 represents the liquidity grab above the prior swing high
p3 < p1 represents the market structure break below the reaction low
6. Drawing Logic (Structure, Highlight, Zone, Labels)
When confirmed, the script draws:
Three connecting legs (LS to Reaction, Reaction to Head, Head to MSB)
A shaded triangle using a transparent “ghost” line to enable filling
A dotted MSB emphasis line between Reaction and MSB
A QML Zone box spanning the LS to Head price range and projecting to the right
Point labels: LS, Head, MSB
A direction label: “Bullish QML” or “Bearish QML”
7. Latest Pattern Extension
To keep the newest setup readable, the script updates the most recently detected pattern by extending its projected elements as new bars print:
QML zone right edge is pushed forward
The main label x position is pushed forward
This keeps the last identified QML zone visible as price evolves, without having to redraw historical patterns on every bar.
SMT (ICT Concepts)Overview
Smart Money Technique (SMT) Divergence is a price action analysis method derived from Inner Circle Trader (ICT) methodology. This indicator automatically detects SMT divergences by comparing price movements across correlated financial instruments, identifying moments when assets that typically move together begin to diverge - a phenomenon often associated with potential price reversals.
An SMT divergence occurs when one instrument makes a new swing high or low while a correlated instrument fails to confirm that move. This failure to confirm suggests that the instrument may be positioning for a reversal, as the divergence indicates a lack of conviction in the current price direction across related markets.
Theoretical Foundation
What is SMT Divergence?
In correlated markets, instruments tend to move in tandem. For example, the E-mini S&P 500 (ES) and E-mini Nasdaq 100 (NQ) futures typically make swing highs and lows together due to their shared exposure to U.S. equity markets. When this correlation breaks down at key swing points, it creates an SMT divergence.
Bullish SMT Divergence:
The chart instrument creates a lower low compared to a previous swing low, while the correlated comparison instrument creates a higher low (or fails to make a lower low). This divergence at the lows suggests potential buying pressure and a possible bullish reversal.
Bearish SMT Divergence:
The chart instrument creates a higher high compared to a previous swing high, while the correlated comparison instrument creates a lower high (or fails to make a higher high). This divergence at the highs suggests potential selling pressure and a possible bearish reversal.
Why SMT Divergences Matter
SMT divergences are considered significant because they may indicate:
Accumulation or distribution occurring in one instrument but not the other
Relative strength or weakness between correlated assets
Potential exhaustion of the current trend
Early warning signs before major reversals
Indicator Features
Multi-Timeframe SMT Detection
This indicator provides simultaneous SMT detection on two timeframes:
Current Timeframe (CTF) Detection:
The indicator scans for SMT divergences on the chart's active timeframe using multiple pivot lookback periods (3, 5, 8, 13, 21, and 34 bars). This multi-period approach ensures detection of both short-term and intermediate swing points, reducing the likelihood of missing valid divergences while filtering out noise.
Higher Timeframe (HTF) Detection:
Simultaneously, the indicator monitors a higher timeframe for SMT divergences using pivot periods of 3, 5, 8, 13, and 21 HTF candles. Higher timeframe signals generally carry more significance as they represent larger market structure.
Automatic Timeframe Pairing:
When enabled, the indicator automatically selects an appropriate higher timeframe based on your chart's current timeframe:
Sub-1 minute charts pair with 5-minute
1-2 minute charts pair with 15-minute
3-4 minute charts pair with 30-minute
5 minute charts pair with 1-hour
6-9 minute charts pair with 1-hour
15 minute charts pair with 4-hour
16-59 minute charts pair with Daily
1-4 hour charts pair with Weekly
Daily charts pair with Monthly
Combined Signal Detection:
When an SMT divergence is detected on both the current timeframe and higher timeframe at the same price pivots, the indicator combines these into a single enhanced signal. Combined signals display both timeframes in the label and use the higher timeframe styling to emphasize their increased significance.
Automatic Symbol Correlation
The indicator includes comprehensive automatic symbol selection based on the instrument you are viewing. When Auto SMT is enabled, the indicator intelligently selects correlated comparison symbols.
Index Futures Correlations:
E-mini Contracts:
NQ (Nasdaq 100) compares with ES (S&P 500) and YM (Dow Jones)
ES (S&P 500) compares with NQ (Nasdaq 100) and YM (Dow Jones)
YM (Dow Jones) compares with NQ (Nasdaq 100) and ES (S&P 500)
RTY (Russell 2000) compares with ES (S&P 500) and NQ (Nasdaq 100)
Micro Contracts:
MNQ (Micro Nasdaq) compares with MES (Micro S&P) and MYM (Micro Dow)
MES (Micro S&P) compares with MNQ (Micro Nasdaq) and MYM (Micro Dow)
MYM (Micro Dow) compares with MNQ (Micro Nasdaq) and MES (Micro S&P)
M2K (Micro Russell) compares with MES (Micro S&P) and MNQ (Micro Nasdaq)
Metals Futures Correlations:
Standard Contracts:
GC (Gold) compares with SI (Silver) and PL (Platinum)
SI (Silver) compares with GC (Gold) and PL (Platinum)
PL (Platinum) compares with GC (Gold) and SI (Silver)
Micro Contracts:
MGC (Micro Gold) compares with SIL (Micro Silver) and PL (Platinum)
SIL (Micro Silver) compares with MGC (Micro Gold) and PL (Platinum)
Energy Futures Correlations:
CL (Crude Oil) compares with RB (RBOB Gasoline) and NG (Natural Gas)
RB (RBOB Gasoline) compares with CL (Crude Oil) and NG (Natural Gas)
NG (Natural Gas) compares with CL (Crude Oil) and RB (RBOB Gasoline)
MCL (Micro Crude) compares with RB (RBOB Gasoline) and NG (Natural Gas)
Major ETF Correlations:
SPY (S&P 500 ETF) compares with QQQ, DIA, and IWM
QQQ (Nasdaq 100 ETF) compares with SPY, DIA, and IWM
DIA (Dow Jones ETF) compares with SPY, QQQ, and IWM
IWM (Russell 2000 ETF) compares with SPY, QQQ, and DIA
Stock Sector Mapping:
When viewing individual stocks, the indicator automatically identifies the stock's sector and selects appropriate sector ETFs for comparison:
Technology Sector (AAPL, MSFT, GOOGL, NVDA, AMD, INTC, etc.):
Primary: QQQ (Nasdaq 100 ETF)
Secondary: XLK (Technology Select Sector SPDR)
Tertiary: SPY (S&P 500 ETF)
Financial Sector (JPM, BAC, GS, MS, WFC, etc.):
Primary: XLF (Financial Select Sector SPDR)
Secondary: KBE (SPDR S&P Bank ETF)
Tertiary: SPY (S&P 500 ETF)
Energy Sector (XOM, CVX, COP, SLB, etc.):
Primary: XLE (Energy Select Sector SPDR)
Secondary: USO (United States Oil Fund)
Tertiary: SPY (S&P 500 ETF)
Healthcare Sector (JNJ, UNH, PFE, MRK, LLY, etc.):
Primary: XLV (Health Care Select Sector SPDR)
Secondary: IBB (iShares Biotechnology ETF)
Tertiary: SPY (S&P 500 ETF)
Consumer Discretionary Sector (TSLA, HD, NKE, MCD, etc.):
Primary: XLY (Consumer Discretionary Select Sector SPDR)
Secondary: SPY (S&P 500 ETF)
Tertiary: QQQ (Nasdaq 100 ETF)
Consumer Staples Sector (PG, KO, PEP, WMT, COST, etc.):
Primary: XLP (Consumer Staples Select Sector SPDR)
Secondary: SPY (S&P 500 ETF)
Tertiary: QQQ (Nasdaq 100 ETF)
Industrial Sector (CAT, BA, HON, UPS, etc.):
Primary: XLI (Industrial Select Sector SPDR)
Secondary: SPY (S&P 500 ETF)
Tertiary: QQQ (Nasdaq 100 ETF)
Materials Sector (LIN, APD, SHW, FCX, NEM, etc.):
Primary: XLB (Materials Select Sector SPDR)
Secondary: GLD (SPDR Gold Shares)
Tertiary: SPY (S&P 500 ETF)
Utilities Sector (NEE, DUK, SO, etc.):
Primary: XLU (Utilities Select Sector SPDR)
Secondary: SPY (S&P 500 ETF)
Tertiary: QQQ (Nasdaq 100 ETF)
Real Estate Sector (AMT, PLD, CCI, etc.):
Primary: XLRE (Real Estate Select Sector SPDR)
Secondary: VNQ (Vanguard Real Estate ETF)
Tertiary: SPY (S&P 500 ETF)
Communication Services Sector (NFLX, DIS, CMCSA, VZ, T, etc.):
Primary: XLC (Communication Services Select Sector SPDR)
Secondary: SPY (S&P 500 ETF)
Tertiary: QQQ (Nasdaq 100 ETF)
Forex Correlations:
EURUSD compares with GBPUSD
GBPUSD compares with EURUSD
Cryptocurrency Correlations:
BTCUSD compares with ETHUSD
ETHUSD compares with BTCUSD
Three-Symbol Comparison
The indicator supports comparison against up to three symbols simultaneously. When multiple comparison symbols show divergence at the same pivot point, all diverging symbols are displayed in the label, providing stronger confluence. For example, if NQ shows divergence with both ES and YM at the same swing high, the label will display "ES1! + YM1!" indicating divergence confirmation from multiple correlated instruments.
Invalidation Logic
SMT divergences are not indefinitely valid. The indicator includes automatic invalidation logic based on price action following the divergence signal.
Invalidation Rules:
Bearish SMT: Invalidates when price trades above the high of the confirmation pivot (right side of the divergence)
Bullish SMT: Invalidates when price trades below the low of the confirmation pivot (right side of the divergence)
The invalidation level is set at the confirmation bar (the second pivot that completes the SMT pattern), not the extreme of both pivots. This approach aligns with the concept that once price exceeds the confirmation point, the divergence setup is no longer valid.
Invalidation Display Options:
Users can choose to show or hide invalidated SMT signals separately for current timeframe and higher timeframe divergences. When shown, invalidated signals can be displayed with different line styles and widths to visually distinguish them from active signals. Separate limits prevent excessive invalidated signals from cluttering the chart (maximum 15 invalidated signals per timeframe type).
Input Settings
General Settings
Enable SMT Detection:
Master toggle to enable or disable all SMT divergence detection. When disabled, no SMT signals will be calculated or displayed.
Direction:
Filter which divergence types to display:
Both: Display both bullish and bearish SMT divergences
Bullish: Display only bullish SMT divergences (divergence at lows)
Bearish: Display only bearish SMT divergences (divergence at highs)
Symbol Settings
Enable Auto SMT:
When enabled, the indicator automatically selects correlated comparison symbols based on the chart instrument using the correlation mappings described above. When disabled, manual symbol inputs are used.
Symbol 1 (with enable toggle):
First comparison symbol. Enabled by default. When Auto SMT is disabled, enter the desired symbol manually.
Symbol 2 (with enable toggle):
Second comparison symbol. Enabled by default. When Auto SMT is disabled, enter the desired symbol manually.
Symbol 3 (with enable toggle):
Third comparison symbol. Disabled by default. Enable for additional confirmation from a third correlated instrument.
Current Timeframe SMT Settings
Show Current TF SMTs:
Toggle visibility of SMT divergences detected on the chart's current timeframe.
Bullish Color:
Color for bullish SMT divergence lines and labels on the current timeframe.
Bearish Color:
Color for bearish SMT divergence lines and labels on the current timeframe.
Line Style:
Style for current timeframe SMT lines (solid, dashed, or dotted).
Line Width:
Width of current timeframe SMT lines (1-4 pixels).
Show Labels:
Toggle visibility of labels on current timeframe SMT divergences.
Label Style:
Normal: Displays full information including timeframe and diverging symbol names
+/-: Displays minimal "+" or "-" characters with full information available in hover tooltip
Label Size:
Size of current timeframe SMT labels (Tiny, Small, Normal, or Large).
Show Invalidated:
Toggle visibility of invalidated current timeframe SMT signals.
Invalidated Line Style:
Line style for invalidated current timeframe SMT signals.
Invalidated Line Width:
Line width for invalidated current timeframe SMT signals.
Higher Timeframe SMT Settings
Show Higher TF SMTs:
Toggle visibility of SMT divergences detected on the higher timeframe.
Auto Timeframe:
When enabled, automatically selects an appropriate higher timeframe based on the chart's current timeframe. When disabled, uses the manually specified timeframe.
Manual Timeframe:
When Auto Timeframe is disabled, specify the higher timeframe to scan for SMT divergences.
Bullish Color:
Color for bullish SMT divergence lines and labels on the higher timeframe.
Bearish Color:
Color for bearish SMT divergence lines and labels on the higher timeframe.
Line Style:
Style for higher timeframe SMT lines (solid, dashed, or dotted).
Line Width:
Width of higher timeframe SMT lines (1-4 pixels).
Show Labels:
Toggle visibility of labels on higher timeframe SMT divergences.
Label Style:
Normal: Displays full information including timeframe and diverging symbol names
+/-: Displays minimal "+" or "-" characters with full information available in hover tooltip
Label Size:
Size of higher timeframe SMT labels (Tiny, Small, Normal, or Large).
Show Invalidated:
Toggle visibility of invalidated higher timeframe SMT signals.
Invalidated Line Style:
Line style for invalidated higher timeframe SMT signals.
Invalidated Line Width:
Line width for invalidated higher timeframe SMT signals.
Visual Representation
Line Display
SMT divergences are displayed as lines connecting the two pivot points that form the divergence:
For bearish SMT: A line connects the previous swing high to the current (higher) swing high
For bullish SMT: A line connects the previous swing low to the current (lower) swing low
The line color indicates the divergence type (bullish or bearish) and whether it was detected on the current timeframe or higher timeframe.
Label Display
Labels are positioned at the midpoint of the SMT line and display:
The timeframe on which the divergence was detected
The symbol(s) that showed divergence with the chart instrument
When using the "+/-" label style, labels show only "+" for bullish or "-" for bearish divergences, with full information accessible via hover tooltip.
All labels use monospace font formatting for consistent visual appearance.
Combined Signals
When the same divergence is detected on both current and higher timeframes, the signals are combined into a single display using higher timeframe styling. The label shows both timeframes (e.g., "M2 + M15") and all diverging symbols, indicating strong multi-timeframe confluence.
Practical Application Guidelines
Signal Interpretation
SMT divergences should be interpreted within the broader market context. Consider the following when evaluating signals:
Market Structure: SMT divergences occurring at key structural levels (previous highs/lows, order blocks, fair value gaps) tend to be more significant.
Timeframe Confluence: Signals appearing on multiple timeframes simultaneously suggest stronger institutional involvement.
Symbol Confluence: Divergences confirmed by multiple comparison symbols indicate broader market disagreement with the current price direction.
Time of Day: SMT divergences during high-volume trading sessions may carry more weight than those during low-liquidity periods.
Limitations and Considerations
Correlation Variability: Correlations between instruments can strengthen or weaken over time. The automatic symbol selection is based on typical correlations but may not always reflect current market conditions.
Pivot Detection Lag: Pivots are only confirmed after subsequent price action, meaning SMT signals appear with some delay after the actual swing point forms.
False Signals: Not all SMT divergences result in reversals. Use additional confirmation methods and proper risk management.
Data Requirements: The indicator requires sufficient historical data and may not function properly on instruments with limited price history.
Technical Notes
The indicator uses multiple pivot detection periods to identify swing points across different scales
Higher timeframe candle tracking is performed on the lower timeframe chart for precise pivot bar indexing
A deduplication system prevents the same divergence from being detected multiple times across different pivot periods
Array-based storage manages active and invalidated SMT signals with automatic cleanup to prevent memory issues
Maximum label and line counts are set to 500 each to accommodate extended analysis periods
Disclaimer
This indicator is provided for educational and informational purposes only. It is designed to assist traders in identifying potential SMT divergences based on historical price data and should not be considered as financial advice or a recommendation to buy or sell any financial instrument.
Trading financial markets involves substantial risk of loss and is not suitable for all investors. Past performance of any trading methodology, including concepts discussed in this indicator, does not guarantee future results. Users should conduct their own research and analysis before making any trading decisions.
The automatic symbol correlations and sector mappings are based on general market relationships and may not accurately reflect current or future correlations. Users are encouraged to verify correlations independently and adjust comparison symbols as needed.
Always use appropriate risk management techniques, including but not limited to position sizing and stop-loss orders. Never risk more capital than you can afford to lose.
NHNL Breadth Scanner [BIG]═══════════════════════════════════════════════════════════════════════════════
NVENTURES NHNL BREADTH SYSTEM v2.0
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OVERVIEW
The NVentures NHNL Breadth System is an institutional-grade market breadth analysis framework designed for equity traders, portfolio managers, and market technicians who require comprehensive internal market structure visibility beyond price action alone. This system integrates New Highs - New Lows (NHNL) data across multiple exchanges with participation breadth metrics to identify market regime shifts, thrust conditions, divergences, and rotation dynamics between large-cap and small-cap equities.
Version 2.0 introduces the Participation Breadth Module , which monitors the percentage of stocks above their 50-day moving averages across S&P 500, Russell 2000, and NASDAQ 100 indices. This extension enables detection of Risk-On/Risk-Off rotations and narrow rally conditions—critical information for portfolio construction, sector allocation, and tactical hedging decisions.
The framework combines:
- Multi-exchange NHNL aggregation – NYSE, NASDAQ, AMEX breadth data integration
- McClellan Oscillator – Exponential moving average difference for trend momentum
- Thrust detection – Extreme breadth expansion/contraction identification
- Divergence analysis – Price vs. breadth non-confirmation patterns
- Participation breadth – Large-cap vs. small-cap rotation detection
- Composite signal scoring – Multi-factor quantitative breadth assessment
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CORE METHODOLOGY
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• NHNL Data Aggregation
The system retrieves daily New Highs and New Lows from three major U.S. exchanges:
- NYSE – INDEX:HIGN (New Highs), INDEX:LOWN (New Lows)
- NASDAQ – INDEX:HIGQ (New Highs), INDEX:LOWQ (New Lows)
- AMEX – INDEX:HIGA (New Highs), INDEX:LOWA (New Lows)
Users can toggle exchanges on/off to isolate specific market segments. All three exchanges are enabled by default for comprehensive market-wide breadth measurement.
Core Calculations :
- NHNL Raw = Total New Highs - Total New Lows
- NHNL % = (NHNL Raw / Total Issues) × 100
- NH/NL Ratio = New Highs / New Lows
These metrics quantify the internal strength or weakness of market advances/declines independent of price index levels.
• McClellan Oscillator
The McClellan Oscillator applies exponential moving average (EMA) logic to NHNL data:
Formula: McClellan Osc = EMA(NHNL, Fast) - EMA(NHNL, Slow)
Default parameters: Fast = 19, Slow = 39
Interpretation :
- Positive values = Breadth momentum favors bulls (more issues making new highs)
- Negative values = Breadth momentum favors bears (more issues making new lows)
- Zero-line crosses = Regime change signals (bullish above, bearish below)
- Extreme readings (>±100) = Overbought/oversold breadth conditions
The McClellan Oscillator is a standard institutional breadth tool used by market technicians since the 1960s. It smooths daily NHNL volatility while maintaining responsiveness to trend changes.
• Thrust Detection
Thrust conditions identify extreme breadth expansion or contraction that historically precedes sustained directional moves:
Bullish Thrust :
- NHNL % > Threshold (default +40%)
- Sustained for Confirmation Bars (default 2 bars)
- Context : Extreme positive breadth expansion. Historically associated with major rally initiations or continuation thrusts.
Bearish Thrust :
- NHNL % < -Threshold (default -40%)
- Sustained for Confirmation Bars (default 2 bars)
- Context : Extreme negative breadth contraction. Historically associated with panic selling, capitulation events, or major downtrend acceleration.
Thrust conditions are the highest-priority signals in the framework and override other conflicting indicators.
• Divergence Detection
The system identifies non-confirmation patterns between price action and breadth:
Bullish Divergence :
- Price makes lower low
- NHNL % makes higher low
- Context : Selling pressure exhausting despite lower prices. Potential reversal signal as fewer stocks participate in decline.
Bearish Divergence :
- Price makes higher high
- NHNL % makes lower high
- Context : Rally losing internal momentum despite higher prices. Potential reversal signal as fewer stocks participate in advance.
Divergences use pivot detection with configurable lookback periods (default 50 bars) and pivot strength (default 5 bars). Visual divergence lines are drawn directly on the price chart when detected.
• Participation Breadth Module (NEW in v2.0)
This module monitors the percentage of stocks trading above their 50-day moving average across three major indices:
- S&P 500 – INDEX:S5FI (Large-cap participation)
- Russell 2000 – INDEX:R2FI (Small-cap participation)
- NASDAQ 100 – INDEX:NDFI (Tech-cap participation)
Rotation Spread Calculation :
Rotation Spread = Russell 2000 % Above 50D - S&P 500 % Above 50D
Interpretation :
- Positive Spread (>+10%) = Risk-On Rotation
Small caps outperforming large caps. Broad market participation. Risk appetite expanding.
- Negative Spread (<-10%) = Risk-Off Rotation
Large caps outperforming small caps. Narrow rally / defensive positioning. Flight to quality or concentration risk.
- Neutral (-10% to +10%) = Balanced market, no clear rotation
This spread identifies critical regime changes between broad market participation (healthy) and narrow leadership (fragile). Risk-On rotations typically occur during economic expansion phases; Risk-Off rotations occur during uncertainty, recession fears, or late-cycle conditions.
• Composite Signal Score
The framework generates a quantitative breadth score (-100 to +100) by weighting five components:
1. Thrust Score (±40 points) – Active thrust condition
2. Trend Score (±30 points) – McClellan Oscillator above/below zero
3. Momentum Score (±20 points) – NHNL % magnitude
4. Ratio Score (±10 points) – NH/NL Ratio extremes
5. Participation Score (±15 points) – Risk-On/Risk-Off regime + participation health
The composite score is smoothed (EMA 5) and classified into five breadth states:
- +50 to +100 = Strong Bull
- +20 to +50 = Bullish
- -20 to +20 = Neutral
- -50 to -20 = Bearish
- -100 to -50 = Strong Bear
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SIGNAL HIERARCHY & PRIORITY
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The indicator generates multiple signal types with distinct priority levels:
Priority 1: Thrust Signals (Highest conviction)
- Green triangle below bar = Bullish Thrust (40%+ breadth expansion)
- Red triangle above bar = Bearish Thrust (40%+ breadth contraction)
- Chart background highlighted in green/red during active thrust
Priority 2: Rotation Signals (Regime identification)
- Cyan diamond below bar = Risk-On Rotation (small caps outperforming)
- Orange diamond above bar = Risk-Off Rotation (large caps outperforming)
- Chart background highlighted in cyan/orange during active rotation
Priority 3: Divergence Signals (Reversal warnings)
- Green label below bar = Bullish Divergence (price/breadth non-confirmation)
- Red label above bar = Bearish Divergence (price/breadth non-confirmation)
- Dashed lines connect divergence pivot points on price chart
Priority 4: Zero-Line Cross (Trend changes)
- Small circle below bar = McClellan crossing above zero (breadth turning positive)
- Small circle above bar = McClellan crossing below zero (breadth turning negative)
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VISUAL COMPONENTS
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• Comprehensive Information Panel
The top-right dashboard (position customizable) displays:
Section 1: Raw NHNL Data
- Total New Highs (green)
- Total New Lows (red)
- Exchange breakdown (NYSE, NASDAQ, AMEX) with individual deltas
Section 2: Core Metrics
- NHNL % with visual indicator (🔥 for thrusts, arrows for direction)
- NH/NL Ratio with strength bars
- McClellan Oscillator with directional arrows
Section 3: Participation Breadth (NEW)
- S&P 500 % above 50D MA with trend arrow
- Russell 2000 % above 50D MA with trend arrow
- NASDAQ 100 % above 50D MA with trend arrow
- Rotation Spread with regime icon (🚀 Risk-On, 🛡️ Risk-Off)
Section 4: Composite Assessment
- Signal Score (-100 to +100) with visual strength bars
- Market Status (large text): BULLISH THRUST, BEARISH THRUST, RISK-ON ROTATION, RISK-OFF ROTATION, or breadth state classification
• Chart Overlays
- Background color-coding for active regimes (thrust, rotation, extreme readings)
- Signal markers (triangles, diamonds, circles, labels) at key inflection points
- Divergence lines connecting pivot highs/lows on price chart
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KEY FEATURES
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- Multi-exchange breadth aggregation – NYSE, NASDAQ, AMEX with individual on/off toggles
- Institutional McClellan Oscillator – Standard market breadth momentum tool
- Automated thrust detection – Identifies extreme breadth conditions with confirmation logic
- Price-breadth divergence scanning – Non-confirmation pattern detection with visual lines
- Participation breadth integration – Risk-On/Risk-Off rotation detection via large-cap vs. small-cap analysis
- Composite signal scoring – Quantitative multi-factor breadth assessment
- No repainting – All signals confirm on bar close
- Comprehensive alerting – 12+ alert conditions for thrust, divergence, rotation, and confluence events
- Fully customizable parameters – EMA periods, thresholds, lookbacks, visual settings
- Professional dashboard – Real-time metrics with color-coded status indicators
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HOW TO USE
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1. Apply to any chart – The indicator pulls multi-security data; chart symbol does not matter (commonly applied to SPY, SPX, or QQQ for reference)
2. Monitor the dashboard :
• Focus on Market Status (bottom row) for current regime
• Check NHNL % and McClellan for breadth direction and momentum
• Watch Rotation Spread for large-cap vs. small-cap dynamics
• Review Signal Score for composite breadth strength
3. Interpret thrust signals (highest priority):
• Bullish Thrust → Major rally initiation or continuation likely. Consider adding long exposure or reducing hedges.
