[F.B]_ZLEMA MACD ZLEMA MACD – A Zero-Lag Variant of the Classic MACD
Introduction & Motivation
The Moving Average Convergence Divergence (MACD) is a standard indicator for measuring trend strength and momentum. However, it suffers from the latency of traditional Exponential Moving Averages (EMAs).
This variant replaces EMAs with Zero Lag Exponential Moving Averages (ZLEMA), reducing delay and increasing the indicator’s responsiveness. This can potentially lead to earlier trend change detection, especially in highly volatile markets.
Calculation Methodology
2.1 Zero-Lag Exponential Moving Average (ZLEMA)
The classic EMA formula is extended with a correction factor:
ZLEMA_t = EMA(2 * P_t - EMA(P_t, L), L)
where:
P_t is the closing price,
L is the smoothing period length.
2.2 MACD Calculation Using ZLEMA
MACD_t = ZLEMA_short,t - ZLEMA_long,t
with standard parameters of 12 and 26 periods.
2.3 Signal Line with Adaptive Methodology
The signal line can be calculated using ZLEMA, EMA, or SMA:
Signal_t = f(MACD, S)
where f is the chosen smoothing function and S is the period length.
2.4 Histogram as a Measure of Momentum Changes
Histogram_t = MACD_t - Signal_t
An increasing histogram indicates a relative acceleration in trend strength.
Potential Applications in Data Analysis
Since the indicator is based solely on price time series, its effectiveness as a standalone trading signal is limited. However, in quantitative models, it can be used as a feature for trend quantification or for filtering market phases with strong trend dynamics.
Potential use cases include:
Trend Classification: Segmenting market phases into "trend" vs. "mean reversion."
Momentum Regime Identification: Analyzing histogram dynamics to detect increasing or decreasing trend strength.
Signal Smoothing: An alternative to classic EMA smoothing in more complex multi-factor models.
Important: Using this as a standalone trading indicator without additional confirmation mechanisms is not recommended, as it does not demonstrate statistical superiority over other momentum indicators.
Evaluation & Limitations
✅ Advantages:
Reduced lag compared to the classic MACD.
Customizable signal line smoothing for different applications.
Easy integration into existing analytical pipelines.
⚠️ Limitations:
Not a standalone trading system: Like any moving average, this indicator is susceptible to noise and false signals in sideways markets.
Parameter sensitivity: Small changes in period lengths can lead to significant signal deviations, requiring robust optimization.
Conclusion
The ZLEMA MACD is a variant of the classic MACD with reduced latency, making it particularly useful for analytical purposes where faster adaptation to price movements is required.
Its application in trading strategies should be limited to multi-factor models with rigorous evaluation. Backtests and out-of-sample analyses are essential to avoid overfitting to past market data.
Disclaimer: This indicator is provided for informational and educational purposes only and does not constitute financial advice. The author assumes no responsibility for any trading decisions made based on this indicator. Trading involves significant risk, and past performance is not indicative of future results.
Tìm kiếm tập lệnh với "histogram"
Neon Momentum Waves StrategyIntroduction
The Neon Momentum Waves Strategy is a momentum-based indicator designed to help traders visualize potential shifts in market direction. It builds upon a MACD-style calculation while incorporating an enhanced visual representation of momentum waves. This approach may assist traders in identifying areas of increasing or decreasing momentum, potentially aligning with market trends or reversals.
How It Works
This strategy is based on a modified MACD (Moving Average Convergence Divergence) method, calculating the difference between two Exponential Moving Averages (EMAs). The momentum wave represents this difference, while an additional smoothing line (signal line) helps highlight potential momentum shifts.
Key Components:
Momentum Calculation:
Uses a fast EMA (12-period) and a slow EMA (26-period) to measure short-term and long-term momentum.
A signal line (20-period EMA of the MACD difference) smooths fluctuations.
The histogram (momentum wave) represents the divergence between the MACD value and the signal line.
Interpreting Momentum Changes:
Momentum Increasing: When the histogram rises above the zero line, it may indicate strengthening upward movement.
Momentum Decreasing: When the histogram moves below the zero line, it may signal a weakening trend or downward momentum.
Potential Exhaustion Points: Users can define custom threshold levels (default: ±10) to highlight when momentum is significantly strong or weak.