• Bearish Thrust → Major decline or capitulation event likely. Consider reducing exposure or adding hedges.
• Historical context: Thrust signals are rare (2-5 per year) but highly reliable for significant market moves.
4. Interpret rotation signals (regime identification):
• Risk-On Rotation → Broad market participation. Small caps outperforming. Healthy advance. Favor cyclical sectors, higher beta names.
• Risk-Off Rotation → Narrow rally or defensive positioning. Large caps outperforming. Caution—market leadership concentrating. Favor quality, defensives.
5. Interpret divergence signals (reversal warnings):
• Bullish Divergence → Selling exhaustion. Potential bottom formation. Wait for confirmation (zero-line cross, thrust) before aggressive positioning.
• Bearish Divergence → Rally losing momentum. Potential top formation. Consider profit-taking or hedging.
6. Combine signals for maximum conviction :
• Bull Confluence : Bullish Thrust + Risk-On Rotation + Positive McClellan = Maximum bullish alignment
• Bear Confluence : Bearish Thrust + Risk-Off Rotation + Negative McClellan = Maximum bearish alignment
• Alert system specifically flags these high-conviction confluences
7. Configure parameters for your style :
• Thrust Threshold : Default 40% catches major moves. Increase to 50%+ for extreme-only signals.
• Rotation Threshold : Default 10% spread. Tighten to 7.5% for earlier rotation detection.
• Divergence Lookback : Default 50 bars. Extend to 100+ for longer-term divergences.
8. Use alerts for proactive monitoring :
• Set TradingView alerts for Thrust, Rotation, Divergence, and Confluence conditions
• Receive notifications when critical breadth regime changes occur
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LIMITATIONS
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- U.S. equity markets only – NHNL data limited to NYSE, NASDAQ, AMEX. Does not cover international markets or other asset classes.
- Daily timeframe only – NHNL data is reported daily. Intraday trading requires alternative breadth measures.
- Lagging in fast reversals – McClellan Oscillator and participation metrics use EMAs, introducing lag during rapid regime shifts. Thrust signals respond faster but require extreme conditions.
- Equal-weighting assumption – All stocks within NHNL counts are equally weighted. Large-cap-dominated rallies (e.g., FANG-led advances) may show strong price performance despite mediocre breadth.
- False positives in sideways markets – Divergence signals can produce false positives during extended consolidation phases. Require confirmation from thrust or rotation signals.
- Participation data quality – S5FI, R2FI, NDFI data from TradingView may have occasional gaps or delays. Indicator includes data validation logic and falls back gracefully when data unavailable.
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TECHNICAL SPECIFICATIONS
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- Pine Script v5
- Non-repainting (signals confirmed on bar close)
- Multi-security data feeds (6 NHNL tickers + 3 participation tickers)
- Maximum 500 lines supported (divergence line drawing)
- Real-time dashboard table with 20+ rows
- 12+ alert conditions (thrust, divergence, rotation, ratio extremes, confluence)
- Fully customizable colors, thresholds, and visual elements
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NOTES
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This indicator is designed for experienced equity traders, portfolio managers, and market technicians familiar with:
- Market breadth analysis and internal market structure
- McClellan Oscillator interpretation
- New High - New Low dynamics and their correlation with market cycles
- Large-cap vs. small-cap rotation patterns
- Risk-On/Risk-Off regime identification
The framework provides objective breadth signals but does not account for:
- Fundamental catalysts (earnings, economic data, Fed policy)
- Sector-specific dynamics (may show broad weakness while certain sectors thrive)
- International market correlations
- Volatility regime changes (VIX dynamics)
Best used in combination with:
- Price action analysis (support/resistance, chart patterns)
- Volume analysis (accumulation/distribution)
- Volatility indicators (VIX, put/call ratios)
- Sentiment indicators (survey data, positioning)
Market breadth is a leading indicator of internal market health. Divergences between price and breadth often precede major reversals by weeks or months.
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Developed for institutional market breadth analysis based on New Highs - New Lows methodology with extended participation breadth integration.
TGIF Dynamic Tracker [NINE]Overview
A professional-grade indicator for tracking weekly price ranges and identifying high-probability retracement zones based on the TGIF (Thank God It's Friday) concept from ICT (Inner Circle Trader) methodology.
What is the TGIF Concept?
The TGIF concept is based on the observation that price tends to retrace a significant portion of the weekly range toward the end of the trading week — typically on Thursday evening or Friday. This phenomenon occurs as institutional traders take profits and rebalance positions before the weekend, creating predictable retracement patterns.
By identifying the weekly high and low, traders can anticipate specific retracement levels where price is likely to find support or resistance. The most commonly referenced retracement zone is the 20-30% level, representing a shallow pullback from the week's extreme before potential continuation.
Features In Depth
Weekly High/Low Tracking
The foundation of the TGIF strategy is accurately tracking the current week's price extremes.
Automatic Detection: The indicator continuously monitors price action and updates the weekly high and low in real-time. As new extremes are made, all dependent calculations (retracement zones, percentage levels) update automatically.
Smart Session Timing: The indicator automatically detects your market type and adjusts accordingly:
Stocks/ETFs: Week begins Monday at 9:30 AM ET (market open)
Forex/Crypto/Futures: Week begins Sunday at 6:00 PM ET (18:00)
This ensures accurate weekly range calculations regardless of which market you're trading.
Visual Customization:
Enable/disable weekly high and low lines independently
Choose line color, style (solid, dashed, dotted), and thickness
Lines extend from week start to current bar
Percentage Level Lines
Individual horizontal lines mark key retracement percentages within the weekly range.
Available Levels:
20% — Shallow retracement, first potential support/resistance
30% — Edge of the primary TGIF zone
50% — Mid-range equilibrium point
60% — Beginning of deeper retracement territory
80% — Deep retracement zone
90% — Near-complete retracement
Independent Controls: Each level can be toggled on or off individually, allowing you to display only the levels relevant to your trading strategy. All levels share common styling settings for a clean, consistent appearance.
Dynamic Bias Adjustment: Levels automatically adjust based on the current weekly bias:
Bullish Bias (new weekly high made): Levels measure DOWN from the high
Bearish Bias (new weekly low made): Levels measure UP from the low
This ensures retracement zones always point toward the direction of potential pullback.
Retracement Zones
Highlighted zones visually emphasize the most significant retracement areas.
Three Configurable Zones:
20-30% Zone (Primary TGIF Zone)
This is the classic TGIF retracement area. When price makes a weekly high or low, traders anticipate a pullback to this zone before potential continuation. This shallow retracement often provides optimal risk/reward entries in the direction of the weekly trend.
50-60% Zone (Equilibrium Zone)
Represents a balanced pullback to the middle of the weekly range. Price reaching this zone suggests a more significant retracement is underway. This area often acts as a decision point — price either finds support/resistance here or continues toward deeper retracement levels.
80-90% Zone (Deep Retracement Zone)
Indicates a near-complete retracement of the weekly range. Price reaching this zone suggests the original weekly move may be fully reversing. Traders watch for reversal signals here or prepare for a potential range expansion in the opposite direction.
Zone Display Options:
Each zone can be enabled/disabled independently
Customizable background colors with transparency control
Zones only appear during the retracement period (starting Thursday/Friday)
Midlines: Optional center lines within each zone (25%, 55%, 85%) provide additional precision points. These midlines often act as the "sweet spot" within each retracement band.
Time-Based Markers
Vertical lines help you identify important session boundaries and timing.
Daily Session Lines:
Mark the start of each trading day with vertical lines extending through the weekly range.
Stocks: 9:30 AM ET (NYSE/NASDAQ open)
Forex/Crypto/Futures: 6:00 PM ET (18:00 — New York session close/new day start)
Control how many historical session lines remain visible (1-5) to avoid chart clutter while maintaining useful reference points.
Weekly Start Lines:
A distinct vertical line marks the beginning of each trading week, providing clear visual separation between weeks and helping you identify the starting point for weekly range calculations.
Retracement Start Lines:
Mark when the TGIF retracement period begins — this is when you should start watching for pullbacks to the retracement zones.
Stocks: Friday 9:30 AM ET (Friday market open)
Forex/Crypto/Futures: Thursday 6:00 PM ET (18:00)
Historical Weeks
View retracement data from previous weeks to identify recurring patterns and validate the TGIF concept on your chosen instrument.
Historical Tracking:
Display up to 20 previous weeks of data
Each historical week shows its own high/low lines, retracement zones, and time markers
Helps identify how consistently the instrument respects TGIF levels
What's Displayed:
Weekly high and low boundaries
All enabled retracement zones with midlines
Weekly start and retracement start lines
Optional labels for historical levels
Historical Labels: Toggle labels on historical weeks independently. Disable them to reduce clutter while keeping the visual reference lines.
Use Cases:
Backtest TGIF setups visually on your chart
Identify instruments that respect TGIF levels consistently
Study how deep retracements typically go on your chosen market
Labels & Display Modes
Comprehensive labeling options for quick reference.
Label Display Modes:
Levels: Shows only the level name (e.g., "HIGH", "20%", "50%")
Price: Shows only the price value
Both: Shows level name and price (e.g., "20% | 1.2345")
Label Positioning: Labels appear to the right of the current bar, staying visible as price action develops.
Tooltips: When using "Levels" display mode, hover over any label to see the exact price in the tooltip.
Label Customization:
Text size: Tiny, Small, Normal, Large, Huge
Text color selection
Labels use monospace font for clean alignment
Info Table
An optional real-time summary table showing all current levels and their distance from price.
Table Contents:
Current day indicator (MON, TUE, WED, THU, FRI)
All six percentage levels (20%, 30%, 50%, 60%, 80%, 90%)
Exact price for each level
Distance from current price to each level
Adaptive Theming: The table automatically detects your chart's background color (light or dark) and adjusts text and border colors for optimal readability.
Display Settings:
9 position options (corners, edges, and center)
Size options: Tiny, Small, Normal, Large
Practical Use: Quickly identify which level is nearest to current price without visually scanning the chart. The distance column helps assess how far price needs to travel to reach key zones.
Smart Market Detection
The indicator automatically identifies your market type and adjusts all timing calculations.
Detected Market Types:
Stocks & ETFs:
Week starts: Monday 9:30 AM ET
Daily sessions: 9:30 AM ET
Retracement period begins: Friday 9:30 AM ET
Standard equity market hours apply
Forex & Crypto:
Week starts: Sunday 6:00 PM ET (18:00)
Daily sessions: 6:00 PM ET (18:00)
Retracement period begins: Thursday 6:00 PM ET (18:00)
24-hour market timing with New York session rollover
Futures Contracts:
Automatically detected via common futures symbols (ES, NQ, YM, RTY, CL, GC, etc.)
Uses forex-style timing (18:00 ET rollover)
Handles continuous contracts and front-month symbols
This automatic detection ensures you get accurate weekly ranges without manual configuration.
Bias Tracking
The indicator dynamically tracks weekly directional bias to orient retracement calculations correctly.
How Bias is Determined:
When price makes a new weekly high, bias shifts to BULLISH
When price makes a new weekly low, bias shifts to BEARISH
Bias can change multiple times throughout the week as new extremes are made
Why Bias Matters:
Retracement levels are calculated from the appropriate extreme based on current bias:
Bullish bias: Levels measure DOWN from the weekly high (anticipating pullback from high)
Bearish bias: Levels measure UP from the weekly low (anticipating pullback from low)
This ensures the 20-30% zone always represents a shallow retracement in the context of the current weekly direction.
Tips
Best Results on Trending Weeks: TGIF works best when there's a clear weekly direction. Choppy, range-bound weeks may not produce clean retracements.
Combine with Other Confluence: TGIF levels are most powerful when they align with other technical factors — Fair Value Gaps, order blocks, previous week highs/lows, or key support/resistance levels.
Use Historical Data: Enable historical weeks to see how your instrument typically respects TGIF levels. Some instruments are more "TGIF-friendly" than others.
Midlines as Precision Points: The midlines (25%, 55%, 85%) often act as the exact reversal point within each zone. Watch for reactions specifically at these levels.
Friday Afternoon Caution: Late Friday sessions can be thin and choppy. Consider taking profits or reducing position sizes heading into the weekend.
Requirements
Intraday Timeframes Only: This indicator requires timeframes of 1 hour or less for accurate session and weekly boundary detection.
Sufficient Historical Data: When using the Historical Weeks feature, ensure your chart has enough bars loaded to display the requested number of weeks.
Session-Based Markets: Optimized for markets with distinct sessions. Continuous 24/7 markets may show different characteristics.
Disclaimer
For Educational and Informational Purposes Only
This indicator is provided as a technical analysis tool for educational and informational purposes only. It is not intended as, and should not be construed as, financial advice, investment advice, trading advice, or any other type of advice.
No Guarantees: Past performance of any trading strategy, indicator, or methodology is not indicative of future results. The TGIF concept and associated retracement levels do not guarantee that price will behave in any predicted manner. Markets are inherently
unpredictable, and no technical indicator can accurately predict future price movements.
Risk Warning: Trading financial instruments involves substantial risk of loss and is not suitable for all investors. You should carefully consider your investment objectives, level of experience, and risk appetite before trading. Never trade with money you cannot afford to lose.
Not Financial Advice: The creator of this indicator (NINE) is not a licensed financial advisor, broker, or dealer. Nothing in this indicator or its documentation should be interpreted as a recommendation to buy, sell, or hold any financial instrument.
Your Responsibility: You are solely responsible for your own trading decisions. Always conduct your own research and due diligence before making any trading or investment decisions. Consider consulting with a qualified financial professional before trading.
No Liability: The creator assumes no responsibility or liability for any errors, inaccuracies, or omissions in this indicator or its documentation. The creator shall not be held liable for any losses, damages, or costs arising from the use or inability to use this indicator.
Historical Volatility EstimatorsHistorical volatility is a statistical measure of the dispersion of returns for a given security or market index over a given period. This indicator provides different historical volatility model estimators with percentile gradient coloring and volatility stats panel.
█ OVERVIEW There are multiple ways to estimate historical volatility. Other than the traditional close-to-close estimator. This indicator provides different range-based volatility estimators that take high low open into account for volatility calculation and volatility estimators that use other statistics measurements instead of standard deviation. The gradient coloring and stats panel provides an overview of how high or low the current volatility is compared to its historical values.
█ CONCEPTS We have mentioned the concepts of historical volatility in our previous indicators, Historical Volatility, Historical Volatility Rank, and Historical Volatility Percentile. You can check the definition of these scripts. The basic calculation is just the sample standard deviation of log return scaled with the square root of time. The main focus of this script is the difference between volatility models.
Close-to-Close HV Estimator: Close-to-Close is the traditional historical volatility calculation. It uses sample standard deviation. Note: the TradingView build in historical volatility value is a bit off because it uses population standard deviation instead of sample deviation. N – 1 should be used here to get rid of the sampling bias.
Pros:
• Close-to-Close HV estimators are the most commonly used estimators in finance. The calculation is straightforward and easy to understand. When people reference historical volatility, most of the time they are talking about the close to close estimator.
Cons:
• The Close-to-close estimator only calculates volatility based on the closing price. It does not take account into intraday volatility drift such as high, low. It also does not take account into the jump when open and close prices are not the same.
• Close-to-Close weights past volatility equally during the lookback period, while there are other ways to weight the historical data.
• Close-to-Close is calculated based on standard deviation so it is vulnerable to returns that are not normally distributed and have fat tails. Mean and Median absolute deviation makes the historical volatility more stable with extreme values.
Parkinson Hv Estimator:
• Parkinson was one of the first to come up with improvements to historical volatility calculation. • Parkinson suggests using the High and Low of each bar can represent volatility better as it takes into account intraday volatility. So Parkinson HV is also known as Parkinson High Low HV. • It is about 5.2 times more efficient than Close-to-Close estimator. But it does not take account into jumps and drift. Therefore, it underestimates volatility. Note: By Dividing the Parkinson Volatility by Close-to-Close volatility you can get a similar result to Variance Ratio Test. It is called the Parkinson number. It can be used to test if the market follows a random walk. (It is mentioned in Nassim Taleb's Dynamic Hedging book but it seems like he made a mistake and wrote the ratio wrongly.)
Garman-Klass Estimator:
• Garman Klass expanded on Parkinson’s Estimator. Instead of Parkinson’s estimator using high and low, Garman Klass’s method uses open, close, high, and low to find the minimum variance method.
• The estimator is about 7.4 more efficient than the traditional estimator. But like Parkinson HV, it ignores jumps and drifts. Therefore, it underestimates volatility.
Rogers-Satchell Estimator:
• Rogers and Satchell found some drawbacks in Garman-Klass’s estimator. The Garman-Klass assumes price as Brownian motion with zero drift.
• The Rogers Satchell Estimator calculates based on open, close, high, and low. And it can also handle drift in the financial series.
• Rogers-Satchell HV is more efficient than Garman-Klass HV when there’s drift in the data. However, it is a little bit less efficient when drift is zero. The estimator doesn’t handle jumps, therefore it still underestimates volatility.
Garman-Klass Yang-Zhang extension:
• Yang Zhang expanded Garman Klass HV so that it can handle jumps. However, unlike the Rogers-Satchell estimator, this estimator cannot handle drift. It is about 8 times more efficient than the traditional estimator.
• The Garman-Klass Yang-Zhang extension HV has the same value as Garman-Klass when there’s no gap in the data such as in cryptocurrencies.
Yang-Zhang Estimator:
• The Yang Zhang Estimator combines Garman-Klass and Rogers-Satchell Estimator so that it is based on Open, close, high, and low and it can also handle non-zero drift. It also expands the calculation so that the estimator can also handle overnight jumps in the data.
• This estimator is the most powerful estimator among the range-based estimators. It has the minimum variance error among them, and it is 14 times more efficient than the close-to-close estimator. When the overnight and daily volatility are correlated, it might underestimate volatility a little.
• 1.34 is the optimal value for alpha according to their paper. The alpha constant in the calculation can be adjusted in the settings. Note: There are already some volatility estimators coded on TradingView. Some of them are right, some of them are wrong. But for Yang Zhang Estimator I have not seen a correct version on TV.
EWMA Estimator:
• EWMA stands for Exponentially Weighted Moving Average. The Close-to-Close and all other estimators here are all equally weighted.
• EWMA weighs more recent volatility more and older volatility less. The benefit of this is that volatility is usually autocorrelated. The autocorrelation has close to exponential decay as you can see using an Autocorrelation Function indicator on absolute or squared returns. The autocorrelation causes volatility clustering which values the recent volatility more. Therefore, exponentially weighted volatility can suit the property of volatility well.
• RiskMetrics uses 0.94 for lambda which equals 30 lookback period. In this indicator Lambda is coded to adjust with the lookback. It's also easy for EWMA to forecast one period volatility ahead.
• However, EWMA volatility is not often used because there are better options to weight volatility such as ARCH and GARCH.
Adjusted Mean Absolute Deviation Estimator:
• This estimator does not use standard deviation to calculate volatility. It uses the distance log return is from its moving average as volatility.
• It’s a simple way to calculate volatility and it’s effective. The difference is the estimator does not have to square the log returns to get the volatility. The paper suggests this estimator has more predictive power.
• The mean absolute deviation here is adjusted to get rid of the bias. It scales the value so that it can be comparable to the other historical volatility estimators.
• In Nassim Taleb’s paper, he mentions people sometimes confuse MAD with standard deviation for volatility measurements. And he suggests people use mean absolute deviation instead of standard deviation when we talk about volatility.
Adjusted Median Absolute Deviation Estimator:
• This is another estimator that does not use standard deviation to measure volatility.
• Using the median gives a more robust estimator when there are extreme values in the returns. It works better in fat-tailed distribution.
• The median absolute deviation is adjusted by maximum likelihood estimation so that its value is scaled to be comparable to other volatility estimators.
█ FEATURES
• You can select the volatility estimator models in the Volatility Model input
• Historical Volatility is annualized. You can type in the numbers of trading days in a year in the Annual input based on the asset you are trading.
• Alpha is used to adjust the Yang Zhang volatility estimator value.
• Percentile Length is used to Adjust Percentile coloring lookbacks.
• The gradient coloring will be based on the percentile value (0- 100). The higher the percentile value, the warmer the color will be, which indicates high volatility. The lower the percentile value, the colder the color will be, which indicates low volatility.
• When percentile coloring is off, it won’t show the gradient color.
• You can also use invert color to make the high volatility a cold color and a low volatility high color. Volatility has some mean reversion properties. Therefore when volatility is very low, and color is close to aqua, you would expect it to expand soon. When volatility is very high, and close to red, you would it expect it to contract and cool down.
• When the background signal is on, it gives a signal when HVP is very low. Warning there might be a volatility expansion soon.
• You can choose the plot style, such as lines, columns, areas in the plotstyle input.
• When the show information panel is on, a small panel will display on the right.
• The information panel displays the historical volatility model name, the 50th percentile of HV, and HV percentile. 50 the percentile of HV also means the median of HV. You can compare the value with the current HV value to see how much it is above or below so that you can get an idea of how high or low HV is. HV Percentile value is from 0 to 100. It tells us the percentage of periods over the entire lookback that historical volatility traded below the current level. Higher HVP, higher HV compared to its historical data. The gradient color is also based on this value.
█ HOW TO USE If you haven’t used the hvp indicator, we suggest you use the HVP indicator first. This indicator is more like historical volatility with HVP coloring. So it displays HVP values in the color and panel, but it’s not range bound like the HVP and it displays HV values. The user can have a quick understanding of how high or low the current volatility is compared to its historical value based on the gradient color. They can also time the market better based on volatility mean reversion. High volatility means volatility contracts soon (Move about to End, Market will cooldown), low volatility means volatility expansion soon (Market About to Move).
█ FINAL THOUGHTS HV vs ATR The above volatility estimator concepts are a display of history in the quantitative finance realm of the research of historical volatility estimations. It's a timeline of range based from the Parkinson Volatility to Yang Zhang volatility. We hope these descriptions make more people know that even though ATR is the most popular volatility indicator in technical analysis, it's not the best estimator. Almost no one in quant finance uses ATR to measure volatility (otherwise these papers will be based on how to improve ATR measurements instead of HV). As you can see, there are much more advanced volatility estimators that also take account into open, close, high, and low. HV values are based on log returns with some calculation adjustment. It can also be scaled in terms of price just like ATR. And for profit-taking ranges, ATR is not based on probabilities. Historical volatility can be used in a probability distribution function to calculated the probability of the ranges such as the Expected Move indicator. Other Estimators There are also other more advanced historical volatility estimators. There are high frequency sampled HV that uses intraday data to calculate volatility. We will publish the high frequency volatility estimator in the future. There's also ARCH and GARCH models that takes volatility clustering into account. GARCH models require maximum likelihood estimation which needs a solver to find the best weights for each component. This is currently not possible on TV due to large computational power requirements. All the other indicators claims to be GARCH are all wrong.
Momentum Market Structure ProThis first indicator in the Beyond Market Structure Suite gives you clear market structure at a glance, with adaptive support & resistance zones. It's the only SMC-style indicator built from momentum highs & lows, as far as I know. It creates dynamic support & resistance zones that change strength and resize intelligently, and gives you timely alerts when price bounces from support/rejects from resistance.
You’re free to use the provided entry and exit signals as a ready-to-use, self-contained strategy, or plug its structure into your existing system to sharpen your edge :
• Market structure bias may help improve a compatible system's win rate by taking longs only in bullish bias and shorts in bearish structure.
• Support/resistance can help trend traders identify inflection points, and help range traders define ranges.
🟩 HIGHLIGHTS
⭐ Unique market structure with different characteristics than purely price-based models.
⭐ Support and resistance created from only the extreme levels.
⭐ Support & resistance zones adapt to remain relevant. Zones are deactivated when they become too weak.
⭐ Long and short signals for a bounce from support/rejection from resistance.
🟩 WHY "MARKET STRUCTURE FIRST, ALWAYS"?
"There is only one side to the stock market; and it is not the bull side or the bear side, but the right side." — Jesse Livermore, Reminiscences of a Stock Operator (1923)
If the market is structurally against your trade, you're gonna have a bad time. So you must know what the market structure is before you plan your trade. The more precise and relevant your definition of market structure, the better.
🟩 HOW TO TRADE USING THIS INDICATOR (SIMPLE)
• Directional filter : The prevailing bias background can be used for any kind of trades you want to take. For example, you can long a bounce from support in a bullish market structure bias, or short a rejection from resistance in bearish bias.
• Entries : For more conservative entries, you could wait for a Candle Trend flip after a reaction from your chosen zone (see below for more about Candle Trend).
• Stops : The included running stop-loss level based on Average True Range (ATR) can be used for a stop-loss — set the desired multiplier, and use the level from the bar where you enter your trade.
• Take-profit : Similarly, you can set a Risk:Return-based take-profit target. Support and resistance zones can also be used as full or partial take-profit targets.
See the Advanced section below for more ideas.
🟩 SIGNALS
⭐ ENTRIES
You can enable signals and alerts for bounces from support and rejections from resistance (you'll get more signals using Adaptive mode). You can filter these by requiring corresponding market structure bias (it uses the bias you've already set for the background), and by requiring that Candle Trend confirm the move.
I've slipped in my all-time favourite creation to this indicator: Candle Trend. When price makes a Simple Low pivot, the trend flips bullish. When price then makes a Simple High pivot, the trend flips bearish (see my Market Structure library for a full explanation). This tool is so simple, yet I haven't noticed it anywhere else. It shows short-term trends beautifully. I use it mainly as confirmation of a move. You can use it to confirm ANY kind of move, but here we use it for bounces from support/rejections from resistance.
Note that the pivots and Zigzags are structure, not signals.
⭐ STOPS
You can use the supplied running ATR-based stop level to find a stop-loss level that suits your trading style. Set the desired multiplier, and use the level from the bar where you enter your trade.
⭐ TAKE-PROFIT
Similarly, you can set a take-profit target based on Risk:Return (R:R). If this setting is enabled, the indicator calculates the distance between the closing price and your configured stop, then multiplies that by the configured R:R factor to calculate an appropriate take-profit level. Note that while the stop line is reasonably smooth, the take-profit line varies much more, reflecting the fact that if price has moved away from your stop, the trade requires a greater move in order to hit a given R:R ratio.
Since the indicator doesn't know where you were actually able to enter a position, add a ray using the drawing tool and set an alert if you want to be notified when price reaches your stop or target.
🟩 WHAT'S UNIQUE ABOUT THIS INDICATOR
⭐ MOMENTUM PIVOTS
Almost all market structure indicators use simple Williams fractals. A very small number incorporate momentum, either as a filter or to actually derive the highs and lows. However, of those that derive pivots from momentum, I'm not aware of any that then create full market structure from it.
⭐ SUPPORT & RESISTANCE
Some other indicators also adjust S/R zones after creation, some use volume in zone creation, some increase strength for overlap, a few merge zones together, and many use price interactions to classify zones. But my implementation differs from others, as far as I can tell after looking at many many indicators, in seven specific ways:
+ Zones are *created* from purely high-momentum pivots, not derived or filtered from simple Williams pivots (e.g. `ta.pivothigh()`).
+ Zones are *weakened* dynamically as well as strengthened. Many people know that S/R gets stronger if price rejects from it, but this is only half the story. Different price patterns strengthen *or weaken* zones.
+ We use *conviction-weighted candle patterns* to adjust strength. Not simply +1 for price touching the zone, but a set of single-bar and multi-bar patterns which all have different effects.
+ The rolling strength adjustments are all *moderated by volume*. The *relative volume* forms a part of each adjustment pattern. Some of our patterns reward strong volume, some punish it.
+ We do our own candle modelling, and the adjustment patterns take this into account.
+ We *resize* zones as a result of certain candle patterns ("indecision erodes, conviction defends").
+ We shrink overlapping zones to their sum *and* add their strengths.
🟩 HOW TO TRADE USING THIS INDICATOR (ADVANCED)
In addition to the ideas in the How to Trade Using This indicator (Simple) section above, here are some more ideas.
You can use the market structure:
• As a bias for entries given by more reactive momentum resets, or indeed other indicators and systems.
• You could use a change in market structure to close a long-running trend-following position.
You can use the distance from a potential entry to the CHoCH line as a filter to choose higher-potential trades in ranging assets.
Confluence between market structure and your favourite trend indicator can be powerful.
Multi timeframe analysis
This is a bit of a rabbit hole, but you could use a split screen with this indicator on a higher timeframe (HTF) view of the same asset:
• If the 1D structure turns bullish, the next time that the 1H structure also flips bullish might be a good entry.
• Rejection from a HTF zone, confirmed by lower timeframe (LTF) structure, could be a good entry.
None of this is advice. You need to master your own system, and especially know your own strengths and weaknesses, in order to be a successful trader. An indicator, no matter how cool, is not going to one-shot that process for you.
In Adaptive mode, a skillful trader will be able to spot more opportunities to classify and use support and resistance than any algorithm, including mine, now that they've been automatically drawn for you.
If you are doing historical analysis, note that the "Calculated bars" setting is set to a reasonably small number by default, which helps performance. Either increase this number (setting to zero means "use all the bars"), or use Bar Replay to examine further back in the chart's history. If you encounter errors or slow loading, reduce this number.
🟩 SUPPORT & RESISTANCE
A support zone is an area where price is more likely to bounce, and a resistance zone is an area where price is more likely to reject. Marking these zones up on the chart is extremely helpful, but time-consuming. We create them automatically from only high-momentum areas, to cut noise and highlight the zones we consider most important.
In Simple mode, we simply mark S/R zones from momentum and Implied pivots. We don't update them, just deactivate them if price closes beyond them. Use this mode if you're interested in only recent levels.
In Adaptive mode, zones persist after they're traversed. Once the zones are created, we adjust them based on how price and volume interact with them. We display stronger zones with more opaque fills, and weaker zones with more transparent fills. To calculate strength, we first preprocess candles to take into account gaps between candles, because price movement after market is just as important in its own way. The preprocessing also redefines what constitutes upper and lower wicks, so as to better account for order flow and commitment. We use these modelled candle values, as well as their relative amplitude historically, rather than the raw OHLC for all calculations for interactions of price and zones. It's important to understand, when trying to figure out why the indicator strengthened or weakened a zone, that it sees fundamental price action in a different way to what is shown on standard chart candles (and in a way that can't easily be represented accurately on chart candles).
Then, we strengthen or weaken , and resize support and resistance zones dynamically using different formulas for different events, based on principles including these:
• The close is the market's "vote", the momentum shift anchor.
• Defended penetrations reveal validated liquidity clusters.
• Markets contract to defended levels.
• "The wick is the fakeout, but the close tells you if institutions held the level." — ICT (Inner Circle Trader)
Adaptive mode is more powerful, but you might need to tweak some of the Advanced Support & Resistance settings to get a comfortable number of zones on the chart.
🟩 MOMENTUM PIVOTS
The building blocks of market structure are Highs and Lows — places where price hits a temporary extreme and reverses. All the indicators I could find that create full market structure do so from basic price pivots — Williams fractals, being the highest/lowest candle wick for N candles backwards and forwards (there are some notable first attempts on TradingView to use momentum to define pivots, but no full structure). "Highest/lowest out of N bars" is the almost universal method, but it also picks up somewhat arbitrary price movements. Recognising this, programmers and traders often use longer lookbacks to focus on the more significant Highs and Lows. This removes some noise, but can also remove detail.
My indicator uses a completely different way of thinking about High and Low pivots. A High is where *momentum* peaks and falls back, and a low is where it dips and then recovers. While this is happening, we record the extremes in price, and use those prices as the High or Low pivot zones.
This deliberately picks out different, more meaningful pivots than any purely price-based approach, helping you focus on the swings that matter. By design, it also ignores some stray wicks and other price action that doesn't reflect significant momentum. Price action "purists" might not like this at first, but remember, ultimately we want to trade this. Check and see which levels the market later respects. It's very often not simply the numerically higher/lower local maxima and minima, but the levels that held meaning, interpreted here through momentum.
The first-release version uses the humble Stochastic as the structural momentum metric. Yes, I know — it's overlooked by most people, but that's because they're using it wrong. Stochastic is a full-range oscillator with medium excursions, unlike RSI, say, which is a creeping oscillator with reluctant resets. This makes Stoch (at the default period of 14) not quite reactive enough for on-the-ball momentum reset entry signals, but close to perfect (no metric is 100%) for structural pivots.
Stochastic is also a solid choice for structure because divergences are rare and not usually very far away in terms of price. More reactive momentum metrics such as Stochastic RSI produce very noisy structure that would take a whole extra layer of interpreting (see Further Research, below).
For these reasons, I may or may not add other options for momentum. In the initial release, I've added smoothed RSI as an alternative just to show it's possible, which takes even longer than Stochastic to migrate from one extreme to another, creating an interesting, longer-term structure.
🟩 IMPLIED PIVOTS
We want pivots to mark important price levels so that we can compute market direction and support & resistance zones from them.
In this context, we see that some momentum metrics, and Stochastic in particular, tend to give multiple consecutive resets in the same direction. In other words, we get High followed by High, or Low followed by Low, which does not give us the chance to create properly detailed structure. To remedy this, we simply take the most extreme price action between two same-direction pivots, and create an Implied pivot out of it, after the second same-direction pivot is created.
Obviously these pivots are created very late. Recalling why we wanted them, we realise that this is fine. By definition , price has not exceeded the Implied Pivot level when they're created. So they show us an interesting level that is yet untested.
Implied Pivots are thus created indirectly by momentum but defined directly by price. They are for structure only. We choose not to give them a Dow type (HH, HL, LH, LL) and not to include them in the Main Zigzag to emphasise their secondary nature. However, Implied Pivots are not "internal" or "minor" pivots. There is no such concept in the current Momentum Market Structure model.
If you want less responsive, more long-term structure, you can turn Implied Pivots off.
🟩 DOW STRUCTURE
Dow structure is the simplest form of market structure — Higher Highs (HHs) and Higher Lows (HLs) is an uptrend (showing buyer dominance), and vice-versa for a downtrend.
We label all Momentum (not Implied) Pivots with their Dow qualifier. You can also choose to display the background bias according to the Dow trend.
There is an input option to enable a "Ranging" Dow state, which happens when you get Lower Highs in an uptrend or Higher Lows in a downtrend.
🟩 SMC-STYLE STRUCTURE (BOS, CHOCH)
The ideas of trend continuation after taking out prior highs/lows and looking for early signs of possible reversal go back to Dow and Wyckoff, but have been popularised by SMC as Break Of Structure (BOS) and Change of Character (CHoCH).
BOS can be used as a trigger: for example:
• Wait for a bullish break of structure
• Then attempt to buy the pullback
• Cancel if structure breaks bearish (meaning, we get a bearish CHoCH break)
How to buy the pullback? This is the trillion-dollar question. First, you need solid structure. Without structure, you got nothin'. Then, you want some identified levels where price might bounce from.
If only we incorporated intelligent support and resistance into this very indicator 😍
Creating and maintaining correct BOS and CHoCH continuously , without resetting arbitrarily when conditions get difficult, is technically challenging. I believe I've created an implementation of this structure that is at least as solid as any other available.
In general, BOS is fully momentum‑pivot‑driven; CHoCH is anchored to momentum pivots but maintained mainly by raw price extremes relative to those anchors (breaks are obviously pure price). This means that the exact levels will sometimes differ from your previous favourite market structure indicator.
We have made some assumptions here which may or may not match any one person's understanding of the "correct" way to do things, including: BOS is not reset on wicks because, for us, if price cannot close beyond the BOS there is no BOS break, therefore the previous wick level is still important. The candidate for CHoCH on opposing CHoCH break *is* reset on a wick, because we want to be sure to overcome the leftover liquidity at that new extreme before calling a Change of Character. The CHoCH is moved on a BOS break. For a bullish BOS break, the new CHoCH is the lowest price *since the last momentum pivot was confirmed, creating the BOS that just broke*, and vice-versa for bearish. If there's a stray wick before that, which doesn't shift momentum, we don't care about it.
🟩 ZIGZAG
The Major Swing Zigzag dynamically connects momentum highs and lows (e.g., from a Higher Low to the latest Higher High), adjusting as new extremes form to reveal the overall trend leg.
The Implied Structure Zigzag joins momentum pivots and Implied pivots, if enabled.
🟩 REPAINTING
It's really important to understand two things before asking "Does it repaint?":
1. ALL structure indicators repaint, in the sense of drawing things into the past or notifying you of things that happened in past bars, because by definition, structure needs some kind of confirmation, which takes at least one bar, usually several. This is normal.
2. Almost all indicators of ANY kind repaint in that they display unconfirmed values until the current bar closes. This is also normal.
Most features of this indicator repaint in the ordinary, intended ways described above: the pivots (Implied doubly so), BOS and CHoCH lines, and formation of S/R zones.
The Zigzags, by design, adjust themselves to new pivots. The active lines often change and attach themselves to new anchors. This is a form of repainting. It's important to note that the Zigzags are not signals. They're there to help visualise market structure, and structure does change. Therefore, I prioritised clearly explaining what price did rather than preserving its history.
One of the "bad" kinds of repainting is if a signal is printed when the bar closes, but then on a later bar that "confirmed" signal changes. This is a fundamental issue with some high timeframe implementations. It's bad because you might already have entered a trade and now the indicator is pretending that it never signalled it for you. My indicators do not do this (in fact I wrote an entire library to help other authors avoid this).
If you are ever in any doubt, play with an indicator in Bar Replay mode to see exactly what it does.
To understand repainting, see the official docs: www.tradingview.com
🟩 FURTHER RESEARCH
I've attempted to answer two of the tricky problems in technical analysis in Pine: how to do robust and responsive market structure, and how to maintain support and resistance zones once created. However, this just opens up more possibilities. Which momentum metrics are suitable for structure? Can more reactive metrics be used, and how do we account for divergences in a structural model based on key horizontal levels? Which sets of rules give the best results for maintaining support and resistance? Does the market have a long or a short memory? Is bar decay a natural law or a coping mechanism?
🟩 CREDITS
❤️ I'd like to thank my humble trading mentor, whose brilliant ideas inspire me to garble out code. Thanks are also due to @Timeframe_Titans for guidance on the finer points of market structure (all mistakes and distortions are my own), and to @NJPorthos for feedback and encouragement during the months in the wilderness.
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Momentum Day Trading ToolkitMomentum Day Trading Toolkit
Complete User Guide
Table of Contents
Overview
Quick Start
The Dashboard
Module 1: 5 Pillars Screener
Module 2: Gap & Go
Module 3: Bull Flag / Flat Top
Module 4: Float Rotation
Module 5: R2G / G2R
Module 6: Micro Pullback
Signal Reference
Quality Score
Settings Guide
Alerts Setup
Trading Workflows
Troubleshooting
Overview
The Momentum Day Trading Toolkit combines 6 powerful indicators into one unified system for day trading momentum stocks.
ModulePurpose① 5 PillarsConfirms stock is "in play"② Gap & GoPre-market levels & gap analysis③ Bull Flag / Flat TopClassic breakout patterns④ Float RotationMeasures true interest level⑤ R2G / G2RTracks prior close crosses⑥ Micro PullbackPrecision continuation entries
All modules work together - the dashboard shows you everything at a glance, and you can enable/disable any module you don't need.
Quick Start
Step 1: Add to Chart
Add the indicator to any stock chart
Recommended timeframes: 1-minute, 5-minute, or 15-minute
Step 2: Check the Dashboard (Top Right)
Look for:
Status = Current state (Scanning, Entry Signal, etc.)
Quality Score = Setup rating out of 10
Green checkmarks (✓) = Criteria passing
Step 3: Watch for Entry Signals
Triangles, circles, diamonds below bars = Entry signals
Arrows = R2G/G2R crosses
Step 4: Set Alerts
Right-click chart → Add Alert
Select "Momentum Day Trading Toolkit"
Choose your alert condition
The Dashboard
The dashboard in the top-right corner gives you instant analysis:
┌─────────────────────────────┐
│ MOMENTUM TOOLKIT │
├─────────────────────────────┤
│ Status │ 🎯 ENTRY SIGNAL │
│ Day │ 🟢 GREEN │
│ Gap │ +8.5% 🔥 │
│ RVol │ 3.2x ✓ │
│ Rotation │ 1.45x 🔥 │
│ Float │ 5.2M 🔥 │
│ Change │ +12.3% ✓ │
│ Pattern │ BULL FLAG! │
│ EMA 9/20 │ Above Both ✓ │
│ VWAP │ Above ✓ │
│ Prior Cl │ 5.91 │
│ PM High │ 9.11 ✓ │
│ Price │ 9.46 ✓ │
└─────────────────────────────┘
Dashboard Row Reference
RowWhat It ShowsGood ValuesStatusCurrent state🎯 ENTRY SIGNALDayGreen/Red vs prior close🟢 GREENGapGap % from prior close🔥 (5%+) or 🔥🔥 (10%+)RVolRelative volume✓ (2x+) or ✓✓ (5x+)RotationFloat rotation🔥 (1x) or 🔥🔥 (2x+)FloatFloat in millions🔥 (<5M) or Low (<10M)ChangeDaily % change✓ (meets minimum)PatternPattern statusBREAKOUT!EMA 9/20Trend positionAbove Both ✓VWAPVWAP positionAbove ✓Prior CloseKey R2G levelReference pricePM HighPre-market high✓ = Above itPriceCurrent price✓ = In range
Status Messages
StatusMeaningActionScanning...Looking for setupsWait✅ ALL PILLARSStock qualifiesWatch for pattern⏳ PATTERN FORMINGSetup developingGet ready🎯 ENTRY SIGNALSignal triggeredExecute trade
Module 1: 5 Pillars Screener
What It Does
Confirms the stock meets basic criteria to be worth trading.
The 5 Pillars
PillarDefaultWhy It MattersRelative Volume2x+ (5x for "strong")Confirms unusual interestDaily Change5%+Stock is movingPrice Range$1-$20Sweet spot for momentumFloat Size<20M sharesLower float = bigger moves
Visual Indicator
Green background appears when ALL pillars pass
Dashboard Shows
Individual pillar status with ✓ checkmarks
Quality score includes pillar factors
Settings
SettingDefaultDescriptionMin RVol2.0xMinimum relative volumeStrong RVol5.0xVolume for full qualificationMin Change5%Minimum daily moveMin Price$1Minimum stock priceMax Price$20Maximum stock priceMax Float20MMaximum float size
Module 2: Gap & Go
What It Does
Analyzes pre-market gaps and displays key price levels.
Key Levels Displayed
LevelColorDescriptionPrior CloseOrangeYesterday's close - THE key levelPM HighGreenPre-market high - breakout levelPM LowRedPre-market low - support
Gap Classification
Gap SizeRatingMeaning5-9.9%🔥 QualifyingWorth watching10%+🔥🔥 StrongHigh priority
Entry Signal
Small green triangle = PM High Breakout
How to Trade
Stock gaps up in pre-market
Wait for market open
Look for break above PM High
Enter on breakout with stop below PM Low
Settings
SettingDefaultDescriptionMin Gap %5%Qualifying gap thresholdStrong Gap %10%Strong gap thresholdShow PM LevelsONDisplay PM high/low lines
Module 3: Bull Flag / Flat Top
What It Does
Detects classic continuation patterns and signals breakouts.
Bull Flag Pattern
▲ BREAKOUT (Entry Signal)
│
┌────┴────┐
│ Pullback │ ← 2-5 red candles
│ (flag) │ Max 50% retrace
└─────────┘
│
┌────┴────┐
│ Pole │ ← 3+ green candles
│ (move) │ Strong momentum
└─────────┘
Flat Top Pattern
═══════════════ Resistance (2+ touches)
│
▲ BREAKOUT above resistance
Entry Signals
SignalShapeColorPatternBull Flag Breakout▲ TriangleLimeFlag breaks upFlat Top Breakout◆ DiamondAquaResistance breaks
How to Trade Bull Flag
See 3+ green candles (the pole)
Price pulls back 2-5 red candles
Pullback stays above 50% of move
Enter on break above pullback high
Stop below pullback low
Settings
SettingDefaultDescriptionMin Pole Candles3Green candles neededMax Pullback5Max red candles allowedMax Retrace50%Max pullback depthFT Touches2Resistance touches neededFT Lookback10Bars to check for resistance
Module 4: Float Rotation
What It Does
Tracks how many times the entire float has traded hands today.
The Formula
Rotation = Cumulative Day Volume ÷ Float
Rotation Levels
RotationEmojiMeaning0.5x—Half float traded1.0x🔥FULL rotation - significant!2.0x🔥🔥Double rotation - extreme3.0x+🔥🔥🔥Triple rotation - rare event
Why It Matters
High rotation = Extreme interest
Everyone who owns shares has likely traded
Often precedes explosive moves
Shows "real" demand beyond just volume
Dashboard Shows
Current rotation level
Fire emojis for milestones
Settings
SettingDefaultDescriptionFloat SourceAutoAuto-detect or manualManual Float10MIf auto fails, use thisAlert Level1.0xAlert when rotation hits this
Module 5: R2G / G2R
What It Does
Tracks when price crosses the prior day's close - a key psychological level.
Red to Green (R2G) 🟢
Prior Close ─────────────────
↗ CROSS TO GREEN
↗
(opened red)
Stock opened below prior close (red)
Crosses above prior close (green)
BULLISH signal
Green to Red (G2R) 🔴
(opened green)
↘
↘ CROSS TO RED
Prior Close ─────────────────
Stock opened above prior close (green)
Crosses below prior close (red)
BEARISH signal
Entry Signals
SignalShapeColorMeaningR2G↑ ArrowLimeCrossed to greenG2R↓ ArrowRedCrossed to red
Why R2G Matters
Bears who shorted get squeezed
Creates FOMO buying
Prior close becomes support
Momentum often continues
Dashboard Shows
Current day status (🟢 GREEN / 🔴 RED)
Whether R2G or G2R occurred (R2G ✓ or G2R ✓)
Settings
SettingDefaultDescriptionRequire Opposite OpenONR2G needs red openShow Prior CloseONDisplay the line
Module 6: Micro Pullback
What It Does
Finds precision entries on brief 1-3 candle pullbacks after strong moves.
The Pattern
▲ ENTRY (break pullback high)
│
┌──┴───┐
│ 1-3 │ ← Micro pullback (brief!)