Visual Enhancements:
The neon glow effect is created by layering multiple plots with decreasing opacity, enhancing the clarity of momentum shifts.
Aqua-colored waves highlight upward momentum, while purple waves represent downward momentum.
Horizontal reference lines mark the zero line and user-defined thresholds to improve interpretability.
How It Differs from Traditional Indicators
Improved Visualization: Unlike standard MACD histograms, this approach provides clearer visual cues using a neon-style wave format.
Customizable Thresholds: Rather than relying solely on MACD crossovers, users can adjust sensitivity settings to better suit their trading style.
Momentum-Based Approach: The strategy is focused on visualizing shifts in momentum strength, rather than predicting price movements.
Potential Use Cases
Momentum Trend Awareness: Helps traders identify periods where momentum appears to be strengthening or fading.
Market Structure Analysis: May complement other indicators to assess whether price action aligns with momentum changes.
Flexible Timeframe Application: Can be used across different timeframes, depending on the trader’s strategy.
Important Considerations
This strategy is purely momentum-based and does not incorporate volume, fundamental factors, or price action confirmation.
Momentum shifts do not guarantee price direction changes—they should be considered alongside broader market context.
The strategy may perform differently in trending vs. ranging markets, so adjustments in sensitivity may be needed.
Risk management is essential—traders should apply proper stop-losses and position sizing techniques in line with their risk tolerance.
Conclusion
The Neon Momentum Waves Strategy provides a visually enhanced method of tracking momentum, allowing traders to observe potential changes in market strength. While not a predictive tool, it serves as a complementary indicator that may help traders in momentum-based decision-making. As with any technical tool, it should be used as part of a broader strategy that considers multiple factors in market analysis.
Normalized ROC²Normalized Rate of Change of Rate of Change (ROC²) Histogram
Overview
The Normalized ROC² Histogram is a momentum-based indicator designed to detect potential trend reversals by measuring the rate of change of the rate of change of price (the second derivative of price movement). This provides insight into when momentum is slowing down, signaling that a price reversal may be approaching.
The indicator also dynamically changes color to highlight shifts in momentum strength, allowing traders to visualize when price acceleration is increasing or decreasing.
How It Works
🔹 Zero Line Crossovers → Potential Direction Change
• When the histogram approaches zero and crosses over, it suggests that price momentum is shifting and a reversal may be imminent.
• Positive to Negative Crossover: Bearish momentum shift.
• Negative to Positive Crossover: Bullish momentum shift.
🔹 Momentum Strength Visualization → Color Shift
• Dark Blue (⬆️ Increasing Positive Momentum) → Price is accelerating upward.
• Light Blue (🔽 Decreasing Positive Momentum) → Uptrend is weakening.
• Dark Red (⬇️ Increasing Negative Momentum) → Price is accelerating downward.
• Light Red (🔼 Decreasing Negative Momentum) → Downtrend is weakening.
🔹 Normalization for Cleaner Visualization
• Prevents extreme volatility spikes from distorting the histogram.
• Normalizes values on a 0 to 100 scale, ensuring consistent bar height.
How to Use It
✅ Watch for Crossovers Near Zero → These can indicate a trend reversal is forming.
✅ Observe Color Changes → A shift from dark to light signals a deceleration, which often precedes price turning points.
✅ Combine with Other Indicators → Works well with Volume Profile, Moving Averages, and Market Structure analysis.
Why This Indicator is Unique
🚀 Second-derivative momentum detection → Provides early insight into potential price shifts.
📊 Normalized bars prevent distortion → No more extreme spikes ruining the scale.
🎯 Color-coded visual cues → Instantly see when momentum is gaining or fading.
📌 Add the Normalized ROC² Histogram to your charts today to detect potential reversals and momentum shifts in real-time! 🚀
Range Channel by Atilla YurtsevenThis script creates a dynamic channel around a user-selected moving average (MA). It calculates the relative difference between price and the MA, then finds the average of the positive differences and the negative differences separately. Using these averages, it plots upper and lower bands around the MA as well as a histogram-like oscillator to show when price moves above or below the average thresholds.
How It Works
Moving Average Selection
The indicator allows you to choose among multiple MA types (SMA, EMA, WMA, Linear Regression, etc.). Depending on your preference, it calculates the chosen MA for the selected lookback period.
Relative Difference Calculation
It then computes the percentage difference between the source (typically the closing price) and the MA. (diff = (src / ma - 1) * 100)
Positive & Negative Averages
- Positive differences are averaged and represent how far the price typically moves above the MA.
- Negative differences are similarly averaged for when price moves below the MA.
Range Channel & Oscillator
- The channel is plotted around the MA using the average positive and negative differences (Upper Edge and Lower Edge).
- The “Untrended” histogram plots the difference (diff). Green bars occur when price is above the MA on average, and red bars when below. Two additional lines mark the upper and lower average thresholds on this histogram.
How to Use
Identify Overbought/Oversold Zones: The upper edge can serve as a dynamic overbought level, while the lower edge can suggest potential oversold conditions. When the histogram approaches or crosses these levels, it may signal price extremes relative to its average movement.
Trend Confirmation: Compare price action relative to the channel. If price and the histogram consistently remain above the MA and upper threshold, it could indicate a stronger bullish trend. If they remain below, it might signal a prolonged bearish trend.
Entry/Exit Timings:
- Entry: Traders can look for moments when price breaks back inside the channel from an extreme, anticipating a mean reversion.
- Exit: Watching how price interacts with these dynamic edges can help define stop-loss or take-profit points.
Because these thresholds adapt over time based on actual price behavior, they can be more responsive than fixed-percentage bands. However, like all indicators, it’s most effective when used in conjunction with other technical and fundamental tools.
Disclaimer
This script is provided for educational and informational purposes only. It does not guarantee any specific outcome or profit. Use it at your own discretion and risk.
Trade smart, stay safe.
Atilla Yurtseven
Squeeze Momentum Indicator [CHE] Squeeze Momentum Indicator
The Squeeze Momentum Indicator is an improved and simplified version of the classic Squeeze Momentum Indicator by LazyBear. It focuses on precise detection of squeeze phases without relying on Keltner Channels (KC) or complex momentum calculations. Instead, it emphasizes the dynamic analysis of Bollinger Band widths and their distance changes to provide clear and intuitive signals.
What is the Squeeze Momentum Indicator ?
This indicator helps you identify periods of low volatility (squeeze phases) when the market is often poised for significant moves. With its clear visualization and innovative methods, it enables traders to spot breakout opportunities early and trade strategically.
Differences from the Original LazyBear Indicator
1. Use of Bollinger Bands (BB):
- LazyBear Indicator combines Bollinger Bands with Keltner Channels. A squeeze is detected when the Bollinger Bands fall inside the Keltner Channels.
- CHE Indicator relies solely on Bollinger Bands and an additional analysis of their width (distance between the upper and lower bands). This makes the calculation more straightforward and reduces dependency on multiple indicator families.
2. Squeeze Detection:
- LazyBear: A squeeze is defined based on the relationship between Bollinger Bands and Keltner Channels. It has three states: “Squeeze On,” “Squeeze Off,” and “No Squeeze.”
- CHE: A squeeze is detected when the width of the Bollinger Bands falls below the lower "Distance Bollinger Bands." It only has two states: Squeeze Active and No Squeeze.
3. Momentum Calculation:
- LazyBear: Uses linear regression (LinReg) to calculate momentum and displays it as color-coded histograms.
- CHE: Does not include momentum calculations. The focus is entirely on volatility visualization and squeeze detection.
4. Visualization:
- LazyBear: Displays momentum histograms and horizontal lines to signal different states.
- CHE: Visualizes the width of the Bollinger Bands and their Distance Bollinger Bands as lines on the chart. The chart background turns green when a squeeze is detected, simplifying interpretation.
What Is Plotted?
1. Bollinger Band Width:
- A line representing the distance between the upper and lower Bollinger Bands, measuring market volatility.
2. Distance Bollinger Bands:
- Two additional lines (upper and lower Distance Bollinger Bands) based on the Bollinger Band width, defining thresholds for squeeze conditions.
3. Session-Specific Box:
- A dynamic box is drawn on the chart during a squeeze phase. The box marks the high and low of the market for the squeeze duration. It visually frames the range, helping traders monitor breakouts beyond these levels.
4. Max/Min Markers:
- The indicator dynamically updates and marks the maximum and minimum price levels during a squeeze. These levels can serve as breakout thresholds or critical reference points for price action.