│ red │ Stop = low of this
└──────┘
│
┌──┴───┐
│ 3+ │ ← Strong move
│green │ Momentum building
└──────┘
Why Micro Pullbacks Work
Tight stop = Pullback low is close
Momentum intact = Only paused briefly
Early entry = Catch continuation early
Clear trigger = Break of pullback high
Entry Signal
SignalShapeColorMicro Pullback Entry● CircleYellow
How to Trade
See 3+ green candles (strong move)
1-3 red candles (brief pause)
Pullback stays above 50% retrace
Enter when green candle breaks pullback high
Stop at pullback low
Settings
SettingDefaultDescriptionMin Green Candles3Candles before pullbackMax Pullback3Max red candlesMax Retrace50%Max pullback depth
Signal Reference
All Entry Signals (Below Bar)
ShapeColorSignalModule▲ Large TriangleLimeBull Flag BreakoutPatterns◆ DiamondAquaFlat Top BreakoutPatterns● CircleYellowMicro Pullback EntryMicro PB▲ Small TriangleGreenPM High BreakoutGap & Go↑ ArrowLimeRed to GreenR2G/G2R
Warning Signals (Above Bar)
ShapeColorSignalModule↓ ArrowRedGreen to RedR2G/G2R
Optional Forming Signals (Disabled by Default)
ShapeColorSignal🚩 FlagFaded LimeBull Flag Forming● CircleFaded YellowMicro PB Forming
Enable "Show 'Forming' Markers" in settings to see these
Quality Score
The quality score (0-10) rates the overall setup strength.
Scoring Breakdown
FactorPointsRVol 5x++2RVol 2x++1Daily change 5%++1Low float (<20M)+1Strong gap (10%+)+2Qualifying gap (5%+)+1Rotation 1x++2Rotation 0.5x++1Above EMA 20+1
Score Interpretation
ScoreGradeAction8-10A+Best setups - full position6-7AGood setups - standard size4-5BAverage - reduced size0-3CWeak - skip or paper trade
Settings Guide
Module Toggles
Turn each module ON/OFF:
SettingDefaultDescription① 5 Pillars ScreenerONStock qualification② Gap & Go AnalysisONGap & level analysis③ Bull Flag / Flat TopONPattern detection④ Float RotationONRotation tracking⑤ R2G / G2R TrackerONPrior close crosses⑥ Micro PullbackONPullback entries
Visual Settings
SettingDefaultDescriptionShow DashboardONDisplay info tableTable SizeNormalSmall/Normal/LargeShow Entry SignalsONDisplay entry shapesShow 'Forming' MarkersOFFShow pattern formingShow Key LevelsONPrior close, PM levelsShow EMA 9/20ONTrend EMAsShow VWAPONVWAP line
Recommended Presets
Minimal (Clean Chart)
Show Dashboard: ON
Show Entry Signals: ON
Show 'Forming' Markers: OFF
Show Key Levels: OFF
Show EMA: OFF
Show VWAP: OFF
Standard (Balanced)
All defaults
Full Analysis
All settings ON
Alerts Setup
Available Alerts
AlertTriggerAny Bullish EntryAny entry signal firesBull Flag BreakoutBull flag breaks outFlat Top BreakoutFlat top breaks outMicro Pullback EntryMicro PB triggersPM High BreakoutBreaks above PM highRed to GreenR2G crossGreen to RedG2R crossFloat RotationHits rotation level5 Pillars PassAll pillars qualifyPattern FormingPattern starts formingHigh Quality EntryEntry with score 7+/10
How to Set Alerts
Right-click on chart
Select "Add Alert"
Condition: "Momentum Day Trading Toolkit"
Select alert type from dropdown
Set expiration and notifications
Click "Create"
Recommended Alerts
For Active Trading:
Any Bullish Entry
High Quality Entry
For Watchlist Monitoring:
5 Pillars Pass
Float Rotation
Trading Workflows
Workflow 1: Full Qualification
Step 1: 5 PILLARS
└─→ Wait for "✅ ALL PILLARS" status
Step 2: CHECK SETUP
└─→ Quality score 6+?
└─→ Above EMA and VWAP?
Step 3: WAIT FOR ENTRY
└─→ Bull Flag, Flat Top, or Micro PB signal
Step 4: EXECUTE
└─→ Enter on signal
└─→ Stop below pattern low
└─→ Target 2:1 minimum
Workflow 2: Gap & Go
Step 1: PRE-MARKET
└─→ Stock gaps 5%+ (shows in Gap row)
Step 2: MARKET OPEN
└─→ Note PM High level (green line)
Step 3: WAIT FOR BREAK
└─→ PM High Breakout signal (small triangle)
Step 4: CONFIRM
└─→ R2G if opened red (double confirmation)
└─→ RVol 2x+
Step 5: EXECUTE
└─→ Enter on PM High break
└─→ Stop below PM Low
Workflow 3: Micro Pullback Scalp
Step 1: FIND MOMENTUM
└─→ Stock moving, 3+ green candles
Step 2: WAIT FOR PAUSE
└─→ 1-3 red candles (brief pullback)
Step 3: ENTRY
└─→ Yellow circle signal appears
Step 4: QUICK TRADE
└─→ Enter at signal
└─→ Tight stop at pullback low
└─→ Quick target (1:1 to 2:1)
Troubleshooting
Q: Lines are moving/jumping on real-time chart?
A: This was fixed in latest version. Make sure you have the newest code. Lines now lock in place at market open.
Q: Too many signals, chart is cluttered?
A:
Turn off "Show 'Forming' Markers"
Disable modules you don't need
Use "Minimal" visual preset
Q: No signals appearing?
A:
Check if "Show Entry Signals" is ON
Make sure relevant module is enabled
Stock may not meet pattern criteria
Q: Dashboard shows wrong float?
A:
TradingView float data isn't available for all stocks
Switch Float Source to "Manual"
Enter correct float in millions
Q: PM High/Low not showing?
A:
Only appears during market hours
Needs pre-market data to calculate
Check if "Show Key Levels" is ON
Q: Quality score seems wrong?
A:
Score updates in real-time
Check individual factors in dashboard
RVol and rotation change throughout day
Q: Alert not triggering?
A:
Make sure alert is set on correct symbol
Check alert hasn't expired
Verify condition is set correctly
Quick Reference Card
Entry Signals
▲ Lime Triangle = Bull Flag Breakout
◆ Aqua Diamond = Flat Top Breakout
● Yellow Circle = Micro Pullback
▲ Green Triangle = PM High Break
↑ Lime Arrow = R2G (bullish)
↓ Red Arrow = G2R (bearish)
Dashboard Quick Read
🎯 = Entry signal active
✅ = All pillars pass
🟢 = Day is green
🔥 = Strong (gap/rotation)
✓ = Criteria met
✗ = Criteria failed
Quality Score
8-10 = A+ (Best)
6-7 = A (Good)
4-5 = B (Average)
0-3 = C (Weak)
Key Levels
Orange Line = Prior Close (R2G level)
Green Line = PM High (breakout level)
Red Line = PM Low (support)
Purple Line = VWAP
Yellow/Orange = EMA 9/20
Happy Trading! 🎯📈
For questions or issues, use TradingView's comment section on the indicator page.
Smart Money Concepts [XoRonX]# Smart Money Concepts (SMC) - Advanced Trading Indicator
## 📊 Deskripsi
**Smart Money Concepts ** adalah indicator trading komprehensif yang menggabungkan konsep Smart Money Trading dengan berbagai alat teknikal analisis modern. Indicator ini dirancang untuk membantu trader mengidentifikasi pergerakan institusional (smart money), struktur pasar, zona supply/demand, dan berbagai sinyal trading penting.
Indicator ini mengintegrasikan multiple timeframe analysis, order blocks detection, fair value gaps, fibonacci retracement, volume profile, RSI multi-timeframe, dan moving averages dalam satu platform yang powerful dan mudah digunakan.
---
## 🎯 Fitur Utama
### 1. **Smart Money Structure**
- **Internal Structure** - Struktur pasar jangka pendek untuk entry presisi
- **Swing Structure** - Struktur pasar jangka panjang untuk trend analysis
- **BOS (Break of Structure)** - Konfirmasi kelanjutan trend
- **CHoCH (Change of Character)** - Deteksi potensi reversal
### 2. **Order Blocks**
- **Internal Order Blocks** - Zona demand/supply jangka pendek
- **Swing Order Blocks** - Zona demand/supply jangka panjang
- Filter otomatis berdasarkan volatilitas (ATR/Range)
- Mitigation tracking (High/Low atau Close)
- Customizable display (jumlah order blocks yang ditampilkan)
### 3. **Equal Highs & Equal Lows (EQH/EQL)**
- Deteksi otomatis equal highs/lows
- Indikasi liquidity zones
- Threshold adjustment untuk sensitivitas
- Visual lines dan labels
### 4. **Fair Value Gaps (FVG)**
- Multi-timeframe FVG detection
- Auto threshold filtering
- Bullish & Bearish FVG boxes
- Extension control
- Color customization
### 5. **Premium & Discount Zones**
- Premium Zone (75-100% dari range)
- Equilibrium Zone (47.5-52.5% dari range)
- Discount Zone (0-25% dari range)
- Auto-update berdasarkan swing high/low
### 6. **Fibonacci Retracement**
- **Equilibrium to Discount** - Fib dari EQ ke discount zone
- **Equilibrium to Premium** - Fib dari EQ ke premium zone
- **Discount to Premium** - Fib full range
- Reverse option
- Show/hide lines
- Custom colors
### 7. **Volume Profile (VRVP)**
- Visible Range Volume Profile
- Point of Control (POC)
- Value Area (70% volume)
- Auto-adjust rows
- Placement options (Left/Right)
- Width customization
### 8. **RSI Multi-Timeframe**
- Monitor 3 timeframes sekaligus
- Overbought/Oversold signals
- Visual table display
- Color-coded signals (Red OB, Green OS)
- Customizable position & size
### 9. **Moving Averages**
- 3 Moving Average lines
- Pilihan tipe: EMA, SMA, WMA
- Automatic/Manual period mode
- Individual color & width settings
- Cross alerts (MA vs MA, Price vs MA)
### 10. **Multi-Timeframe Levels**
- Support up to 5 different timeframes
- Previous high/low levels
- Custom line styles
- Color customization
### 11. **Candle Color**
- Color candles berdasarkan trend
- Bullish = Green, Bearish = Red
- Optional toggle
---
## 🛠️ Cara Penggunaan
### **A. Setup Awal**
1. **Tambahkan Indicator ke Chart**
- Buka TradingView
- Klik "Indicators" → "My Scripts" atau paste code
- Pilih "Smart Money Concepts "
2. **Pilih Mode Display**
- **Historical**: Tampilkan semua struktur (untuk backtesting)
- **Present**: Hanya tampilkan struktur terbaru (clean chart)
3. **Pilih Style**
- **Colored**: Warna berbeda untuk bullish/bearish
- **Monochrome**: Tema warna abu-abu
---
### **B. Penggunaan Fitur**
#### **1. Smart Money Structure**
**Internal Structure (Real-time):**
- ✅ Aktifkan "Show Internal Structure"
- Pilih tampilan: All, BOS only, atau CHoCH only
- Gunakan untuk entry timing presisi
- Filter confluence untuk mengurangi noise
**Swing Structure:**
- ✅ Aktifkan "Show Swing Structure"
- Pilih tampilan struktur bullish/bearish
- Adjust "Swings Length" (default: 50)
- Gunakan untuk konfirmasi trend utama
**Tips:**
- BOS = Konfirmasi trend continuation
- CHoCH = Warning untuk possible reversal
- Tunggu price retest ke order block setelah BOS
---
#### **2. Order Blocks**
**Setup:**
- ✅ Aktifkan Internal/Swing Order Blocks
- Set jumlah blocks yang ditampil (1-20)
- Pilih filter: ATR atau Cumulative Mean Range
- Pilih mitigation: Close atau High/Low
**Cara Trading:**
1. Tunggu BOS/CHoCH terbentuk
2. Identifikasi order block terdekat
3. Wait for price pullback ke order block
4. Entry saat price respek order block (rejection)
5. Stop loss di bawah/atas order block
6. Target: swing high/low berikutnya
**Color Code:**
- 🔵 Light Blue = Internal Bullish OB
- 🔴 Light Red = Internal Bearish OB
- 🔵 Dark Blue = Swing Bullish OB
- 🔴 Dark Red = Swing Bearish OB
---
#### **3. Equal Highs/Lows (EQH/EQL)**
**Setup:**
- ✅ Aktifkan "Equal High/Low"
- Set "Bars Confirmation" (default: 3)
- Adjust threshold (0-0.5, default: 0.1)
**Interpretasi:**
- EQH = Liquidity di atas, kemungkinan sweep lalu dump
- EQL = Liquidity di bawah, kemungkinan sweep lalu pump
- Biasanya smart money akan grab liquidity sebelum move besar
**Trading Strategy:**
- Wait for EQH/EQL formation
- Anticipate liquidity grab
- Entry setelah sweep dengan konfirmasi (order block, FVG, CHoCH)
---
#### **4. Fair Value Gaps (FVG)**
**Setup:**
- ✅ Aktifkan "Fair Value Gaps"
- Pilih timeframe (default: chart timeframe)
- Enable/disable auto threshold
- Set extension bars
**Cara Trading:**
1. Bullish FVG = Support zone untuk buy
2. Bearish FVG = Resistance zone untuk sell
3. Price tends to fill FVG (retest)
4. Entry saat price kembali ke FVG
5. Partial fill = valid, full fill = invalidated
**Tips:**
- FVG + Order Block = High probability setup
- Multi-timeframe FVG lebih kuat
- Unfilled FVG = strong momentum
---
#### **5. Premium & Discount Zones**
**Setup:**
- ✅ Aktifkan "Premium/Discount Zones"
- Zones akan auto-update berdasarkan swing high/low
**Interpretasi:**
- 🟢 **Discount Zone** = Area BUY (price murah)
- ⚪ **Equilibrium** = Neutral (50%)
- 🔴 **Premium Zone** = Area SELL (price mahal)
**Trading Strategy:**
- BUY dari discount zone
- SELL dari premium zone
- Avoid trading di equilibrium
- Combine dengan structure confirmation
---
#### **6. Fibonacci Retracement**
**Setup:**
- Pilih Fib yang ingin ditampilkan:
- Equilibrium to Discount
- Equilibrium to Premium
- Discount to Premium
- Toggle show lines
- Enable reverse jika perlu
- Custom colors
**Key Levels:**
- 0.236 = Shallow retracement
- 0.382 = Common retracement
- 0.5 = 50% golden level
- 0.618 = Golden ratio (penting!)
- 0.786 = Deep retracement
**Cara Pakai:**
- 0.618-0.786 = Ideal entry zone dalam trend
- Combine dengan order blocks
- Wait for confirmation candle
---
#### **7. Volume Profile (VRVP)**
**Setup:**
- ✅ Aktifkan "Show Volume Profile"
- Set jumlah rows (10-100)
- Adjust width (5-50%)
- Pilih placement (Left/Right)
- Enable POC dan Value Area
**Interpretasi:**
- **POC (Point of Control)** = Harga dengan volume tertinggi = magnet
- **Value Area** = 70% volume = fair price range
- **Low Volume Nodes** = Weak support/resistance
- **High Volume Nodes** = Strong support/resistance
**Trading:**
- POC acts as support/resistance
- Price tends to return to POC
- Breakout dari Value Area = momentum
---
#### **8. RSI Multi-Timeframe**
**Setup:**
- ✅ Aktifkan "Show RSI Table"
- Set 3 timeframes (default: chart, 5m, 15m)
- Set RSI period (default: 14)
- Set Overbought level (default: 70)
- Set Oversold level (default: 30)
- Pilih posisi & ukuran table
**Interpretasi:**
- 🟢 **OS (Oversold)** = RSI ≤ 30 = Kondisi jenuh jual
- 🔴 **OB (Overbought)** = RSI ≥ 70 = Kondisi jenuh beli
- **-** = Neutral zone
**Trading Strategy:**
1. Multi-timeframe alignment = strong signal
2. OS + Bullish structure = BUY signal
3. OB + Bearish structure = SELL signal
4. Divergence RSI vs Price = reversal warning
**Contoh:**
- TF1: OS, TF2: OS, TF3: OS + Price di discount zone = STRONG BUY
---
#### **9. Moving Averages**
**Setup:**
- Pilih MA Type: EMA, SMA, atau WMA (berlaku untuk ketiga MA)
- Pilih Period Mode: Automatic atau Manual
- Set period untuk MA 1, 2, 3 (default: 20, 50, 100)
- Custom color & width per MA
- ✅ Enable Cross Alerts
**Interpretasi:**
- **Golden Cross** = MA fast cross above MA slow = Bullish
- **Death Cross** = MA fast cross below MA slow = Bearish
- Price above all MAs = Strong uptrend
- Price below all MAs = Strong downtrend
**Trading Strategy:**
1. MA1 (20) = Short-term trend
2. MA2 (50) = Medium-term trend
3. MA3 (100) = Long-term trend
**Entry Signals:**
- Price bounce dari MA dalam trend = continuation
- MA cross dengan konfirmasi structure = entry
- Multiple MA confluence = strong support/resistance
**Alerts Available:**
- MA1 cross MA2/MA3
- MA2 cross MA3
- Price cross any MA
---
#### **10. Multi-Timeframe Levels**
**Setup:**
- Enable HTF Level 1-5
- Set timeframes (contoh: 5m, 1H, 4H, D, W)
- Pilih line style (solid/dashed/dotted)
- Custom colors
**Cara Pakai:**
- Previous high/low dari HTF = strong S/R
- Breakout HTF level = significant move
- Multiple HTF levels confluence = major zone
---
### **C. Trading Setup Combination**
#### **Setup 1: High Probability Buy (Bullish)**
1. ✅ Swing structure: Bullish BOS
2. ✅ Price di Discount Zone
3. ✅ Pullback ke Bullish Order Block
4. ✅ Bullish FVG di bawah
5. ✅ RSI Multi-TF: Oversold
6. ✅ Price bounce dari MA
7. ✅ POC/Value Area support
8. ✅ Fibonacci 0.618-0.786 retracement
**Entry:** Saat price reject dari order block dengan confirmation candle
**Stop Loss:** Below order block
**Target:** Swing high atau premium zone
---
#### **Setup 2: High Probability Sell (Bearish)**
1. ✅ Swing structure: Bearish BOS
2. ✅ Price di Premium Zone
3. ✅ Pullback ke Bearish Order Block
4. ✅ Bearish FVG di atas
5. ✅ RSI Multi-TF: Overbought
6. ✅ Price reject dari MA
7. ✅ POC/Value Area resistance
8. ✅ Fibonacci 0.618-0.786 retracement
**Entry:** Saat price reject dari order block dengan confirmation candle
**Stop Loss:** Above order block
**Target:** Swing low atau discount zone
---
#### **Setup 3: Liquidity Grab (EQH/EQL)**
1. ✅ Identifikasi EQH atau EQL
2. ✅ Wait for liquidity sweep
3. ✅ Konfirmasi dengan CHoCH
4. ✅ Order block terbentuk setelah sweep
5. ✅ Entry saat retest order block
---
### **D. Tips & Best Practices**
**Risk Management:**
- Selalu gunakan stop loss
- Risk 1-2% per trade
- Risk:Reward minimum 1:2
- Jangan over-leverage
**Confluence adalah Kunci:**
- Minimal 3-4 konfirmasi sebelum entry
- Lebih banyak konfirmasi = higher probability
- Quality over quantity
**Timeframe Analysis:**
- HTF (Higher Timeframe) = Trend direction
- LTF (Lower Timeframe) = Entry timing
- Align dengan HTF trend
**Backtesting:**
- Gunakan mode "Historical"
- Test strategy di berbagai market condition
- Record dan analyze hasil
**Market Condition:**
- Trending market = Follow BOS, use order blocks
- Ranging market = Use premium/discount zones, EQH/EQL
- High volatility = Wider stops, wait for clear structure
**Avoid:**
- Trading di equilibrium zone
- Entry tanpa konfirmasi
- Fighting the trend
- Overleveraging
- Emotional trading
---
## 📈 Recommended Settings
### **For Scalping (1m - 5m):**
- Internal Structure: ON
- Swing Structure: OFF
- Order Blocks: Internal only
- RSI Timeframes: 1m, 5m, 15m
- MA Periods: 9, 21, 50
### **For Day Trading (15m - 1H):**
- Internal Structure: ON
- Swing Structure: ON
- Order Blocks: Both
- RSI Timeframes: 15m, 1H, 4H
- MA Periods: 20, 50, 100
### **For Swing Trading (4H - D):**
- Internal Structure: OFF
- Swing Structure: ON
- Order Blocks: Swing only
- RSI Timeframes: 4H, D, W
- MA Periods: 20, 50, 200
---
## ⚠️ Disclaimer
Indicator ini adalah alat bantu analisis teknikal. Tidak ada indicator yang 100% akurat. Selalu:
- Lakukan analisa fundamental
- Gunakan proper risk management
- Praktik di demo account terlebih dahulu
- Trading memiliki resiko, trade at your own risk
---
## 📝 Version Info
**Version:** 5.0
**Platform:** TradingView Pine Script v5
**Author:** XoRonX
**Max Labels:** 500
**Max Lines:** 500
**Max Boxes:** 500
---
## 🔄 Updates & Support
Untuk update, bug reports, atau pertanyaan:
- Check documentation regularly
- Test new features in replay mode
- Backup your settings before updates
---
## 🎓 Learning Resources
**Recommended Study:**
1. Smart Money Concepts (SMC) basics
2. Order blocks theory
3. Liquidity concepts
4. ICT (Inner Circle Trader) concepts
5. Volume profile analysis
6. Multi-timeframe analysis
**Practice:**
- Start with higher timeframes
- Master one concept at a time
- Keep a trading journal
- Review your trades weekly
---
**Happy Trading! 🚀📊**
_Remember: The best indicator is your own analysis and discipline._
Liquidity & inducementsHi all!
This indicator will show liquidity and inducements.
I will continue to try to add different types of liquidity and inducements, at this moment it contains 6 kinds of liquidity/inducement, they are:
• Grabs
• Big grabs
• Sweeps
• Turtle soups
• Equal highs/lows (liquidity and inducement)
• BSL & SSL
And 1 type of inducement:
• Retracement
This description will contain indicator examples of each individual liquidity and inducement. They will all be with the default settings.
Settings
First you will find settings for the market structure (BOS/CHoCH/CHoCH+). Select left and right pivot lengths and if the pivots should have a label or not.
This is the base foundation of this indicator and is possible with my library 'PriceAction' ().
You will see solid lines for break of structures (BOS), change of characters (CHoCH) and change of character plus (CHoCH+).
The pivots found will be the core of this indicator and will show you when the closing price breaks it. When that happens a break of structure (BOS) or a change of character (CHoCH or CHoCH+) will be created. The latest 5 pivots found within the current trend will be kept to take action on.
A break of structure is removed if an earlier pivot within the same trend is broken and the pivot's high price for a bullish trend or low price for a bearish trend is more extreme than the BOS pivot's price.
You are able to show the pivots that are used. "HH" (higher high), "HL" (higher low), "LH" (lower high), "LL" (lower low) and "H"/"L" (for pivots (high/low) when the trend has changed) are the labels used.
In the next section ('Liquidity ($$$)') you can select which types of liquidity you want to see. Note that 'Equal highs/lows' can also show inducement (more on that later).
In the section afterwards ('Inducement (IDM)') you can select if you want retracement inducements to be visible or not. More information on what they are later on.
The section for each individual liquidity and/or inducement can first contain a line named 'Pivot', where you can set the pivot lengths (first left, then right). Then you can set the 'Lookback', which means that the 'Lookback' number of past pivots is to take action on. After that you set the 'Timeframe' for the pivots used. That means that all available liquidity/inducements will be from your desired timeframe. Lastly you set the color of the liquidity/inducement (either a single color or bullish followed by bearish colors).
Lastly in the settings you can select the font sizes for the market structure and liquidity/inducements and what style liquidity/inducements lines will have. The sizes defaults to 7 and has a dotted line look.
Grabs
Liquidity grabs and liquidity sweeps are very similar. It all depends on if the current bar closed above/below the liquidity pivot and on if its a continuation or reversal. In a liquidity grab the bar that's above or below the liquidity pivot was not closed above or below it. Like this:
Or
The visual feedback will be a dotted line between the liquidity pivot and liquidity grab bar and a linefill between the high of the liquidity grab bar and the liquidity pivot.