5. Background Color:
- The chart background turns green when a squeeze is active (Bollinger Band width falls below the lower Distance Bollinger Bands). This highlights potential breakout conditions.
How to Use the CHE Indicator
1. Add the Indicator:
- Add the indicator to your chart and customize settings such as Bollinger Band length (`sqz_length`) and multiplier (`sqz_multiplier`) to fit your strategy.
2. Identify Squeeze Conditions:
- Watch for the green background, which signals a squeeze—indicating a period of low volatility where significant market moves often follow.
3. Monitor the Box and Max/Min Levels:
- During a squeeze, the box outlines the trading range, and the maximum and minimum levels are updated in real time. Use these as breakout triggers or support/resistance zones.
4. Session-Specific Analysis:
- The indicator can highlight squeezes during specific trading sessions (e.g., market open), allowing you to focus on key time frames.
5. Additional Confirmation:
- Combine the CHE Indicator with price action analysis or momentum tools to determine the direction of potential breakouts.
Why Use the Squeeze Momentum Indicator ?
- Simplicity: Clear visualization and reduced complexity by eliminating Keltner Channels and momentum calculations.
- Flexibility: Suitable for all markets—stocks, forex, crypto, and more.
- Enhanced Visualization: The box and max/min markers provide real-time visual cues for range-bound trading and breakout strategies.
- Efficiency: Focuses on what matters most—identifying volatility and squeeze phases.
With the Squeeze Momentum Indicator , you can take your trading strategy to the next level. Thanks to its clear design, dynamic range visualization, and innovative methods, you’ll recognize breakout opportunities earlier and trade with greater precision. Try it out and experience its user-friendliness and effectiveness for yourself!
faiz MACDMACD: Moving Average Convergence Divergence
The Moving Average Convergence Divergence (MACD) is a popular momentum indicator used in technical analysis to gauge the strength, direction, and potential reversal points of a trend in a financial asset's price movement. Developed by Gerald Appel in the late 1970s, MACD is particularly favored by traders for its ability to capture both trend-following and momentum aspects of price behavior.
Components of the MACD
The MACD is derived from two exponential moving averages (EMAs) of a security's price:
MACD Line: This is the difference between the 12-day and 26-day EMAs. The shorter 12-day EMA reacts more quickly to price changes, while the 26-day EMA smooths out price fluctuations, offering a longer-term perspective.
Formula: MACD Line = 12-day EMA - 26-day EMA
Signal Line: This is the 1-day EMA of the MACD Line itself. The signal line is used to generate buy and sell signals when it crosses the MACD line.
Formula: Signal Line = 1-day EMA of the MACD Line
MACD Histogram: The histogram represents the difference between the MACD Line and the Signal Line. It is displayed as bars that oscillate above and below a zero line, helping to visualize the convergence or divergence between the two lines.
Formula: Histogram = MACD Line - Signal Line
Interpretation of MACD
The MACD indicator is used to identify potential buy and sell signals based on the following observations:
MACD Line and Signal Line Crossovers:
Bullish Crossover: A buy signal occurs when the MACD Line crosses above the Signal Line. This suggests that the momentum is shifting in favor of the bulls, indicating a potential upward price movement.
Bearish Crossover: A sell signal occurs when the MACD Line crosses below the Signal Line. This suggests a bearish trend may be emerging, signaling a potential downward movement.
Divergence:
Bullish Divergence: Occurs when the price of the asset is making new lows, but the MACD is forming higher lows. This suggests that the downward momentum is weakening and a potential reversal to the upside may be imminent.
Bearish Divergence: Occurs when the price is making new highs, but the MACD is forming lower highs. This suggests that the upward momentum is weakening and a reversal to the downside may occur.
Only use it in timeframe m1, and solely use for XAUUSD pair.
Advisable to use it as a confirmation with other indicator such as
BBMA, SMC, SUPPORT RESISTANCE, SUPPLY AND DEMAND.
how to use :
MA 5 Crossing above MA9, will generate BUY signals
MA 5 Crossing below MA9, will generate SELL signals
Trade at your own SKILLS.
I dont mind people using this script for free.
All I want is just prayer for me and my family success.