Indicator example:
Big grabs
This is another 'grabs' option. You can show an additional grab if you want to. I suggest having this grab from a higher timeframe or with larger pivot lengths than the other grab.
The default is with the chart timeframe and 10/10 as pivot lengths.
Indicator example:
Sweeps
A liquidity sweep is like a liquidity grab but with the difference that price closes above/below and has a continuation instead of a reversal. If the liquidity pivot was at the same bar as a BOS/CHoCH/CHoCH+ it will not be a liquidity grab but a structural break instead.
They can look like this:
Indicator example;
Turtle soups
If only one candle is beyond the pivot it could be a liquidity grab. It's a grab if price didn't close beyond the liquidity pivot, if so it's invaliditet. Turtle soups are basically false breakouts that takes liquidity (is a false breakout from a pivot with the lengths and timeframe from the settings).
The turtle soup can have a confirmation in the terms of a change of character (CHoCH). You can enable this in the settings section for 'Turtle soups' through the 'Confirmation' checkbox (enabled by default). The turtle soup strategy usually comes with some sort of confirmation, in this case a CHoCH, but it can also be a market structure shift (MSS) or a change in state of delivery (CISD).
The addition of turtle soups is possible through my script 'Turtle soup' ().
The drawing will be a dotted line between the liquidity pivot and the last bar of the false breakout and a box from the start of the false breakout to the end of it.
Indicator example:
Equal highs/lows
Equal highs/lows will always show liquidity, but might also show inducement. Inducement will be shown on equal lows if the trend is bullish and on equal highs if it's bearish, like this:
Or
Equal highs can only be created if the second pivot is lower than the first one. Equal lows can only be created if the second pivot is higher than the first one. If that is not the case it could be a liquidity grab.
When equal highs or equal lows are find that produces inducement (equal lows in a bullish trend and equal highs in a bearish trend), the indicator will first display inducement and will show liquidity once traders are induced to enter the security. Stop loss placement, for liquidity, is 0.1 * the average true range (ATR, of length 14). They will look like this:
Only inducement:
Inducement and liquidity:
Indicator example:
Equal highs/lows inducements can not be triggered after a BOS/CHoCH/CHoCH+. They are cleared upon a structural break.
BSL & SSL
Buyside liquidity (BSL) and sellside liquidity (SSL) will be shown. A pivot that's been mitigated (touched by price) can never be BSL or SSL. The BSL/SSL available will be dynamic while price moves (work in Replay and lower timeframes that moves fast) and pick the latest pivot/s (with left and right lengths from the 'Market structure' section). You can define how many BSL/SSL you want to see with a default value of 1, meaning only 1 BSL and 1 SSL can be shown. If there is no unmitigated high (BSL) or low (SSL), no BSL/SSL will be available to show. If there are BSL/SSL available they're very useful to use as targets for entering a trade.
The will look like this when available;
And without BSL available:
Or
And without SSL available:
Note that the examples without BSL/SSL available could have liquidity available from previous price legs.
This can be an example of a BSL/SSL sequence:
First both buyside and sellside liquidity is available:
Then a new low appears and new sellside liquidity is available:
Then buyside liquidity is mitigated, so only sellside liquidity is available:
A new high pivot appears and buyside liquidity is available again:
Lastly a bearish CHoCH happens and sellside liquidity is mitigated, only buyside liquidity is available:
Retracement
The first retracement after a BOS/CHoCH/CHoCH+ is considered an inducement with the mission to get traders into a trade prematurely to get stopped out. This level is shown and look like this:
Or
A retracement inducement is removed when a new BOS/CHoCH/CHoCH+ appears and it's not triggered.
---------------------------
As of now there aren't any alerts available. You cannot use the Pine Screener from Tradingview either to see new liquidity/inducement events. I have this planned for future updates though.
I hope that this long description makes sense, let me know otherwise! Also let me know if you experience any bugs or have a feature request or just want to share good settings to use.
Best of trading luck!
RED-E Market Structure (Pro V2)RED-E Market Structure - Comprehensive Technical Analysis System
⚠️ EDUCATIONAL TOOL - NO GUARANTEES
This indicator is designed for educational purposes to help traders learn technical analysis concepts. It does not predict future price movements or guarantee profitable trades. Trading involves substantial risk of loss.
═══════════════════════════════════════════════════════════════
📊 WHAT THIS INDICATOR DOES
This indicator combines multiple standard technical analysis methods into a unified system for analyzing market structure, momentum, volume dynamics, and key price levels. Rather than adding 10 separate indicators to your chart, this consolidates related information into one cohesive interface where each component informs the others.
═══════════════════════════════════════════════════════════════
🔧 TECHNICAL METHODOLOGY - HOW IT WORKS
1️⃣ MOMENTUM CANDLE COLORING (6 Levels)
Calculation Method:
- Compares close vs EMA(9) and EMA(21)
- Applies RSI(14) thresholds for strength
- Color codes: Royal Blue (strongest bull) → Cyan → Green → Yellow → Orange → Red (strongest bear) → White (neutral)
Formula Logic:
IF close > EMA(9) AND close > EMA(21) AND close > open:
RSI > 70 = Level 3 Bull (Royal Blue)
RSI 60-70 = Level 2 Bull (Cyan)
RSI < 60 = Level 1 Bull (Green)
Purpose: Visualizes momentum strength by combining trend (EMAs), candle direction, and overbought/oversold conditions (RSI).
2️⃣ ENTRY SIGNAL LABELS
Calculation Method:
- Uses EMA alignment: EMA(9) > EMA(21) > EMA(50) for bullish
- Filters RSI to avoid extremes
- Requires confirming candle
BUY Signal Logic:
IF close > EMA(9) AND RSI between 40-70 AND EMA(9) > EMA(21) > EMA(50) AND close > open
THEN: Display "BUY" label
Purpose: Identifies potential entries when multiple trend and momentum conditions align. This is standard multi-confirmation technical analysis.
3️⃣ VOLUME DELTA PERCENTAGE
Calculation Method:
FOR each bar in lookback period (default 20):
IF close > open: add volume to bullish_volume
IF close < open: add volume to bearish_volume
bullish_percent = (bullish_volume / total_volume) × 100
Purpose: Quantifies buying vs selling pressure as percentages. Shows if volume supports the current trend.
Display: "🟢65.3% | 🔴34.7%" in dashboard
4️⃣ PRE-MARKET HIGH/LOW TRACKING
Calculation Method:
1. Detect pre-market session (4:00-9:30 AM ET)
2. Track highest high during pre-market
3. Track lowest low during pre-market
4. Draw horizontal lines when market opens
Purpose: Pre-market levels often act as support/resistance during regular hours. This automates their tracking and visualization.
5️⃣ OPENING RANGE BREAKOUT (ORB)
Calculation Method:
1. User sets start time (default 9:30 AM) and duration (default 15 min)
2. Track highest high and lowest low during this period
3. Draw box and extend lines
Purpose: The opening range breakout is a well-documented day trading strategy. First X minutes establish a range, and breakouts often signal directional moves.
6️⃣ SUPPORT/RESISTANCE TRENDLINES
Calculation Method:
1. Identify pivot highs: ta.pivothigh(high, 5, 5)
2. Identify pivot lows: ta.pivotlow(low, 5, 5)
3. Connect last two pivot highs = Resistance (red)
4. Connect last two pivot lows = Support (blue)
Purpose: Automatically connects significant pivot points. Based on standard pivot analysis where price respects these levels.
7️⃣ GAMMA ZONE DETECTION
Calculation Method:
1. Calculate 30-min range: (high - low)
2. Calculate 10-period SMA of range
3. Calculate ratio: current_range / average_range
IF ratio < (1.0 / sensitivity): HIGH GAMMA = Low volatility
IF ratio > (1.0 × sensitivity): LOW GAMMA = High volatility
Purpose: Approximates options gamma effects. High gamma = dealers hedge more = suppressed volatility. Low gamma = less hedging = potential explosive moves.
8️⃣ TAKE PROFIT LEVELS (5 Levels + ATR Stop Loss)
Calculation Method:
LONG: TP = entry_price × (1 + percentage/100)
SHORT: TP = entry_price × (1 - percentage/100)
Stop Loss (ATR): entry ± (ATR(14) × multiplier)
Purpose: Automatically calculates percentage-based targets and volatility-adjusted stops. ATR adapts stop to current market conditions.
9️⃣ THE STRAT PATTERN RECOGNITION
Calculation Method:
Compare current bar to previous:
- Strat 3 (outside bar): high > high AND low < low
- Strat 1 (inside bar): high ≤ high AND low ≥ low
- Strat 2 (directional): All others
Purpose: The Strat is a price action system categorizing bars by relationship to previous bars. This automates classification.
🔟 FIBONACCI RETRACEMENTS
Calculation Method:
1. Find highest high in lookback (default 30 bars)
2. Find lowest low in lookback
3. Calculate: 0.0, 0.382, 0.5, 0.618, 1.0 levels
Purpose: Standard Fibonacci tool. These ratios are commonly used support/resistance in technical analysis.
1️⃣1️⃣ MULTI-TIMEFRAME ANALYSIS
Calculation Method:
FOR each timeframe (default 15m, 1H, 4H):
Check if close > EMA(9) on that timeframe
IF true: "BULLISH", else: "BEARISH"
Purpose: Shows trend alignment across timeframes using Pine's request.security(). Common confirmation technique.
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💡 WHY THESE COMPONENTS WORK TOGETHER
This indicator's originality lies in its unified system approach:
1. TREND IDENTIFICATION (EMAs, MTF) - Shows direction
2. MOMENTUM MEASUREMENT (RSI, candles) - Shows strength
3. VOLUME CONFIRMATION (Volume Delta) - Shows conviction
4. KEY LEVELS (PM, ORB, Fib, S/R) - Shows decision points
5. RISK MANAGEMENT (TP levels, ATR stops) - Shows exits
VALUE OF INTEGRATION:
Rather than 10 separate indicators creating chart clutter, this consolidates related concepts where each component provides different information that, when viewed together, gives a more complete market picture.
Example Integration:
- Entry signal appears (EMA + RSI aligned)
- Volume Delta confirms (more buying than selling)
- MTF shows higher timeframes agree
- TP levels auto-calculate with good risk:reward
- Support trendline nearby provides stop reference
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⚙️ CUSTOMIZATION OPTIONS
All features independently toggleable:
- EMAs: Adjust lengths (9, 21, 50, 200), colors, widths
- RSI: Change overbought/oversold levels (70/30)
- Volume Delta: Adjust lookback period (20)
- ORB: Set custom start time, duration, timezone
- Gamma: Adjust sensitivity (1-10)
- TP Levels: Customize all 5 percentages
- Dashboard: Reposition, resize, recolor
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📖 HOW TO USE
Step 1 - Assess Context:
- Check MTF Dashboard for alignment
- Check EMA indicator for trend
- Check Gamma Zone for volatility expectation
Step 2 - Identify Setups:
- Wait for BUY/SELL signal
- Check Volume Delta matches direction
- Verify RSI not extreme (30-70)
- Look for support/resistance confluence
Step 3 - Evaluate Risk:Reward:
- Review TP3 R:R ratio (target 2:1+)
- Check stop loss placement
- Ensure risk acceptable
Step 4 - Monitor:
- Track P&L % in real-time
- Use TP levels as potential exits
- Adjust stops based on S/R
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⚠️ LIMITATIONS & REALISTIC EXPECTATIONS
This indicator does NOT:
- Predict future price movements
- Guarantee profitable trades
- Work in all market conditions
- Replace proper education and practice
This indicator CAN:
- Display standard technical indicators in organized way
- Automate common calculations
- Visualize multiple analysis methods simultaneously
- Help learn how different indicators relate
Key Understanding:
All technical indicators use historical data. They help identify patterns and conditions but cannot predict the future. Successful trading requires risk management, psychology, and experience—not just indicators.
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📚 EDUCATIONAL CONCEPTS TAUGHT
- How EMAs show trend direction and alignment
- How RSI identifies momentum extremes
- How volume confirms or diverges from price
- How support/resistance levels form
- How multiple timeframes provide context
- How ATR adapts stops to volatility
- How risk:reward ratios work
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📊 BEST SUITED FOR
- Scalping: 1m-5m charts with quick entries/exits
- Day Trading: 15m-1H focusing on ORB and PM levels
- Swing Trading: 4H-D following major trends
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⚠️ RISK DISCLAIMER
Trading involves substantial risk of loss. This educational tool:
- Does NOT guarantee profits
- Cannot predict future performance
- Requires proper risk management
- Should be practiced on demo accounts first
Always use stop losses, risk only 1-2% per trade, and consult licensed financial professionals before trading with real capital.
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Educational tool for learning technical analysis. Not financial advice. Past results do not indicate future performance.
Algorithm Predator - ProAlgorithm Predator - Pro: Advanced Multi-Agent Reinforcement Learning Trading System
Algorithm Predator - Pro combines four specialized market microstructure agents with a state-of-the-art reinforcement learning framework . Unlike traditional indicator mashups, this system implements genuine machine learning to automatically discover which detection strategies work best in current market conditions and adapts continuously without manual intervention.
Core Innovation: Rather than forcing traders to interpret conflicting signals, this system uses 15 different multi-armed bandit algorithms and a full reinforcement learning stack (Q-Learning, TD(λ) with eligibility traces, and Policy Gradient with REINFORCE) to learn optimal agent selection policies. The result is a self-improving system that gets smarter with every trade.
Target Users: Swing traders, day traders, and algorithmic traders seeking systematic signal generation with mathematical rigor. Suitable for stocks, forex, crypto, and futures on liquid instruments (>100k daily volume).
Why These Components Are Combined
The Fundamental Problem
No single indicator works consistently across all market regimes. What works in trending markets fails in ranging conditions. Traditional solutions force traders to manually switch indicators (slow, error-prone) or interpret all signals simultaneously (cognitive overload).
This system solves the problem through automated meta-learning: Deploy multiple specialized agents designed for specific market microstructure conditions, then use reinforcement learning to discover which agent (or combination) performs best in real-time.
Why These Specific Four Agents?
The four agents provide orthogonal failure mode coverage —each agent's weakness is another's strength:
Spoofing Detector - Optimal in consolidation/manipulation; fails in trending markets (hedged by Exhaustion Detector)
Exhaustion Detector - Optimal at trend climax; fails in range-bound markets (hedged by Liquidity Void)
Liquidity Void - Optimal pre-breakout compression; fails in established trends (hedged by Mean Reversion)
Mean Reversion - Optimal in low volatility; fails in strong trends (hedged by Spoofing Detector)
This creates complete market state coverage where at least one agent should perform well in any condition. The bandit system identifies which one without human intervention.
Why Reinforcement Learning vs. Simple Voting?
Traditional consensus systems have fatal flaws: equal weighting assumes all agents are equally reliable (false), static thresholds don't adapt, and no learning means past mistakes repeat indefinitely.
Reinforcement learning solves this through the exploration-exploitation tradeoff: Continuously test underused agents (exploration) while primarily relying on proven winners (exploitation). Over time, the system builds a probability distribution over agent quality reflecting actual market performance.
Mathematical Foundation: Multi-armed bandit problem from probability theory, where each agent is an "arm" with unknown reward distribution. The goal is to maximize cumulative reward while efficiently learning each arm's true quality.
The Four Trading Agents: Technical Explanation
Agent 1: 🎭 Spoofing Detector (Institutional Manipulation Detection)
Theoretical Basis: Market microstructure theory on order flow toxicity and information asymmetry. Based on research by Easley, López de Prado, and O'Hara on high-frequency trading manipulation.
What It Detects:
1. Iceberg Orders (Hidden Liquidity Absorption)
Method: Monitors volume spikes (>2.5× 20-period average) with minimal price movement (<0.3× ATR)
Formula: score += (close > open ? -2.5 : 2.5) when volume > vol_avg × 2.5 AND abs(close - open) / ATR < 0.3
Interpretation: Large volume without price movement indicates institutional absorption (buying) or distribution (selling) using hidden orders
Signal Logic: Contrarian—fade false breakouts caused by institutional manipulation
2. Spoofing Patterns (Fake Liquidity via Layering)
Method: Analyzes candlestick wick-to-body ratios during volume spikes
Formula: if upper_wick > body × 2 AND volume_spike: score += 2.0
Mechanism: Spoofing creates large wicks (orders pulled before execution) with volume evidence
Signal Logic: Wick direction indicates trapped participants; trade against the failed move
3. Post-Manipulation Reversals
Method: Tracks volume decay after manipulation events
Formula: if volume > vol_avg × 3 AND volume / volume < 0.3: score += (close > open ? -1.5 : 1.5)
Interpretation: Sharp volume drop after manipulation indicates exhaustion of manipulative orders
Why It Works: Institutional manipulation creates detectable microstructure anomalies. While retail traders see "mysterious reversals," this agent quantifies the order flow patterns causing them.
Parameter: i_spoof (sensitivity 0.5-2.0) - Controls detection threshold
Best Markets: Consolidations before breakouts, London/NY overlap windows, stocks with institutional ownership >70%
Agent 2: ⚡ Exhaustion Detector (Momentum Failure Analysis)
Theoretical Basis: Technical analysis divergence theory combined with VPIN reversals from market microstructure literature.
What It Detects:
1. Price-RSI Divergence (Momentum Deceleration)
Method: Compares 5-bar price ROC against RSI change
Formula: if price_roc > 5% AND rsi_current < rsi : score += 1.8
Mathematics: Second derivative detecting inflection points
Signal Logic: When price makes higher highs but momentum makes lower highs, expect mean reversion
2. Volume Exhaustion (Buying/Selling Climax)
Method: Identifies strong price moves (>5% ROC) with declining volume (<-20% volume ROC)
Formula: if price_roc > 5 AND vol_roc < -20: score += 2.5
Interpretation: Price extension without volume support indicates retail chasing while institutions exit
3. Momentum Deceleration (Acceleration Analysis)
Method: Compares recent 3-bar momentum to prior 3-bar momentum
Formula: deceleration = abs(mom1) < abs(mom2) × 0.5 where momentum significant (> ATR)
Signal Logic: When rate of price change decelerates significantly, anticipate directional shift
Why It Works: Momentum is lagging, but momentum divergence is leading. By comparing momentum's rate of change to price, this agent detects "weakening conviction" before reversals become obvious.
Parameter: i_momentum (sensitivity 0.5-2.0)
Best Markets: Strong trends reaching climax, parabolic moves, instruments with high retail participation
Agent 3: 💧 Liquidity Void Detector (Breakout Anticipation)
Theoretical Basis: Market liquidity theory and order book dynamics. Based on research into "liquidity holes" and volatility compression preceding expansion.
What It Detects:
1. Bollinger Band Squeeze (Volatility Compression)
Method: Monitors Bollinger Band width relative to 50-period average
Formula: bb_width = (upper_band - lower_band) / middle_band; triggers when < 0.6× average
Mathematical Foundation: Regression to the mean—low volatility precedes high volatility
Signal Logic: When volatility compresses AND cumulative delta shows directional bias, anticipate breakout
2. Volume Profile Gaps (Thin Liquidity Zones)
Method: Identifies sharp volume transitions indicating few limit orders
Formula: if volume < vol_avg × 0.5 AND volume < vol_avg × 0.5 AND volume > vol_avg × 1.5
Interpretation: Sudden volume drop after spike indicates price moved through order book to low-opposition area
Signal Logic: Price accelerates through low-liquidity zones
3. Stop Hunts (Liquidity Grabs Before Reversals)
Method: Detects new 20-bar highs/lows with immediate reversal and rejection wick
Formula: if new_high AND close < high - (high - low) × 0.6: score += 3.0
Mechanism: Market makers push price to trigger stop-loss clusters, then reverse
Signal Logic: Enter reversal after stop-hunt completes
Why It Works: Order book theory shows price moves fastest through zones with minimal liquidity. By identifying these zones before major moves, this agent provides early entry for high-reward breakouts.
Parameter: i_liquidity (sensitivity 0.5-2.0)
Best Markets: Range-bound pre-breakout setups, volatility compression zones, instruments prone to gap moves
Agent 4: 📊 Mean Reversion (Statistical Arbitrage Engine)
Theoretical Basis: Statistical arbitrage theory, Ornstein-Uhlenbeck mean-reverting processes, and pairs trading methodology applied to single instruments.
What It Detects:
1. Z-Score Extremes (Standard Deviation Analysis)
Method: Calculates price distance from 20-period and 50-period SMAs in standard deviation units
Formula: zscore_20 = (close - SMA20) / StdDev(50)
Statistical Interpretation: Z-score >2.0 means price is 2 standard deviations above mean (97.5th percentile)
Trigger Logic: if abs(zscore_20) > 2.0: score += zscore_20 > 0 ? -1.5 : 1.5 (fade extremes)
2. Ornstein-Uhlenbeck Process (Mean-Reverting Stochastic Model)
Method: Models price as mean-reverting stochastic process: dx = θ(μ - x)dt + σdW
Implementation: Calculates spread = close - SMA20, then z-score of spread vs. spread distribution
Formula: ou_signal = (spread - spread_mean) / spread_std
Interpretation: Measures "tension" pulling price back to equilibrium
3. Correlation Breakdown (Regime Change Detection)
Method: Compares 50-period price-volume correlation to 10-period correlation
Formula: corr_breakdown = abs(typical_corr - recent_corr) > 0.5
Enhancement: if corr_breakdown AND abs(zscore_20) > 1.0: score += zscore_20 > 0 ? -1.2 : 1.2
Why It Works: Mean reversion is the oldest quantitative strategy (1970s pairs trading at Morgan Stanley). While simple, it remains effective because markets exhibit periodic equilibrium-seeking behavior. This agent applies rigorous statistical testing to identify when mean reversion probability is highest.
Parameter: i_statarb (sensitivity 0.5-2.0)
Best Markets: Range-bound instruments, low-volatility periods (VIX <15), algo-dominated markets (forex majors, index futures)
Multi-Armed Bandit System: 15 Algorithms Explained
What Is a Multi-Armed Bandit Problem?
Origin: Named after slot machines ("one-armed bandits"). Imagine facing multiple slot machines, each with unknown payout rates. How do you maximize winnings?
Formal Definition: K arms (agents), each with unknown reward distribution with mean μᵢ. Goal: Maximize cumulative reward over T trials. Challenge: Balance exploration (trying uncertain arms to learn quality) vs. exploitation (using known-best arm for immediate reward).
Trading Application: Each agent is an "arm." After each trade, receive reward (P&L). Must decide which agent to trust for next signal.
Algorithm Categories
Bayesian Approaches (probabilistic, optimal for stationary environments):
Thompson Sampling
Bootstrapped Thompson Sampling
Discounted Thompson Sampling
Frequentist Approaches (confidence intervals, deterministic):
UCB1
UCB1-Tuned
KL-UCB
SW-UCB (Sliding Window)
D-UCB (Discounted)
Adversarial Approaches (robust to non-stationary environments):
EXP3-IX
Hedge
FPL-Gumbel
Reinforcement Learning Approaches (leverage learned state-action values):
Q-Values (from Q-Learning)
Policy Network (from Policy Gradient)
Simple Baseline:
Epsilon-Greedy
Softmax
Key Algorithm Details
Thompson Sampling (DEFAULT - RECOMMENDED)
Theoretical Foundation: Bayesian decision theory with conjugate priors. Published by Thompson (1933), rediscovered for bandits by Chapelle & Li (2011).
How It Works:
Model each agent's reward distribution as Beta(α, β) where α = wins, β = losses
Each step, sample from each agent's beta distribution: θᵢ ~ Beta(αᵢ, βᵢ)
Select agent with highest sample: argmaxᵢ θᵢ
Update winner's distribution after observing outcome
Mathematical Properties:
Optimality: Achieves logarithmic regret O(K log T) (proven optimal)
Bayesian: Maintains probability distribution over true arm means
Automatic Balance: High uncertainty → more exploration; high certainty → exploitation
⚠️ CRITICAL APPROXIMATION: This is a pseudo-random approximation of true Thompson Sampling. True implementation requires random number generation from beta distributions, which Pine Script doesn't provide. This version uses Box-Muller transform with market data (price/volume decimal digits) as entropy source. While not mathematically pure, it maintains core exploration-exploitation balance and learns agent preferences effectively.
When To Use: Best all-around choice. Handles non-stationary markets reasonably well, balances exploration naturally, highly sample-efficient.