Thank You and Have a nice and pleasant day :-)
NYSE VOLD RatioThe UVOL/DVOL Two-Sided Ratio Histogram is a custom indicator that visualizes the relationship between the up volume ( USI:UVOL ) and down volume ( USI:DVOL ) on any given chart timeframe. The indicator dynamically adjusts to the chart’s timeframe and displays the ratio of USI:UVOL to USI:DVOL in a histogram format, making it easy to spot when the up volume exceeds down volume (and vice versa).
The ratio is calculated as follows:
If USI:UVOL > USI:DVOL : The ratio is USI:UVOL / USI:DVOL , displayed as a positive bar.
If USI:DVOL > USI:UVOL : The ratio is USI:DVOL / USI:UVOL , displayed as a negative bar.
This approach allows traders to quickly gauge market sentiment by comparing buying volume to selling volume. The indicator is centered around a zero line, where:
Positive bars indicate that up volume is stronger than down volume.
Negative bars indicate that down volume is stronger than up volume.
Features:
Dynamic Timeframe: Automatically adjusts to the chart’s selected timeframe.
Two-Sided Histogram: Displays positive and negative bars based on the $UVOL/ USI:DVOL ratio.
Zero Reference Line: A clear horizontal line at 0 to help identify shifts in volume dominance.
Easy Volume Sentiment Analysis: Quickly spot trends in market buying vs. selling pressure.
Use Case:
This indicator is ideal for traders who want a quick, visual representation of market sentiment by comparing volume on the upside (buying pressure) versus downside (selling pressure). It can be used for identifying strong buying or selling pressure and potential reversal points.
Volume PACustom volume histogram that visually represents trading volume in relation to the price action of the current bar. The histogram is colored based on whether the current bar is bullish or bearish, and it greys out when the current volume is lower than the volumes of the previous specified number of bars.
Customizable Bar Count: Users can specify how many previous bars to compare against for determining if the current volume is lower.
Default color-coded histogram:
Green: Indicates a bullish bar (closing price is greater than opening price).
Red: Indicates a bearish bar (closing price is less than opening price).
Grey: Indicates that the current volume is lower than the volumes of the previous specified number of bars.
RSI Trend Following StrategyOverview
The RSI Trend Following Strategy utilizes Relative Strength Index (RSI) to enter the trade for the potential trend continuation. It uses Stochastic indicator to check is the price is not in overbought territory and the MACD to measure the current price momentum. Moreover, it uses the 200-period EMA to filter the counter trend trades with the higher probability. The strategy opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Two layers trade filtering system: Strategy utilizes MACD and Stochastic indicators measure the current momentum and overbought condition and use 200-period EMA to filter trades against major trend.
Trailing take profit level: After reaching the trailing profit activation level script activates the trailing of long trade using EMA. More information in methodology.
Wide opportunities for strategy optimization: Flexible strategy settings allows users to optimize the strategy entries and exits for chosen trading pair and time frame.
Methodology
The strategy opens long trade when the following price met the conditions:
RSI is above 50 level.
MACD line shall be above the signal line
Both lines of Stochastic shall be not higher than 80 (overbought territory)
Candle’s low shall be above the 200 period EMA
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with trailing EMA(by default = 20 period). If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.75)
ATR Trailing Profit Activation Level (by default = 2.25)
MACD Fast Length (by default = 12, period of averaging fast MACD line)
MACD Fast Length (by default = 26, period of averaging slow MACD line)
MACD Signal Smoothing (by default = 9, period of smoothing MACD signal line)
Oscillator MA Type (by default = EMA, available options: SMA, EMA)
Signal Line MA Type (by default = EMA, available options: SMA, EMA)
RSI Length (by default = 14, period for RSI calculation)
Trailing EMA Length (by default = 20, period for EMA, which shall be broken close the trade after trailing profit activation)
Justification of Methodology
This trading strategy is designed to leverage a combination of technical indicators—Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), Stochastic Oscillator, and the 200-period Exponential Moving Average (EMA)—to determine optimal entry points for long trades. Additionally, the strategy uses the Average True Range (ATR) for dynamic risk management to adapt to varying market conditions. Let's look in details for which purpose each indicator is used for and why it is used in this combination.
Relative Strength Index (RSI) is a momentum indicator used in technical analysis to measure the speed and change of price movements in a financial market. It helps traders identify whether an asset is potentially overbought (overvalued) or oversold (undervalued), which can indicate a potential reversal or continuation of the current trend.