UCB1 (Upper Confidence Bound)
Formula: UCB_i = reward_mean_i + sqrt(2 × ln(total_pulls) / pulls_i)
Interpretation: First term (exploitation) + second term (exploration bonus for less-tested arms)
Mathematical Properties:
Deterministic : Always selects same arm given same state
Regret Bound: O(K log T) — same optimality as Thompson Sampling
Interpretable: Can visualize confidence intervals
When To Use: Prefer deterministic behavior, want to visualize uncertainty, stable markets
EXP3-IX (Exponential Weights - Adversarial)
Theoretical Foundation: Adversarial bandit algorithm. Assumes environment may be actively hostile (worst-case analysis).
How It Works:
Maintain exponential weights: w_i = exp(η × cumulative_reward_i)
Select agent with probability proportional to weights: p_i = (1-γ)w_i/Σw_j + γ/K
After outcome, update with importance weighting: estimated_reward = observed_reward / p_i
Mathematical Properties:
Adversarial Regret: O(sqrt(TK log K)) even if environment is adversarial
No Assumptions: Doesn't assume stationary or stochastic reward distributions
Robust: Works even when optimal arm changes continuously
When To Use: Extreme non-stationarity, don't trust reward distribution assumptions, want robustness over efficiency
KL-UCB (Kullback-Leibler Upper Confidence Bound)
Theoretical Foundation: Uses KL-divergence instead of Hoeffding bounds. Tighter confidence intervals.
Formula (conceptual): Find largest q such that: n × KL(p||q) ≤ ln(t) + 3×ln(ln(t))
Mathematical Properties:
Tighter Bounds: KL-divergence adapts to reward distribution shape
Asymptotically Optimal: Better constant factors than UCB1
Computationally Intensive: Requires iterative binary search (15 iterations)
When To Use: Maximum sample efficiency needed, willing to pay computational cost, long-term trading (>500 bars)
Q-Values & Policy Network (RL-Based Selection)
Unique Feature: Instead of treating agents as black boxes with scalar rewards, these algorithms leverage the full RL state representation .
Q-Values Selection:
Uses learned Q-values: Q(state, agent_i) from Q-Learning
Selects agent via softmax over Q-values for current market state
Advantage: Selects based on state-conditional quality (which agent works best in THIS market state)
Policy Network Selection:
Uses neural network policy: π(agent | state, θ) from Policy Gradient
Direct policy over agents given market features
Advantage: Can learn non-linear relationships between market features and agent quality
When To Use: After 200+ RL updates (Q-Values) or 500+ updates (Policy Network) when models converged
Machine Learning & Reinforcement Learning Stack
Why Both Bandits AND Reinforcement Learning?
Critical Distinction:
Bandits treat agents as contextless black boxes: "Agent 2 has 60% win rate"
Reinforcement Learning adds state context: "Agent 2 has 60% win rate WHEN trend_score > 2 and RSI < 40"
Power of Combination: Bandits provide fast initial learning with minimal assumptions. RL provides state-dependent policies for superior long-term performance.
Component 1: Q-Learning (Value-Based RL)
Algorithm: Temporal Difference Learning with Bellman equation.
State Space: 54 discrete states formed from:
trend_state = {0: bearish, 1: neutral, 2: bullish} (3 values)
volatility_state = {0: low, 1: normal, 2: high} (3 values)
RSI_state = {0: oversold, 1: neutral, 2: overbought} (3 values)
volume_state = {0: low, 1: high} (2 values)
Total states: 3 × 3 × 3 × 2 = 54 states
Action Space: 5 actions (No trade, Agent 1, Agent 2, Agent 3, Agent 4)
Total state-action pairs: 54 × 5 = 270 Q-values
Bellman Equation:
Q(s,a) ← Q(s,a) + α ×
Parameters:
α (learning rate): 0.01-0.50, default 0.10 - Controls step size for updates
γ (discount factor): 0.80-0.99, default 0.95 - Values future rewards
ε (exploration): 0.01-0.30, default 0.10 - Probability of random action
Update Mechanism:
Position opens with state s, action a (selected agent)
Every bar position is open: Calculate floating P&L → scale to reward
Perform online TD update
When position closes: Perform terminal update with final reward
Gradient Clipping: TD errors clipped to ; Q-values clipped to for stability.
Why It Works: Q-Learning learns "quality" of each agent in each market state through trial and error. Over time, builds complete state-action value function enabling optimal state-dependent agent selection.
Component 2: TD(λ) Learning (Temporal Difference with Eligibility Traces)
Enhancement Over Basic Q-Learning: Credit assignment across multiple time steps.
The Problem TD(λ) Solves:
Position opens at t=0
Market moves favorably at t=3
Position closes at t=8
Question: Which earlier decisions contributed to success?
Basic Q-Learning: Only updates Q(s₈, a₈) ← reward
TD(λ): Updates ALL visited state-action pairs with decayed credit
Eligibility Trace Formula:
e(s,a) ← γ × λ × e(s,a) for all s,a (decay all traces)
e(s_current, a_current) ← 1 (reset current trace)
Q(s,a) ← Q(s,a) + α × TD_error × e(s,a) (update all with trace weight)
Lambda Parameter (λ): 0.5-0.99, default 0.90
λ=0: Pure 1-step TD (only immediate next state)
λ=1: Full Monte Carlo (entire episode)
λ=0.9: Balance (recommended)
Why Superior: Dramatically faster learning for multi-step tasks. Q-Learning requires many episodes to propagate rewards backwards; TD(λ) does it in one.
Component 3: Policy Gradient (REINFORCE with Baseline)
Paradigm Shift: Instead of learning value function Q(s,a), directly learn policy π(a|s).
Policy Network Architecture:
Input: 12 market features
Hidden: None (linear policy)
Output: 5 actions (softmax distribution)
Total parameters: 12 features × 5 actions + 5 biases = 65 parameters
Feature Set (12 Features):
Price Z-score (close - SMA20) / ATR
Volume ratio (volume / vol_avg - 1)
RSI deviation (RSI - 50) / 50
Bollinger width ratio
Trend score / 4 (normalized)
VWAP deviation
5-bar price ROC
5-bar volume ROC
Range/ATR ratio - 1
Price-volume correlation (20-period)
Volatility ratio (ATR / ATR_avg - 1)
EMA50 deviation
REINFORCE Update Rule:
θ ← θ + α × ∇log π(a|s) × advantage
where advantage = reward - baseline (variance reduction)
Why Baseline? Raw rewards have high variance. Subtracting baseline (running average) centers rewards around zero, reducing gradient variance by 50-70%.
Learning Rate: 0.001-0.100, default 0.010 (much lower than Q-Learning because policy gradients have high variance)
Why Policy Gradient?
Handles 12 continuous features directly (Q-Learning requires discretization)
Naturally maintains exploration through probability distribution
Can converge to stochastic optimal policy
Component 4: Ensemble Meta-Learner (Stacking)
Architecture: Level-1 meta-learner combines Level-0 base learners (Q-Learning, TD(λ), Policy Gradient).
Three Meta-Learning Algorithms:
1. Simple Average (Baseline)
Final_prediction = (Q_prediction + TD_prediction + Policy_prediction) / 3
2. Weighted Vote (Reward-Based)
weight_i ← 0.95 × weight_i + 0.05 × (reward_i + 1)
3. Adaptive Weighting (Gradient-Based) — RECOMMENDED
Loss Function: L = (y_true - ŷ_ensemble)²
Gradient: ∂L/∂weight_i = -2 × (y_true - ŷ_ensemble) × agent_contribution_i
Updates weights via gradient descent with clipping and normalization
Why It Works: Unlike simple averaging, meta-learner discovers which base learner is most reliable in current regime. If Policy Gradient excels in trending markets while Q-Learning excels in ranging, meta-learner learns these patterns and weights accordingly.
Feature Importance Tracking
Purpose: Identify which of 12 features contribute most to successful predictions.
Update Rule: importance_i ← 0.95 × importance_i + 0.05 × |feature_i × reward|
Use Cases:
Feature selection: Drop low-importance features
Market regime detection: Importance shifts reveal regime changes
Agent tuning: If VWAP deviation has high importance, consider boosting agents using VWAP
RL Position Tracking System
Critical Innovation: Proper reinforcement learning requires tracking which decisions led to outcomes.
State Tracking (When Signal Validates):
active_rl_state ← current_market_state (0-53)
active_rl_action ← selected_agent (1-4)
active_rl_entry ← entry_price
active_rl_direction ← 1 (long) or -1 (short)
active_rl_bar ← current_bar_index
Online Updates (Every Bar Position Open):
floating_pnl = (close - entry) / entry × direction
reward = floating_pnl × 10 (scale to meaningful range)
reward = clip(reward, -5.0, 5.0)
Update Q-Learning, TD(λ), and Policy Gradient
Terminal Update (Position Close):
Final Q-Learning update (no next Q-value, terminal state)
Update meta-learner with final result
Update agent memory
Clear position tracking
Exit Conditions:
Time-based: ≥3 bars held (minimum hold period)
Stop-loss: 1.5% adverse move
Take-profit: 2.0% favorable move
Market Microstructure Filters
Why Microstructure Matters
Traditional technical analysis assumes fair, efficient markets. Reality: Markets have friction, manipulation, and information asymmetry. Microstructure filters detect when market structure indicates adverse conditions.
Filter 1: VPIN (Volume-Synchronized Probability of Informed Trading)
Theoretical Foundation: Easley, López de Prado, & O'Hara (2012). "Flow Toxicity and Liquidity in a High-Frequency World."
What It Measures: Probability that current order flow is "toxic" (informed traders with private information).
Calculation:
Classify volume as buy or sell (close > close = buy volume)
Calculate imbalance over 20 bars: VPIN = |Σ buy_volume - Σ sell_volume| / Σ total_volume
Compare to moving average: toxic = VPIN > VPIN_MA(20) × sensitivity
Interpretation:
VPIN < 0.3: Normal flow (uninformed retail)
VPIN 0.3-0.4: Elevated (smart money active)
VPIN > 0.4: Toxic flow (informed institutions dominant)
Filter Logic:
Block LONG when: VPIN toxic AND price rising (don't buy into institutional distribution)
Block SHORT when: VPIN toxic AND price falling (don't sell into institutional accumulation)
Adaptive Threshold: If VPIN toxic frequently, relax threshold; if rarely toxic, tighten threshold. Bounded .
Filter 2: Toxicity (Kyle's Lambda Approximation)
Theoretical Foundation: Kyle (1985). "Continuous Auctions and Insider Trading."
What It Measures: Price impact per unit volume — market depth and informed trading.
Calculation:
price_impact = (close - close ) / sqrt(Σ volume over 10 bars)
impact_zscore = (price_impact - impact_mean) / impact_std
toxicity = abs(impact_zscore)
Interpretation:
Low toxicity (<1.0): Deep liquid market, large orders absorbed easily
High toxicity (>2.0): Thin market or informed trading
Filter Logic: Block ALL SIGNALS when toxicity > threshold. Most dangerous when price breaks from VWAP with high toxicity.
Filter 3: Regime Filter (Counter-Trend Protection)
Purpose: Prevent counter-trend trades during strong trends.
Trend Scoring:
trend_score = 0
trend_score += close > EMA8 ? +1 : -1
trend_score += EMA8 > EMA21 ? +1 : -1
trend_score += EMA21 > EMA50 ? +1 : -1
trend_score += close > EMA200 ? +1 : -1
Range:
Regime Classification:
Strong Bull: trend_score ≥ +3 → Block all SHORT signals
Strong Bear: trend_score ≤ -3 → Block all LONG signals
Neutral: -2 ≤ trend_score ≤ +2 → Allow both directions
Filter 4: Liquidity Boost (Signal Enhancer)
Unique: Unlike other filters (which block), this amplifies signals during low liquidity.
Logic: if volume < vol_avg × 0.7: agent_scores × 1.2
Why It Works: Low liquidity often precedes explosive moves (breakouts). By increasing agent sensitivity during compression, system catches pre-breakout signals earlier.
Technical Implementation & Approximations
⚠️ Critical Approximations Required by Pine Script
1. Thompson Sampling: Pseudo-Random Beta Distribution
Academic Standard: True random sampling from beta distributions using cryptographic RNG
This Implementation: Box-Muller transform for normal distribution using market data (price/volume decimal digits) as entropy source, then scale to beta distribution mean/variance
Impact: Not cryptographically random, may have subtle biases in specific price ranges, but maintains correct mean and approximate variance. Sufficient for bandit agent selection.
2. VPIN: Simplified Volume Classification
Academic Standard: Lee-Ready algorithm or exchange-provided aggressor flags with tick-by-tick data
This Implementation: Bar-based classification: if close > close : buy_volume += volume
Impact: 10-15% precision loss. Works well in directional markets, misclassifies in choppy conditions. Still captures order flow imbalance signal.
3. Policy Gradient: Simplified Per-Action Updates
Academic Standard: Full softmax gradient updating all actions (selected action UP, others DOWN proportionally)
This Implementation: Only updates selected action's weights
Impact: Valid approximation for small action spaces (5 actions). Slower convergence than full softmax but still learns optimal policy.
4. Kyle's Lambda: Simplified Price Impact
Academic Standard: Regression over multiple time scales with signed order flow
This Implementation: price_impact = Δprice_10 / sqrt(Σvolume_10); z_score calculation
Impact: 15-20% precision loss. No proper signed order flow. Still detects informed trading signals at extremes (>2σ).
5. Other Simplifications:
Hawkes Process: Fixed exponential decay (0.9) not MLE-optimized
Entropy: Ratio approximation not true Shannon entropy H(X) = -Σ p(x)·log₂(p(x))
Feature Engineering: 12 features vs. potential 100+ with polynomial interactions
RL Hybrid Updates: Both online and terminal (non-standard but empirically effective)
Overall Precision Loss Estimate: 10-15% compared to academic implementations with institutional data feeds.
Practical Trade-off: For retail trading with OHLCV data, these approximations provide 90%+ of the edge while maintaining full transparency, zero latency, no external dependencies, and runs on any TradingView plan.
How to Use: Practical Guide
Initial Setup (5 Minutes)
Select Trading Mode: Start with "Balanced" for most users
Enable ML/RL System: Toggle to TRUE, select "Full Stack" ML Mode
Bandit Configuration: Algorithm: "Thompson Sampling", Mode: "Switch" or "Blend"
Microstructure Filters: Enable all four filters, enable "Adaptive Microstructure Thresholds"
Visual Settings: Enable dashboard (Top Right), enable all chart visuals
Learning Phase (First 50-100 Signals)
What To Monitor:
Agent Performance Table: Watch win rates develop (target >55%)
Bandit Weights: Should diverge from uniform (0.25 each) after 20-30 signals
RL Core Metrics: "RL Updates" should increase when position open
Filter Status: "Blocked" count indicates filter activity
Optimization Tips:
Too few signals: Lower min_confidence to 0.25, increase agent sensitivities to 1.1-1.2
Too many signals: Raise min_confidence to 0.35-0.40, decrease agent sensitivities to 0.8-0.9
One agent dominates (>70%): Consider "Lock Agent" feature
Signal Interpretation
Dashboard Signal Status:
⚪ WAITING FOR SIGNAL: No agent signaling
⏳ ANALYZING...: Agent signaling but not confirmed
🟡 CONFIRMING 2/3: Building confirmation (2 of 3 bars)
🟢 LONG ACTIVE : Validated long entry
🔴 SHORT ACTIVE : Validated short entry
Kill Zone Boxes: Entry price (triangle marker), Take Profit (Entry + 2.5× ATR), Stop Loss (Entry - 1.5× ATR). Risk:Reward = 1:1.67
Risk Management
Position Sizing:
Risk per trade = 1-2% of capital
Position size = (Capital × Risk%) / (Entry - StopLoss)
Stop-Loss Placement:
Initial: Entry ± 1.5× ATR (shown in kill zone)
Trailing: After 1:1 R:R achieved, move stop to breakeven
Take-Profit Strategy:
TP1 (2.5× ATR): Take 50% off
TP2 (Runner): Trail stop at 1× ATR or use opposite signal as exit
Memory Persistence
Why Save Memory: Every chart reload resets the system. Saving learned parameters preserves weeks of learning.
When To Save: After 200+ signals when agent weights stabilize
What To Save: From Memory Export panel, copy all alpha/beta/weight values and adaptive thresholds
How To Restore: Enable "Restore From Saved State", input all values into corresponding fields
What Makes This Original
Innovation 1: Genuine Multi-Armed Bandit Framework
This implements 15 mathematically rigorous bandit algorithms from academic literature (Thompson Sampling from Chapelle & Li 2011, UCB family from Auer et al. 2002, EXP3 from Auer et al. 2002, KL-UCB from Garivier & Cappé 2011). Each algorithm maintains proper state, updates according to proven theory, and converges to optimal behavior. This is real learning, not superficial parameter changes.
Innovation 2: Full Reinforcement Learning Stack
Beyond bandits learning which agent works best globally, RL learns which agent works best in each market state. After 500+ positions, system builds 54-state × 5-action value function (270 learned parameters) capturing context-dependent agent quality.
Innovation 3: Market Microstructure Integration
Combines retail technical analysis with institutional-grade microstructure metrics: VPIN from Easley, López de Prado, O'Hara (2012), Kyle's Lambda from Kyle (1985), Hawkes Processes from Hawkes (1971). These detect informed trading, manipulation, and liquidity dynamics invisible to technical analysis.
Innovation 4: Adaptive Threshold System
Dynamic quantile-based thresholds: Maintains histogram of each agent's score distribution (24 bins, exponentially decayed), calculates 80th percentile threshold from histogram. Agent triggers only when score exceeds its own learned quantile. Proper non-parametric density estimation automatically adapts to instrument volatility, agent behavior shifts, and market regime changes.
Innovation 5: Episodic Memory with Transfer Learning
Dual-layer architecture: Short-term memory (last 20 trades, fast adaptation) + Long-term memory (condensed episodes, historical patterns). Transfer mechanism consolidates knowledge when STM reaches threshold. Mimics hippocampus → neocortex consolidation in human memory.
Limitations & Disclaimers
General Limitations
No Predictive Guarantee: Pattern recognition ≠ prediction. Past performance ≠ future results.
Learning Period Required: Minimum 50-100 bars for reliable statistics. Initial performance may be suboptimal.
Overfitting Risk: System learns patterns in historical data. May not generalize to unprecedented conditions.
Approximation Limitations: See technical implementation section (10-15% precision loss vs. academic standards)
Single-Instrument Limitation: No multi-asset correlation, sector context, or VIX integration.
Forward-Looking Bias Disclaimer
CRITICAL TRANSPARENCY: The RL system uses an 8-bar forward-looking window for reward calculation.
What This Means: System learns from rewards incorporating future price information (bars 101-108 relative to entry at bar 100).
Why Acceptable:
✅ Signals do NOT look ahead: Entry decisions use only data ≤ entry bar
✅ Learning only: Forward data used for optimization, not signal generation
✅ Real-time mirrors backtest: In live trading, system learns identically
⚠️ Implication: Dashboard "Agent Win%" reflects this 8-bar evaluation. Real-time performance may differ slightly if positions held longer, slippage/fees not captured, or market microstructure changes.
Risk Warnings
No Guarantee of Profit: All trading involves risk of loss
System Failures: Bugs possible despite extensive testing
Market Conditions: Optimized for liquid markets (>100k daily volume). Performance degrades in illiquid instruments, major news events, flash crashes
Broker-Specific Issues: Execution slippage, commission/fees, overnight financing costs
Appropriate Use
This Indicator Is:
✅ Entry trigger system
✅ Risk management framework (stop/target)
✅ Adaptive agent selection engine
✅ Learning system that improves over time
This Indicator Is NOT:
❌ Complete trading strategy (requires position sizing, portfolio management)
❌ Replacement for fundamental analysis
❌ Guaranteed profit generator
❌ Suitable for complete beginners without training
Recommended Complementary Analysis: Market context (support/resistance), volume profile, fundamental catalysts, correlation with related instruments, broader market regime
Recommended Settings by Instrument
Stocks (Large Cap, >$1B):
Mode: Balanced | ML/RL: Enabled, Full Stack | Bandit: Thompson Sampling, Switch
Agent Sensitivity: Spoofing 1.0-1.2, Exhaustion 0.9-1.1, Liquidity 0.8-1.0, StatArb 1.1-1.3
Microstructure: All enabled, VPIN 1.2, Toxicity 1.5 | Timeframe: 15min-1H
Forex Majors (EURUSD, GBPUSD):
Mode: Balanced to Conservative | ML/RL: Enabled, Full Stack | Bandit: Thompson Sampling, Blend
Agent Sensitivity: Spoofing 0.8-1.0, Exhaustion 0.9-1.1, Liquidity 0.7-0.9, StatArb 1.2-1.5
Microstructure: All enabled, VPIN 1.0-1.1, Toxicity 1.3-1.5 | Timeframe: 5min-30min
Crypto (BTC, ETH):
Mode: Aggressive to Balanced | ML/RL: Enabled, Full Stack | Bandit: Thompson Sampling OR EXP3-IX
Agent Sensitivity: Spoofing 1.2-1.5, Exhaustion 1.1-1.3, Liquidity 1.2-1.5, StatArb 0.7-0.9
Microstructure: All enabled, VPIN 1.4-1.6, Toxicity 1.8-2.2 | Timeframe: 15min-4H
Futures (ES, NQ, CL):
Mode: Balanced | ML/RL: Enabled, Full Stack | Bandit: UCB1 or Thompson Sampling
Agent Sensitivity: All 1.0-1.2 (balanced)
Microstructure: All enabled, VPIN 1.1-1.3, Toxicity 1.4-1.6 | Timeframe: 5min-30min
Conclusion
Algorithm Predator - Pro synthesizes academic research from market microstructure theory, reinforcement learning, and multi-armed bandit algorithms. Unlike typical indicator mashups, this system implements 15 mathematically rigorous bandit algorithms, deploys a complete RL stack (Q-Learning, TD(λ), Policy Gradient), integrates institutional microstructure metrics (VPIN, Kyle's Lambda), adapts continuously through dual-layer memory and meta-learning, and provides full transparency on approximations and limitations.
The system is designed for serious algorithmic traders who understand that no indicator is perfect, but through proper machine learning, we can build systems that improve over time and adapt to changing markets without manual intervention.
Use responsibly. Risk disclosure applies. Past performance ≠ future results.
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Hellenic EMA Matrix - PremiumHellenic EMA Matrix - Alpha Omega Premium
Complete User Guide
Table of Contents
Introduction
Indicator Philosophy
Mathematical Constants
EMA Types
Settings
Trading Signals
Visualization
Usage Strategies
FAQ
Introduction
Hellenic EMA Matrix is a premium indicator based on mathematical constants of nature: Phi (Phi - Golden Ratio), Pi (Pi), e (Euler's number). The indicator uses these universal constants to create dynamic EMAs that adapt to the natural rhythms of the market.
Key Features:
6 EMA types based on mathematical constants
Premium visualization with Neon Glow and Gradient Clouds
Automatic Fast/Mid/Slow EMA sorting
STRONG signals for powerful trends
Pulsing Ribbon Bar for instant trend assessment
Works on all timeframes (M1 - MN)
Indicator Philosophy
Why Mathematical Constants?
Traditional EMAs use arbitrary periods (9, 21, 50, 200). Hellenic Matrix goes further, using universal mathematical constants found in nature:
Phi (1.618) - Golden Ratio: galaxy spirals, seashells, human body proportions
Pi (3.14159) - Pi: circles, waves, cycles
e (2.71828) - Natural logarithm base: exponential growth, radioactive decay
Markets are also a natural system composed of millions of participants. Using mathematical constants allows tuning into the natural rhythms of market cycles.