How RSI Works? RSI tracks the strength of recent price changes. It compares the average gains and losses over a specific period (usually 14 periods) to assess the momentum of an asset. Average gain is the average of all positive price changes over the chosen period. It reflects how much the price has typically increased during upward movements. Average loss is the average of all negative price changes over the same period. It reflects how much the price has typically decreased during downward movements.
RSI calculates these average gains and losses and compares them to create a value between 0 and 100. If the RSI value is above 70, the asset is generally considered overbought, meaning it might be due for a price correction or reversal downward. Conversely, if the RSI value is below 30, the asset is considered oversold, suggesting it could be poised for an upward reversal or recovery. RSI is a useful tool for traders to determine market conditions and make informed decisions about entering or exiting trades based on the perceived strength or weakness of an asset's price movements.
This strategy uses RSI as a short-term trend approximation. If RSI crosses over 50 it means that there is a high probability of short-term trend change from downtrend to uptrend. Therefore RSI above 50 is our first trend filter to look for a long position.
The MACD (Moving Average Convergence Divergence) is a popular momentum and trend-following indicator used in technical analysis. It helps traders identify changes in the strength, direction, momentum, and duration of a trend in an asset's price.
The MACD consists of three components:
MACD Line: This is the difference between a short-term Exponential Moving Average (EMA) and a long-term EMA, typically calculated as: MACD Line = 12 period EMA − 26 period EMA
Signal Line: This is a 9-period EMA of the MACD Line, which helps to identify buy or sell signals. When the MACD Line crosses above the Signal Line, it can be a bullish signal (suggesting a buy); when it crosses below, it can be a bearish signal (suggesting a sell).
Histogram: The histogram shows the difference between the MACD Line and the Signal Line, visually representing the momentum of the trend. Positive histogram values indicate increasing bullish momentum, while negative values indicate increasing bearish momentum.
This strategy uses MACD as a second short-term trend filter. When MACD line crossed over the signal line there is a high probability that uptrend has been started. Therefore MACD line above signal line is our additional short-term trend filter. In conjunction with RSI it decreases probability of following false trend change signals.
The Stochastic Indicator is a momentum oscillator that compares a security's closing price to its price range over a specific period. It's used to identify overbought and oversold conditions. The indicator ranges from 0 to 100, with readings above 80 indicating overbought conditions and readings below 20 indicating oversold conditions.
It consists of two lines:
%K: The main line, calculated using the formula (CurrentClose−LowestLow)/(HighestHigh−LowestLow)×100 . Highest and lowest price taken for 14 periods.
%D: A smoothed moving average of %K, often used as a signal line.
This strategy uses stochastic to define the overbought conditions. The logic here is the following: we want to avoid long trades in the overbought territory, because when indicator reaches it there is a high probability that the potential move is gonna be restricted.
The 200-period EMA is a widely recognized indicator for identifying the long-term trend direction. The strategy only trades in the direction of this primary trend to increase the probability of successful trades. For instance, when the price is above the 200 EMA, only long trades are considered, aligning with the overarching trend direction.
Therefore, strategy uses combination of RSI and MACD to increase the probability that price now is in short-term uptrend, Stochastic helps to avoid the trades in the overbought (>80) territory. To increase the probability of opening long trades in the direction of a main trend and avoid local bounces we use 200 period EMA.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.08.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 30%
Maximum Single Position Loss: -3.94%
Maximum Single Profit: +15.78%
Net Profit: +1359.21 USDT (+13.59%)
Total Trades: 111 (36.04% win rate)
Profit Factor: 1.413
Maximum Accumulated Loss: 625.02 USDT (-5.85%)
Average Profit per Trade: 12.25 USDT (+0.40%)
Average Trade Duration: 40 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 2h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
MACD with 1D Stochastic Confirmation Reversal StrategyOverview
The MACD with 1D Stochastic Confirmation Reversal Strategy utilizes MACD indicator in conjunction with 1 day timeframe Stochastic indicators to obtain the high probability short-term trend reversal signals. The main idea is to wait until MACD line crosses up it’s signal line, at the same time Stochastic indicator on 1D time frame shall show the uptrend (will be discussed in methodology) and not to be in the oversold territory. Strategy works on time frames from 30 min to 4 hours and opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Higher time frame confirmation: Strategy utilizes 1D Stochastic to establish the major trend and confirm the local reversals with the higher probability.