Mathematical Constants
Phi (Phi) - Golden Ratio
Phi = 1.618033988749895
Properties:
Phi² = Phi + 1 = 2.618
Phi³ = 4.236
Phi⁴ = 6.854
Application: Ideal for trending movements and Fibonacci corrections
Pi (Pi) - Pi Number
Pi = 3.141592653589793
Properties:
2Pi = 6.283 (full circle)
3Pi = 9.425
4Pi = 12.566
Application: Excellent for cyclical markets and wave structures
e (Euler) - Euler's Number
e = 2.718281828459045
Properties:
e² = 7.389
e³ = 20.085
e⁴ = 54.598
Application: Suitable for exponential movements and volatile markets
EMA Types
1. Phi (Phi) - Golden Ratio EMA
Description: EMA based on the golden ratio
Period Formula:
Period = Phi^n × Base Multiplier
Parameters:
Phi Power Level (1-8): Power of Phi
Phi¹ = 1.618 → ~16 period (with Base=10)
Phi² = 2.618 → ~26 period
Phi³ = 4.236 → ~42 period (recommended)
Phi⁴ = 6.854 → ~69 period
Recommendations:
Phi² or Phi³ for day trading
Phi⁴ or Phi⁵ for swing trading
Works excellently as Fast EMA
2. Pi (Pi) - Circular EMA
Description: EMA based on Pi for cyclical movements
Period Formula:
Period = Pi × Multiple × Base Multiplier
Parameters:
Pi Multiple (1-10): Pi multiplier
1Pi = 3.14 → ~31 period (with Base=10)
2Pi = 6.28 → ~63 period (recommended)
3Pi = 9.42 → ~94 period
Recommendations:
2Pi ideal as Mid or Slow EMA
Excellently identifies cycles and waves
Use on volatile markets (crypto, forex)
3. e (Euler) - Natural EMA
Description: EMA based on natural logarithm
Period Formula:
Period = e^n × Base Multiplier
Parameters:
e Power Level (1-6): Power of e
e¹ = 2.718 → ~27 period (with Base=10)
e² = 7.389 → ~74 period (recommended)
e³ = 20.085 → ~201 period
Recommendations:
e² works excellently as Slow EMA
Ideal for stocks and indices
Filters noise well on lower timeframes
4. Delta (Delta) - Adaptive EMA
Description: Adaptive EMA that changes period based on volatility
Period Formula:
Period = Base Period × (1 + (Volatility - 1) × Factor)
Parameters:
Delta Base Period (5-200): Base period (default 20)
Delta Volatility Sensitivity (0.5-5.0): Volatility sensitivity (default 2.0)
How it works:
During low volatility → period decreases → EMA reacts faster
During high volatility → period increases → EMA smooths noise
Recommendations:
Works excellently on news and sharp movements
Use as Fast EMA for quick adaptation
Sensitivity 2.0-3.0 for crypto, 1.0-2.0 for stocks
5. Sigma (Sigma) - Composite EMA
Description: Composite EMA combining multiple active EMAs
Composition Methods:
Weighted Average (default):
Sigma = (Phi + Pi + e + Delta) / 4
Simple average of all active EMAs
Geometric Mean:
Sigma = fourth_root(Phi × Pi × e × Delta)
Geometric mean (more conservative)
Harmonic Mean:
Sigma = 4 / (1/Phi + 1/Pi + 1/e + 1/Delta)
Harmonic mean (more weight to smaller values)
Recommendations:
Enable for additional confirmation
Use as Mid EMA
Weighted Average - most universal method
6. Lambda (Lambda) - Wave EMA
Description: Wave EMA with sinusoidal period modulation
Period Formula:
Period = Base Period × (1 + Amplitude × sin(2Pi × bar / Frequency))
Parameters:
Lambda Base Period (10-200): Base period
Lambda Wave Amplitude (0.1-2.0): Wave amplitude
Lambda Wave Frequency (10-200): Wave frequency in bars
How it works:
Period pulsates sinusoidally
Creates wave effect following market cycles
Recommendations:
Experimental EMA for advanced users
Works well on cyclical markets
Frequency = 50 for day trading, 100+ for swing
Settings
Matrix Core Settings
Base Multiplier (1-100)
Multiplies all EMA periods
Base = 1: Very fast EMAs (Phi³ = 4, 2Pi = 6, e² = 7)
Base = 10: Standard (Phi³ = 42, 2Pi = 63, e² = 74)
Base = 20: Slow EMAs (Phi³ = 85, 2Pi = 126, e² = 148)
Recommendations by timeframe:
M1-M5: Base = 5-10
M15-H1: Base = 10-15 (recommended)
H4-D1: Base = 15-25
W1-MN: Base = 25-50
Matrix Source
Data source selection for EMA calculation:
close - closing price (standard)
open - opening price
high - high
low - low
hl2 - (high + low) / 2
hlc3 - (high + low + close) / 3
ohlc4 - (open + high + low + close) / 4
When to change:
hlc3 or ohlc4 for smoother signals
high for aggressive longs
low for aggressive shorts
Manual EMA Selection
Critically important setting! Determines which EMAs are used for signal generation.
Use Manual Fast/Slow/Mid Selection
Enabled (default): You select EMAs manually
Disabled: Automatic selection by periods
Fast EMA
Fast EMA - reacts first to price changes
Recommendations:
Phi Golden (recommended) - universal choice
Delta Adaptive - for volatile markets
Must be fastest (smallest period)
Slow EMA
Slow EMA - determines main trend
Recommendations:
Pi Circular (recommended) - excellent trend filter
e Natural - for smoother trend
Must be slowest (largest period)
Mid EMA
Mid EMA - additional signal filter
Recommendations:
e Natural (recommended) - excellent middle level
Pi Circular - alternative
None - for more frequent signals (only 2 EMAs)
IMPORTANT: The indicator automatically sorts selected EMAs by their actual periods:
Fast = EMA with smallest period
Mid = EMA with middle period
Slow = EMA with largest period
Therefore, you can select any combination - the indicator will arrange them correctly!
Premium Visualization
Neon Glow
Enable Neon Glow for EMAs - adds glowing effect around EMA lines
Glow Strength:
Light - subtle glow
Medium (recommended) - optimal balance
Strong - bright glow (may be too bright)
Effect: 2 glow layers around each EMA for 3D effect
Gradient Clouds
Enable Gradient Clouds - fills space between EMAs with gradient
Parameters:
Cloud Transparency (85-98): Cloud transparency
95-97 (recommended)
Higher = more transparent
Dynamic Cloud Intensity - automatically changes transparency based on EMA distance
Cloud Colors:
Phi-Pi Cloud:
Blue - when Pi above Phi (bullish)
Gold - when Phi above Pi (bearish)
Pi-e Cloud:
Green - when e above Pi (bullish)
Blue - when Pi above e (bearish)
2 layers for volumetric effect
Pulsing Ribbon Bar
Enable Pulsing Indicator Bar - pulsing strip at bottom/top of chart
Parameters:
Ribbon Position: Top / Bottom (recommended)
Pulse Speed: Slow / Medium (recommended) / Fast
Symbols and colors:
Green filled square - STRONG BULLISH
Pink filled square - STRONG BEARISH
Blue hollow square - Bullish (regular)
Red hollow square - Bearish (regular)
Purple rectangle - Neutral
Effect: Pulsation with sinusoid for living market feel
Signal Bar Highlights
Enable Signal Bar Highlights - highlights bars with signals
Parameters:
Highlight Transparency (88-96): Highlight transparency
Highlight Style:
Light Fill (recommended) - bar background fill
Thin Line - bar outline only
Highlights:
Golden Cross - green
Death Cross - pink
STRONG BUY - green
STRONG SELL - pink
Show Greek Labels
Shows Greek alphabet letters on last bar:
Phi - Phi EMA (gold)
Pi - Pi EMA (blue)
e - Euler EMA (green)
Delta - Delta EMA (purple)
Sigma - Sigma EMA (pink)
When to use: For education or presentations
Show Old Background
Old background style (not recommended):
Green background - STRONG BULLISH
Pink background - STRONG BEARISH
Blue background - Bullish
Red background - Bearish
Not recommended - use new Gradient Clouds and Pulsing Bar
Info Table
Show Info Table - table with indicator information
Parameters:
Position: Top Left / Top Right (recommended) / Bottom Left / Bottom Right
Size: Tiny / Small (recommended) / Normal / Large
Table contents:
EMA list - periods and current values of all active EMAs
Effects - active visual effects
TREND - current trend state:
STRONG UP - strong bullish
STRONG DOWN - strong bearish
Bullish - regular bullish
Bearish - regular bearish
Neutral - neutral
Momentum % - percentage deviation of price from Fast EMA
Setup - current Fast/Slow/Mid configuration
Trading Signals
Show Golden/Death Cross
Golden Cross - Fast EMA crosses Slow EMA from below (bullish signal) Death Cross - Fast EMA crosses Slow EMA from above (bearish signal)
Symbols:
Yellow dot "GC" below - Golden Cross
Dark red dot "DC" above - Death Cross
Show STRONG Signals
STRONG BUY and STRONG SELL - the most powerful indicator signals
Conditions for STRONG BULLISH:
EMA Alignment: Fast > Mid > Slow (all EMAs aligned)
Trend: Fast > Slow (clear uptrend)
Distance: EMAs separated by minimum 0.15%
Price Position: Price above Fast EMA
Fast Slope: Fast EMA rising
Slow Slope: Slow EMA rising
Mid Trending: Mid EMA also rising (if enabled)
Conditions for STRONG BEARISH:
Same but in reverse
Visual display:
Green label "STRONG BUY" below bar
Pink label "STRONG SELL" above bar
Difference from Golden/Death Cross:
Golden/Death Cross = crossing moment (1 bar)
STRONG signal = sustained trend (lasts several bars)
IMPORTANT: After fixes, STRONG signals now:
Work on all timeframes (M1 to MN)
Don't break on small retracements
Work with any Fast/Mid/Slow combination
Automatically adapt thanks to EMA sorting
Show Stop Loss/Take Profit
Automatic SL/TP level calculation on STRONG signal
Parameters:
Stop Loss (ATR) (0.5-5.0): ATR multiplier for stop loss
1.5 (recommended) - standard
1.0 - tight stop
2.0-3.0 - wide stop
Take Profit R:R (1.0-5.0): Risk/reward ratio
2.0 (recommended) - standard (risk 1.5 ATR, profit 3.0 ATR)
1.5 - conservative
3.0-5.0 - aggressive
Formulas:
LONG:
Stop Loss = Entry - (ATR × Stop Loss ATR)
Take Profit = Entry + (ATR × Stop Loss ATR × Take Profit R:R)
SHORT:
Stop Loss = Entry + (ATR × Stop Loss ATR)
Take Profit = Entry - (ATR × Stop Loss ATR × Take Profit R:R)
Visualization:
Red X - Stop Loss
Green X - Take Profit
Levels remain active while STRONG signal persists
Trading Signals
Signal Types
1. Golden Cross
Description: Fast EMA crosses Slow EMA from below
Signal: Beginning of bullish trend
How to trade:
ENTRY: On bar close with Golden Cross
STOP: Below local low or below Slow EMA
TARGET: Next resistance level or 2:1 R:R
Strengths:
Simple and clear
Works well on trending markets
Clear entry point
Weaknesses:
Lags (signal after movement starts)
Many false signals in ranging markets
May be late on fast moves
Optimal timeframes: H1, H4, D1
2. Death Cross
Description: Fast EMA crosses Slow EMA from above
Signal: Beginning of bearish trend
How to trade:
ENTRY: On bar close with Death Cross
STOP: Above local high or above Slow EMA
TARGET: Next support level or 2:1 R:R
Application: Mirror of Golden Cross
3. STRONG BUY
Description: All EMAs aligned + trend + all EMAs rising
Signal: Powerful bullish trend
How to trade:
ENTRY: On bar close with STRONG BUY or on pullback to Fast EMA
STOP: Below Fast EMA or automatic SL (if enabled)
TARGET: Automatic TP (if enabled) or by levels
TRAILING: Follow Fast EMA
Entry strategies:
Aggressive: Enter immediately on signal
Conservative: Wait for pullback to Fast EMA, then enter on bounce
Pyramiding: Add positions on pullbacks to Mid EMA
Position management:
Hold while STRONG signal active
Exit on STRONG SELL or Death Cross appearance
Move stop behind Fast EMA
Strengths:
Most reliable indicator signal
Doesn't break on pullbacks
Catches large moves
Works on all timeframes
Weaknesses:
Appears less frequently than other signals
Requires confirmation (multiple conditions)
Optimal timeframes: All (M5 - D1)
4. STRONG SELL
Description: All EMAs aligned down + downtrend + all EMAs falling
Signal: Powerful bearish trend
How to trade: Mirror of STRONG BUY
Visual Signals
Pulsing Ribbon Bar
Quick market assessment at a glance:
Symbol Color State
Filled square Green STRONG BULLISH
Filled square Pink STRONG BEARISH
Hollow square Blue Bullish
Hollow square Red Bearish
Rectangle Purple Neutral
Pulsation: Sinusoidal, creates living effect
Signal Bar Highlights
Bars with signals are highlighted:
Green highlight: STRONG BUY or Golden Cross
Pink highlight: STRONG SELL or Death Cross
Gradient Clouds
Colored space between EMAs shows trend strength:
Wide clouds - strong trend
Narrow clouds - weak trend or consolidation
Color change - trend change
Info Table
Quick reference in corner:
TREND: Current state (STRONG UP, Bullish, Neutral, Bearish, STRONG DOWN)
Momentum %: Movement strength
Effects: Active visual effects
Setup: Fast/Slow/Mid configuration
Usage Strategies
Strategy 1: "Golden Trailing"
Idea: Follow STRONG signals using Fast EMA as trailing stop
Settings:
Fast: Phi Golden (Phi³)
Mid: Pi Circular (2Pi)
Slow: e Natural (e²)
Base Multiplier: 10
Timeframe: H1, H4
Entry rules:
Wait for STRONG BUY
Enter on bar close or on pullback to Fast EMA
Stop below Fast EMA
Management:
Hold position while STRONG signal active
Move stop behind Fast EMA daily
Exit on STRONG SELL or Death Cross
Take Profit:
Partially close at +2R
Trail remainder until exit signal
For whom: Swing traders, trend followers
Pros:
Catches large moves
Simple rules
Emotionally comfortable
Cons:
Requires patience
Possible extended drawdowns on pullbacks
Strategy 2: "Scalping Bounces"
Idea: Scalp bounces from Fast EMA during STRONG trend
Settings:
Fast: Delta Adaptive (Base 15, Sensitivity 2.0)
Mid: Phi Golden (Phi²)
Slow: Pi Circular (2Pi)
Base Multiplier: 5
Timeframe: M5, M15
Entry rules:
STRONG signal must be active
Wait for price pullback to Fast EMA
Enter on bounce (candle closes above/below Fast EMA)
Stop behind local extreme (15-20 pips)
Take Profit:
+1.5R or to Mid EMA
Or to next level
For whom: Active day traders
Pros:
Many signals
Clear entry point
Quick profits
Cons:
Requires constant monitoring
Not all bounces work
Requires discipline for frequent trading
Strategy 3: "Triple Filter"
Idea: Enter only when all 3 EMAs and price perfectly aligned
Settings:
Fast: Phi Golden (Phi³)
Mid: e Natural (e²)
Slow: Pi Circular (3Pi)
Base Multiplier: 15
Timeframe: H4, D1
Entry rules (LONG):
STRONG BUY active
Price above all three EMAs
Fast > Mid > Slow (all aligned)
All EMAs rising (slope up)
Gradient Clouds wide and bright
Entry:
On bar close meeting all conditions
Or on next pullback to Fast EMA
Stop:
Below Mid EMA or -1.5 ATR
Take Profit:
First target: +3R
Second target: next major level
Trailing: Mid EMA
For whom: Conservative swing traders, investors
Pros:
Very reliable signals
Minimum false entries
Large profit potential
Cons:
Rare signals (2-5 per month)
Requires patience
Strategy 4: "Adaptive Scalper"
Idea: Use only Delta Adaptive EMA for quick volatility reaction
Settings:
Fast: Delta Adaptive (Base 10, Sensitivity 3.0)
Mid: None
Slow: Delta Adaptive (Base 30, Sensitivity 2.0)
Base Multiplier: 3
Timeframe: M1, M5
Feature: Two different Delta EMAs with different settings
Entry rules:
Golden Cross between two Delta EMAs
Both Delta EMAs must be rising/falling
Enter on next bar
Stop:
10-15 pips or below Slow Delta EMA
Take Profit:
+1R to +2R
Or Death Cross
For whom: Scalpers on cryptocurrencies and forex
Pros:
Instant volatility adaptation
Many signals on volatile markets
Quick results
Cons:
Much noise on calm markets
Requires fast execution
High commissions may eat profits
Strategy 5: "Cyclical Trader"
Idea: Use Pi and Lambda for trading cyclical markets
Settings:
Fast: Pi Circular (1Pi)
Mid: Lambda Wave (Base 30, Amplitude 0.5, Frequency 50)
Slow: Pi Circular (3Pi)
Base Multiplier: 10
Timeframe: H1, H4
Entry rules:
STRONG signal active
Lambda Wave EMA synchronized with trend
Enter on bounce from Lambda Wave
For whom: Traders of cyclical assets (some altcoins, commodities)
Pros:
Catches cyclical movements
Lambda Wave provides additional entry points
Cons:
More complex to configure
Not for all markets
Lambda Wave may give false signals
Strategy 6: "Multi-Timeframe Confirmation"
Idea: Use multiple timeframes for confirmation
Scheme:
Higher TF (D1): Determine trend direction (STRONG signal)
Middle TF (H4): Wait for STRONG signal in same direction
Lower TF (M15): Look for entry point (Golden Cross or bounce from Fast EMA)
Settings for all TFs:
Fast: Phi Golden (Phi³)
Mid: e Natural (e²)
Slow: Pi Circular (2Pi)
Base Multiplier: 10
Rules:
All 3 TFs must show one trend
Entry on lower TF
Stop by lower TF
Target by higher TF
For whom: Serious traders and investors
Pros:
Maximum reliability
Large profit targets
Minimum false signals
Cons:
Rare setups
Requires analysis of multiple charts
Experience needed
Practical Tips
DOs
Use STRONG signals as primary - they're most reliable
Let signals develop - don't exit on first pullback
Use trailing stop - follow Fast EMA
Combine with levels - S/R, Fibonacci, volumes
Test on demo before real
Adjust Base Multiplier for your timeframe
Enable visual effects - they help see the picture
Use Info Table - quick situation assessment
Watch Pulsing Bar - instant state indicator
Trust auto-sorting of Fast/Mid/Slow
DON'Ts
Don't trade against STRONG signal - trend is your friend
Don't ignore Mid EMA - it adds reliability
Don't use too small Base Multiplier on higher TFs
Don't enter on Golden Cross in range - check for trend
Don't change settings during open position
Don't forget risk management - 1-2% per trade
Don't trade all signals in row - choose best ones
Don't use indicator in isolation - combine with Price Action
Don't set too tight stops - let trade breathe
Don't over-optimize - simplicity = reliability
Optimal Settings by Asset
US Stocks (SPY, AAPL, TSLA)
Recommendation:
Fast: Phi Golden (Phi³)
Mid: e Natural (e²)
Slow: Pi Circular (2Pi)
Base: 10-15
Timeframe: H4, D1
Features:
Use on daily for swing
STRONG signals very reliable
Works well on trending stocks
Forex (EUR/USD, GBP/USD)
Recommendation:
Fast: Delta Adaptive (Base 15, Sens 2.0)
Mid: Phi Golden (Phi²)
Slow: Pi Circular (2Pi)
Base: 8-12
Timeframe: M15, H1, H4
Features:
Delta Adaptive works excellently on news
Many signals on M15-H1
Consider spreads
Cryptocurrencies (BTC, ETH, altcoins)
Recommendation:
Fast: Delta Adaptive (Base 10, Sens 3.0)
Mid: Pi Circular (2Pi)
Slow: e Natural (e²)
Base: 5-10
Timeframe: M5, M15, H1
Features:
High volatility - adaptation needed
STRONG signals can last days
Be careful with scalping on M1-M5
Commodities (Gold, Oil)
Recommendation:
Fast: Pi Circular (1Pi)
Mid: Phi Golden (Phi³)
Slow: Pi Circular (3Pi)
Base: 12-18
Timeframe: H4, D1
Features:
Pi works excellently on cyclical commodities
Gold responds especially well to Phi
Oil volatile - use wide stops
Indices (S&P500, Nasdaq, DAX)
Recommendation:
Fast: Phi Golden (Phi³)
Mid: e Natural (e²)
Slow: Pi Circular (2Pi)
Base: 15-20
Timeframe: H4, D1, W1
Features:
Very trending instruments
STRONG signals last weeks
Good for position trading
Alerts
The indicator supports 6 alert types:
1. Golden Cross
Message: "Hellenic Matrix: GOLDEN CROSS - Fast EMA crossed above Slow EMA - Bullish trend starting!"
When: Fast EMA crosses Slow EMA from below
2. Death Cross
Message: "Hellenic Matrix: DEATH CROSS - Fast EMA crossed below Slow EMA - Bearish trend starting!"
When: Fast EMA crosses Slow EMA from above
3. STRONG BULLISH
Message: "Hellenic Matrix: STRONG BULLISH SIGNAL - All EMAs aligned for powerful uptrend!"
When: All conditions for STRONG BUY met (first bar)
4. STRONG BEARISH
Message: "Hellenic Matrix: STRONG BEARISH SIGNAL - All EMAs aligned for powerful downtrend!"
When: All conditions for STRONG SELL met (first bar)
5. Bullish Ribbon
Message: "Hellenic Matrix: BULLISH RIBBON - EMAs aligned for uptrend"
When: EMAs aligned bullish + price above Fast EMA (less strict condition)
6. Bearish Ribbon
Message: "Hellenic Matrix: BEARISH RIBBON - EMAs aligned for downtrend"
When: EMAs aligned bearish + price below Fast EMA (less strict condition)
How to Set Up Alerts:
Open indicator on chart
Click on three dots next to indicator name
Select "Create Alert"
In "Condition" field select needed alert:
Golden Cross
Death Cross
STRONG BULLISH
STRONG BEARISH
Bullish Ribbon
Bearish Ribbon
Configure notification method:
Pop-up in browser
Email
SMS (in Premium accounts)
Push notifications in mobile app
Webhook (for automation)
Select frequency:
Once Per Bar Close (recommended) - once on bar close
Once Per Bar - during bar formation
Only Once - only first time
Click "Create"
Tip: Create separate alerts for different timeframes and instruments
FAQ
1. Why don't STRONG signals appear?
Possible reasons:
Incorrect Fast/Mid/Slow order
Solution: Indicator automatically sorts EMAs by periods, but ensure selected EMAs have different periods
Base Multiplier too large
Solution: Reduce Base to 5-10 on lower timeframes
Market in range
Solution: STRONG signals appear only in trends - this is normal
Too strict EMA settings
Solution: Try classic combination: Phi³ / Pi×2 / e² with Base=10
Mid EMA too close to Fast or Slow
Solution: Select Mid EMA with period between Fast and Slow
2. How often should STRONG signals appear?
Normal frequency:
M1-M5: 5-15 signals per day (very active markets)
M15-H1: 2-8 signals per day
H4: 3-10 signals per week
D1: 2-5 signals per month
W1: 2-6 signals per year
If too many signals - market very volatile or Base too small
If too few signals - market in range or Base too large
4. What are the best settings for beginners?
Universal "out of the box" settings:
Matrix Core:
Base Multiplier: 10
Source: close
Phi Golden: Enabled, Power = 3
Pi Circular: Enabled, Multiple = 2
e Natural: Enabled, Power = 2
Delta Adaptive: Enabled, Base = 20, Sensitivity = 2.0
Manual Selection:
Fast: Phi Golden
Mid: e Natural
Slow: Pi Circular
Visualization:
Gradient Clouds: ON
Neon Glow: ON (Medium)
Pulsing Bar: ON (Medium)
Signal Highlights: ON (Light Fill)
Table: ON (Top Right, Small)
Signals:
Golden/Death Cross: ON
STRONG Signals: ON
Stop Loss: OFF (while learning)
Timeframe for learning: H1 or H4
5. Can I use only one EMA?
No, minimum 2 EMAs (Fast and Slow) for signal generation.
Mid EMA is optional:
With Mid EMA = more reliable but rarer signals
Without Mid EMA = more signals but less strict filtering
Recommendation: Start with 3 EMAs (Fast/Mid/Slow), then experiment
6. Does the indicator work on cryptocurrencies?
Yes, works excellently! Especially good on:
Bitcoin (BTC)
Ethereum (ETH)
Major altcoins (SOL, BNB, XRP)
Recommended settings for crypto:
Fast: Delta Adaptive (Base 10-15, Sensitivity 2.5-3.0)
Mid: Pi Circular (2Pi)
Slow: e Natural (e²)
Base: 5-10
Timeframe: M15, H1, H4
Crypto market features:
High volatility → use Delta Adaptive
24/7 trading → set alerts
Sharp movements → wide stops
7. Can I trade only with this indicator?
Technically yes, but NOT recommended.
Best approach - combine with:
Price Action - support/resistance levels, candle patterns
Volume - movement strength confirmation
Fibonacci - retracement and extension levels
RSI/MACD - divergences and overbought/oversold
Fundamental analysis - news, company reports
Hellenic Matrix:
Excellently determines trend and its strength
Provides clear entry/exit points
Doesn't consider fundamentals
Doesn't see major levels
8. Why do Gradient Clouds change color?
Color depends on EMA order:
Phi-Pi Cloud:
Blue - Pi EMA above Phi EMA (bullish alignment)
Gold - Phi EMA above Pi EMA (bearish alignment)
Pi-e Cloud:
Green - e EMA above Pi EMA (bullish alignment)
Blue - Pi EMA above e EMA (bearish alignment)
Color change = EMA order change = possible trend change
9. What is Momentum % in the table?
Momentum % = percentage deviation of price from Fast EMA
Formula:
Momentum = ((Close - Fast EMA) / Fast EMA) × 100
Interpretation:
+0.5% to +2% - normal bullish momentum
+2% to +5% - strong bullish momentum
+5% and above - overheating (correction possible)
-0.5% to -2% - normal bearish momentum
-2% to -5% - strong bearish momentum
-5% and below - oversold (bounce possible)
Usage:
Monitor momentum during STRONG signals
Large momentum = don't enter (wait for pullback)
Small momentum = good entry point
10. How to configure for scalping?
Settings for scalping (M1-M5):
Base Multiplier: 3-5
Source: close or hlc3 (smoother)
Fast: Delta Adaptive (Base 8-12, Sensitivity 3.0)
Mid: None (for more signals)
Slow: Phi Golden (Phi²) or Pi Circular (1Pi)
Visualization:
- Gradient Clouds: ON (helps see strength)
- Neon Glow: OFF (doesn't clutter chart)
- Pulsing Bar: ON (quick assessment)
- Signal Highlights: ON
Signals:
- Golden/Death Cross: ON
- STRONG Signals: ON
- Stop Loss: ON (1.0-1.5 ATR, R:R 1.5-2.0)
Scalping rules:
Trade only STRONG signals
Enter on bounce from Fast EMA
Tight stops (10-20 pips)
Quick take profit (+1R to +2R)
Don't hold through news
11. How to configure for long-term investing?
Settings for investing (D1-W1):
Base Multiplier: 20-30
Source: close
Fast: Phi Golden (Phi³ or Phi⁴)
Mid: e Natural (e²)
Slow: Pi Circular (3Pi or 4Pi)
Visualization:
- Gradient Clouds: ON
- Neon Glow: ON (Medium)
- Everything else - to taste
Signals:
- Golden/Death Cross: ON
- STRONG Signals: ON
- Stop Loss: OFF (use percentage stop)
Investing rules:
Enter only on STRONG signals
Hold while STRONG active (weeks/months)
Stop below Slow EMA or -10%
Take profit: by company targets or +50-100%
Ignore short-term pullbacks
12. What if indicator slows down chart?
Indicator is optimized, but if it slows:
Disable unnecessary visual effects:
Neon Glow: OFF (saves 8 plots)
Gradient Clouds: ON but low quality
Lambda Wave EMA: OFF (if not using)
Reduce number of active EMAs:
Sigma Composite: OFF
Lambda Wave: OFF
Leave only Phi, Pi, e, Delta
Simplify settings:
Pulsing Bar: OFF
Greek Labels: OFF
Info Table: smaller size
13. Can I use on different timeframes simultaneously?
Yes! Multi-timeframe analysis is very powerful:
Classic scheme:
Higher TF (D1, W1) - determine global trend
Wait for STRONG signal
This is our trading direction
Middle TF (H4, H1) - look for confirmation
STRONG signal in same direction
Precise entry zone
Lower TF (M15, M5) - entry point
Golden Cross or bounce from Fast EMA
Precise stop loss
Example:
W1: STRONG BUY active (global uptrend)
H4: STRONG BUY appeared (confirmation)
M15: Wait for Golden Cross or bounce from Fast EMA → ENTRY
Advantages:
Maximum reliability
Clear timeframe hierarchy
Large targets
14. How does indicator work on news?
Delta Adaptive EMA adapts excellently to news:
Before news:
Low volatility → Delta EMA becomes fast → pulls to price
During news:
Sharp volatility spike → Delta EMA slows → filters noise
After news:
Volatility normalizes → Delta EMA returns to normal
Recommendations:
Don't trade at news release moment (spreads widen)
Wait for STRONG signal after news (2-5 bars)
Use Delta Adaptive as Fast EMA for quick reaction
Widen stops by 50-100% during important news
Advanced Techniques
Technique 1: "Divergences with EMA"
Idea: Look for discrepancies between price and Fast EMA
Bullish divergence:
Price makes lower low
Fast EMA makes higher low
= Possible reversal up
Bearish divergence:
Price makes higher high
Fast EMA makes lower high
= Possible reversal down
How to trade:
Find divergence
Wait for STRONG signal in divergence direction
Enter on confirmation
Technique 2: "EMA Tunnel"
Idea: Use space between Fast and Slow EMA as "tunnel"
Rules:
Wide tunnel - strong trend, hold position
Narrow tunnel - weak trend or consolidation, caution
Tunnel narrowing - trend weakening, prepare to exit
Tunnel widening - trend strengthening, can add
Visually: Gradient Clouds show this automatically!
Trading:
Enter on STRONG signal (tunnel starts widening)
Hold while tunnel wide
Exit when tunnel starts narrowing
Technique 3: "Wave Analysis with Lambda"
Idea: Lambda Wave EMA creates sinusoid matching market cycles
Setup:
Lambda Base Period: 30
Lambda Wave Amplitude: 0.5
Lambda Wave Frequency: 50 (adjusted to asset cycle)
How to find correct Frequency:
Look at historical cycles (distance between local highs)
Average distance = your Frequency
Example: if highs every 40-60 bars, set Frequency = 50
Trading:
Enter when Lambda Wave at bottom of sinusoid (growth potential)
Exit when Lambda Wave at top (fall potential)
Combine with STRONG signals
Technique 4: "Cluster Analysis"
Idea: When all EMAs gather in narrow cluster = powerful breakout soon
Cluster signs:
All EMAs (Phi, Pi, e, Delta) within 0.5-1% of each other
Gradient Clouds almost invisible
Price jumping around all EMAs
Trading:
Identify cluster (all EMAs close)
Determine breakout direction (where more volume, higher TFs direction)
Wait for breakout and STRONG signal
Enter on confirmation
Target = cluster size × 3-5
This is very powerful technique for big moves!
Technique 5: "Sigma as Dynamic Level"
Idea: Sigma Composite EMA = average of all EMAs = magnetic level
Usage:
Enable Sigma Composite (Weighted Average)
Sigma works as dynamic support/resistance
Price often returns to Sigma before trend continuation
Trading:
In trend: Enter on bounces from Sigma
In range: Fade moves from Sigma (trade return to Sigma)
On breakout: Sigma becomes support/resistance
Risk Management
Basic Rules
1. Position Size
Conservative: 1% of capital per trade
Moderate: 2% of capital per trade (recommended)
Aggressive: 3-5% (only for experienced)
Calculation formula:
Lot Size = (Capital × Risk%) / (Stop in pips × Pip value)
2. Risk/Reward Ratio
Minimum: 1:1.5
Standard: 1:2 (recommended)
Optimal: 1:3
Aggressive: 1:5+
3. Maximum Drawdown
Daily: -3% to -5%
Weekly: -7% to -10%
Monthly: -15% to -20%
Upon reaching limit → STOP trading until end of period
Position Management Strategies
1. Fixed Stop
Method:
Stop below/above Fast EMA or local extreme
DON'T move stop against position
Can move to breakeven
For whom: Beginners, conservative traders
2. Trailing by Fast EMA
Method:
Each day (or bar) move stop to Fast EMA level
Position closes when price breaks Fast EMA
Advantages:
Stay in trend as long as possible
Automatically exit on reversal
For whom: Trend followers, swing traders
3. Partial Exit
Method:
50% of position close at +2R
50% hold with trailing by Mid EMA or Slow EMA
Advantages:
Lock profit
Leave position for big move
Psychologically comfortable
For whom: Universal method (recommended)
4. Pyramiding
Method:
First entry on STRONG signal (50% of planned position)
Add 25% on pullback to Fast EMA
Add another 25% on pullback to Mid EMA
Overall stop below Slow EMA
Advantages:
Average entry price
Reduce risk
Increase profit in strong trends
Caution:
Works only in trends
In range leads to losses
For whom: Experienced traders
Trading Psychology
Correct Mindset
1. Indicator is a tool, not holy grail
Indicator shows probability, not guarantee
There will be losing trades - this is normal
Important is series statistics, not one trade
2. Trust the system
If STRONG signal appeared - enter
Don't search for "perfect" moment
Follow trading plan
3. Patience
STRONG signals don't appear every day
Better miss signal than enter against trend
Quality over quantity
4. Discipline
Always set stop loss
Don't move stop against position
Don't increase risk after losses
Beginner Mistakes
1. "I know better than indicator"
Indicator says STRONG BUY, but you think "too high, will wait for pullback"
Result: miss profitable move
Solution: Trust signals or don't use indicator
2. "Will reverse now for sure"
Trading against STRONG trend
Result: stops, stops, stops
Solution: Trend is your friend, trade with trend
3. "Will hold a bit more"
Don't exit when STRONG signal disappears
Greed eats profit
Solution: If signal gone - exit!
4. "I'll recover"
After losses double risk
Result: huge losses
Solution: Fixed % risk ALWAYS
5. "I don't like this signal"
Skip signals because of "feeling"
Result: inconsistency, no statistics
Solution: Trade ALL signals or clearly define filters
Trading Journal
What to Record
For each trade:
1. Entry/exit date and time
2. Instrument and timeframe
3. Signal type
Golden Cross
STRONG BUY
STRONG SELL
Death Cross
4. Indicator settings
Fast/Mid/Slow EMA
Base Multiplier
Other parameters
5. Chart screenshot
Entry moment
Exit moment
6. Trade parameters
Position size
Stop loss
Take Profit
R:R
7. Result
Profit/Loss in $
Profit/Loss in %
Profit/Loss in R
8. Notes
What was right
What was wrong
Emotions during trade
Lessons
Journal Analysis
Analyze weekly:
1. Win Rate
Win Rate = (Profitable trades / All trades) × 100%
Good: 50-60%
Excellent: 60-70%
Exceptional: 70%+
2. Average R
Average R = Sum of all R / Number of trades
Good: +0.5R
Excellent: +1.0R
Exceptional: +1.5R+
3. Profit Factor
Profit Factor = Total profit / Total losses
Good: 1.5+
Excellent: 2.0+
Exceptional: 3.0+
4. Maximum Drawdown
Track consecutive losses
If more than 5 in row - stop, check system
5. Best/Worst Trades
What was common in best trades? (do more)
What was common in worst trades? (avoid)
Pre-Trade Checklist
Technical Analysis
STRONG signal active (BUY or SELL)
All EMAs properly aligned (Fast > Mid > Slow or reverse)
Price on correct side of Fast EMA
Gradient Clouds confirm trend
Pulsing Bar shows STRONG state
Momentum % in normal range (not overheated)
No close strong levels against direction
Higher timeframe doesn't contradict
Risk Management
Position size calculated (1-2% risk)
Stop loss set
Take profit calculated (minimum 1:2)
R:R satisfactory
Daily/weekly risk limit not exceeded
No other open correlated positions
Fundamental Analysis
No important news in coming hours
Market session appropriate (liquidity)
No contradicting fundamentals
Understand why asset is moving
Psychology
Calm and thinking clearly
No emotions from previous trades
Ready to accept loss at stop
Following trading plan
Not revenging market for past losses
If at least one point is NO - think twice before entering!
Learning Roadmap
Week 1: Familiarization
Goals:
Install and configure indicator
Study all EMA types
Understand visualization
Tasks:
Add indicator to chart
Test all Fast/Mid/Slow settings
Play with Base Multiplier on different timeframes
Observe Gradient Clouds and Pulsing Bar
Study Info Table
Result: Comfort with indicator interface
Week 2: Signals
Goals:
Learn to recognize all signal types
Understand difference between Golden Cross and STRONG
Tasks:
Find 10 Golden Cross examples in history
Find 10 STRONG BUY examples in history
Compare their results (which worked better)
Set up alerts
Get 5 real alerts
Result: Understanding signals
Week 3: Demo Trading
Goals:
Start trading signals on demo account
Gather statistics
Tasks:
Open demo account
Trade ONLY STRONG signals
Keep journal (minimum 20 trades)
Don't change indicator settings
Strictly follow stop losses
Result: 20+ documented trades
Week 4: Analysis
Goals:
Analyze demo trading results
Optimize approach
Tasks:
Calculate win rate and average R
Find patterns in profitable trades
Find patterns in losing trades
Adjust approach (not indicator!)
Write trading plan
Result: Trading plan on 1 page
Month 2: Improvement
Goals:
Deepen understanding
Add additional techniques
Tasks:
Study multi-timeframe analysis
Test combinations with Price Action
Try advanced techniques (divergences, tunnels)
Continue demo trading (minimum 50 trades)
Achieve stable profitability on demo
Result: Win rate 55%+ and Profit Factor 1.5+
Month 3: Real Trading
Goals:
Transition to real account
Maintain discipline
Tasks:
Open small real account
Trade minimum lots
Strictly follow trading plan
DON'T increase risk
Focus on process, not profit
Result: Psychological comfort on real
Month 4+: Scaling
Goals:
Increase account
Become consistently profitable
Tasks:
With 60%+ win rate can increase risk to 2%
Upon doubling account can add capital
Continue keeping journal
Periodically review and improve strategy
Share experience with community
Result: Stable profitability month after month
Additional Resources
Recommended Reading
Technical Analysis:
"Technical Analysis of Financial Markets" - John Murphy
"Trading in the Zone" - Mark Douglas (psychology)
"Market Wizards" - Jack Schwager (trader interviews)
EMA and Moving Averages:
"Moving Averages 101" - Steve Burns
Articles on Investopedia about EMA
Risk Management:
"The Mathematics of Money Management" - Ralph Vince
"Trade Your Way to Financial Freedom" - Van K. Tharp
Trading Journals:
Edgewonk (paid, very powerful)
Tradervue (free version + premium)
Excel/Google Sheets (free)
Screeners:
TradingView Stock Screener
Finviz (stocks)
CoinMarketCap (crypto)
Conclusion
Hellenic EMA Matrix is a powerful tool based on universal mathematical constants of nature. The indicator combines:
Mathematical elegance - Phi, Pi, e instead of arbitrary numbers
Premium visualization - Neon Glow, Gradient Clouds, Pulsing Bar
Reliable signals - STRONG BUY/SELL work on all timeframes
Flexibility - 6 EMA types, adaptation to any trading style
Automation - auto-sorting EMAs, SL/TP calculation, alerts
Key Success Principles:
Simplicity - start with basic settings (Phi/Pi/e, Base=10)
Discipline - follow STRONG signals strictly
Patience - wait for quality setups
Risk Management - 1-2% per trade, ALWAYS
Journal - document every trade
Learning - constantly improve skills
Remember:
Indicator shows probability, not guarantee
Important is series statistics, not one trade
Psychology more important than technique
Quality more important than quantity
Process more important than result
Acknowledgments
Thank you for using Hellenic EMA Matrix - Alpha Omega Premium!
The indicator was created with love for mathematics, markets, and beautiful visualization.
Wishing you profitable trading!
Guide Version: 1.0
Date: 2025
Compatibility: Pine Script v6, TradingView
"In the simplicity of mathematical constants lies the complexity of market movements"
True Opens & Key Levels# True Opens & Key Levels - Standalone Indicator Guide
## Overview
This is a clean, focused indicator that displays only key level rays and true open levels. All impulsive series detection, FVG detection, and Fibonacci projections have been removed for a minimal, uncluttered chart experience.
---
## Features Included
### 📊 Previous Period Levels
- **Previous Day High/Low** - Daily reference points
- **Previous Week High/Low** - Weekly reference points
- **Previous Month High/Low** - Monthly reference points
### 🕐 Session High/Low Levels
- **NY AM Session** (9:30-12:00 ET) - Morning session range
- **NY Lunch Session** (12:00-13:30 ET) - Lunch hour range
- **NY PM Session** (13:30-16:00 ET) - Afternoon session range
- **London Session** (2:00-5:00 ET) - London trading hours
- **Asia Session** (20:00-00:00 ET) - Asian market hours
### 🎯 True Open Levels (NEW)
- **True Day Open** - Updates daily at 00:00 ET
- **True Session Open** - Updates every 6 hours (1:30, 7:30, 13:30, 19:30 ET)
- **True Week Open** - Updates every Monday at 18:00 ET
---
## Settings
### Key Level Rays Group
**Master Toggle:**
- Enable Key Level Rays (master on/off switch)
**Previous Period Levels:**
- Show Previous Day H/L
- Show Previous Week H/L
- Show Previous Month H/L
**Session Levels:**
- Show NY AM H/L (9:30-12:00 ET)
- Show NY Lunch H/L (12:00-13:30 ET)
- Show NY PM H/L (13:30-16:00 ET)
- Show London H/L (2:00-5:00 ET)
- Show Asia H/L (20:00-00:00 ET)
**True Open Levels:**
- Show True Day Open (00:00)
- Show True Session Open (6h intervals)
- Show True Week Open (Mon 18:00)
**Visual Settings:**
- High Level Color (default: red with 50% transparency)
- Low Level Color (default: green with 50% transparency)
- Open Level Color (default: blue with 50% transparency)
- Ray Line Width (1-5 pixels)
- Ray Label Size (tiny/small/normal/large)
---
## How It Works
### Level Behavior
**Session High/Low Levels:**
1. During session: Tracks the highest high and lowest low
2. After session ends: Draws horizontal rays extending right
3. When price hits level: Ray stops extending (hit marker)
4. Label updates position to stay at chart's right edge
**Previous Period Levels:**
1. At period change: Draws rays from previous period's H/L
2. Extends right until price hits the level
3. When hit: Ray stops extending
4. Label positions at midpoint of ray
**True Open Levels:**
1. At trigger time: Draws ray from opening price
2. Extends right until next trigger
3. Previous level is deleted when new one appears
4. Label stays at right edge of chart
---
## Color Scheme
### Three Color Categories:
1. **Red** - All HIGH levels (session highs, previous highs)
2. **Green** - All LOW levels (session lows, previous lows)
3. **Blue** - All OPEN levels (True Day/Session/Week Opens)
This makes it instantly clear what type of level you're looking at.
---
## Best Practices
### For Intraday Trading (1m-1H):
```
Enable:
✓ True Day Open
✓ True Session Open
✓ NY AM/PM H/L
✓ Previous Day H/L
Disable:
✗ Previous Week/Month H/L
✗ London/Asia sessions (unless trading them)
✗ True Week Open
```
### For Swing Trading (1H-4H):
```
Enable:
✓ True Week Open
✓ True Day Open
✓ Previous Week H/L
✓ Previous Day H/L
Disable:
✗ All session H/L
✗ True Session Open
✗ Previous Month H/L
```
### For Clean Charts:
```
Enable:
✓ True Day Open
✓ True Week Open
✓ Previous Day H/L only
Disable:
✗ Everything else
Result: Just 4 levels on chart - super clean!
```
---
## Level Update Schedule
| Level | Update Frequency | Time(s) |
|---------------------|------------------|-----------------------------|
| True Day Open | Daily | 00:00 ET |
| True Session Open | Every 6 hours | 1:30, 7:30, 13:30, 19:30 ET |
| True Week Open | Weekly | Monday 18:00 ET |
| Previous Day H/L | Daily | At day change |
| Previous Week H/L | Weekly | At week change |
| Previous Month H/L | Monthly | At month change |
| NY AM H/L | Daily | After 12:00 ET |
| NY Lunch H/L | Daily | After 13:30 ET |
| NY PM H/L | Daily | After 16:00 ET |
| London H/L | Daily | After 5:00 ET |
| Asia H/L | Daily | After 00:00 ET |
---
## File Size & Performance
- **File Size:** ~22 KB (less than half the size of full indicator)
- **Total Lines:** ~700 lines
- **Max Lines/Labels:** 500 (configurable in declaration)
- **Performance:** Lightweight, minimal CPU usage
- **Memory:** Efficient variable management
---
## Installation
1. Open TradingView
2. Open Pine Editor (Alt+E or bottom toolbar)
3. Click "Create new indicator"
4. Delete default code
5. Copy and paste contents of `TRUE_OPENS_KEY_LEVELS.pine`
6. Click "Save" and name it "True Opens & Key Levels"
7. Click "Add to Chart"
---
## Usage Tips
### 1. Start Minimal
Begin with just 2-3 levels enabled:
- True Day Open
- Previous Day High
- Previous Day Low
Add more as needed.
### 2. Color Customization
Adjust transparency for cleaner look:
- High Level: Red 60-70% transparency
- Low Level: Green 60-70% transparency
- Open Level: Blue 60-70% transparency
### 3. Multi-Timeframe Approach
Lower timeframes (1m-15m): Use True Session Open + NY session H/L
Mid timeframes (15m-1H): Use True Day Open + Previous Day H/L
Higher timeframes (1H-4H): Use True Week Open + Previous Week H/L
### 4. Line Width
For cleaner charts, use Line Width = 1
For emphasis, use Line Width = 2-3
### 5. Label Size
Smaller screens: Use "small" or "tiny"
Larger screens: Use "normal"
Presentations: Use "large"
---
## Advantages of Standalone Version
✅ **Cleaner Charts** - No detection lines or arrows
✅ **Faster Loading** - Less code to process
✅ **Easier Setup** - Fewer settings to configure
✅ **Pure Levels** - Focus only on key price levels
✅ **Less Distraction** - No moving parts during trading
✅ **Perfect for Combining** - Use with other indicators without clutter
---
## Combining with Other Indicators
This lightweight indicator works great alongside:
- RSI / Stochastic (oscillators)
- Moving Averages (trend)
- Volume Profile (structure)
- VWAP (intraday reference)
- Your own custom indicators
The minimal chart footprint leaves room for additional tools.
---
## Time Zones
All times are in **Eastern Time (ET)**. TradingView automatically converts to your local timezone, so you don't need to manually adjust anything.
**Example Conversions:**
- 00:00 ET = 05:00 UTC
- 18:00 ET = 23:00 UTC
- 13:30 ET = 18:30 UTC
---
## Support & Updates
This is a standalone version of the True Opens & Key Levels from the full GOTE Indicator. It contains only the level detection code with all series detection removed.
**Version:** 1.0
**Pine Script Version:** 6
**Last Updated:** November 8, 2025
---
## Quick Reference Card
```
╔══════════════════════════════════════════════════════════╗
║ TRUE OPENS & KEY LEVELS - QUICK REFERENCE ║
╠══════════════════════════════════════════════════════════╣
║ ║
║ 📊 PREVIOUS PERIODS ║
║ • Previous Day/Week/Month High/Low ║
║ • Updates at period change ║
║ ║
║ 🕐 SESSION LEVELS ║
║ • NY AM/Lunch/PM, London, Asia H/L ║
║ • Updates after each session ║
║ ║
║ 🎯 TRUE OPENS ║
║ • True Day: Daily 00:00 ET ║
║ • True Session: 1:30/7:30/13:30/19:30 ET ║
║ • True Week: Monday 18:00 ET ║
║ ║
║ 🎨 COLORS ║
║ • Red = Highs • Green = Lows • Blue = Opens ║
║ ║
╚══════════════════════════════════════════════════════════╝
```
---
**Ready to trade with clean, focused key levels!** 🎯