Trailing take profit level: After reaching the trailing profit activation level scrip activate the trailing of long trade using EMA. More information in methodology.
Methodology
The strategy opens long trade when the following price met the conditions:
MACD line of MACD indicator shall cross over the signal line of MACD indicator.
1D time frame Stochastic’s K line shall be above the D line.
1D time frame Stochastic’s K line value shall be below 80 (not overbought)
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with EMA. If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 3.25, value multiplied by ATR to be subtracted from position entry price to setup stop loss)
ATR Trailing Profit Activation Level (by default = 4.25, value multiplied by ATR to be added to position entry price to setup trailing profit activation level)
Trailing EMA Length (by default = 20, period for EMA, when price reached trailing profit activation level EMA will stop out of position if price closes below it)
User can choose the optimal parameters during backtesting on certain price chart, in our example we use default settings.
Justification of Methodology
This strategy leverages 2 time frames analysis to have the high probability reversal setups on lower time frame in the direction of the 1D time frame trend. That’s why it’s recommended to use this strategy on 30 min – 4 hours time frames.
To have an approximation of 1D time frame trend strategy utilizes classical Stochastic indicator. The Stochastic Indicator is a momentum oscillator that compares a security's closing price to its price range over a specific period. It's used to identify overbought and oversold conditions. The indicator ranges from 0 to 100, with readings above 80 indicating overbought conditions and readings below 20 indicating oversold conditions.
It consists of two lines:
%K: The main line, calculated using the formula (CurrentClose−LowestLow)/(HighestHigh−LowestLow)×100 . Highest and lowest price taken for 14 periods.
%D: A smoothed moving average of %K, often used as a signal line.
Strategy logic assumes that on 1D time frame it’s uptrend in %K line is above the %D line. Moreover, we can consider long trade only in %K line is below 80. It means that in overbought state the long trade will not be opened due to higher probability of pullback or even major trend reversal. If these conditions are met we are going to our working (lower) time frame.
On the chosen time frame, we remind you that for correct work of this strategy you shall use 30min – 4h time frames, MACD line shall cross over it’s signal line. The MACD (Moving Average Convergence Divergence) is a popular momentum and trend-following indicator used in technical analysis. It helps traders identify changes in the strength, direction, momentum, and duration of a trend in a stock's price.
The MACD consists of three components:
MACD Line: This is the difference between a short-term Exponential Moving Average (EMA) and a long-term EMA, typically calculated as: MACD Line=12-period EMA−26-period
Signal Line: This is a 9-period EMA of the MACD Line, which helps to identify buy or sell signals. When the MACD Line crosses above the Signal Line, it can be a bullish signal (suggesting a buy); when it crosses below, it can be a bearish signal (suggesting a sell).
Histogram: The histogram shows the difference between the MACD Line and the Signal Line, visually representing the momentum of the trend. Positive histogram values indicate increasing bullish momentum, while negative values indicate increasing bearish momentum.
In our script we are interested in only MACD and signal lines. When MACD line crosses signal line there is a high chance that short-term trend reversed to the upside. We use this strategy on 45 min time frame.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.08.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 30%
Maximum Single Position Loss: -4.79%
Maximum Single Profit: +20.14%
Net Profit: +2361.33 USDT (+44.72%)
Total Trades: 123 (44.72% win rate)
Profit Factor: 1.623
Maximum Accumulated Loss: 695.80 USDT (-5.48%)
Average Profit per Trade: 19.20 USDT (+0.59%)
Average Trade Duration: 30 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe between 30 min and 4 hours and chart (optimal performance observed on 45 min BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Entropy Volatility Index [CHE]I Entropy Volatility Index (EVI)
II An Experimental Script for Measuring Market Volatility
III Introduction
The Entropy Volatility Index (EVI) is an experimental indicator based on concepts from thermodynamics and information theory. The goal of the EVI is to quantify market uncertainty and volatility by calculating the entropy of price changes.
IV Basic Concepts
Entropy in Thermodynamics
Entropy is a measure of disorder or randomness in a system.
The second law of thermodynamics states that entropy in a closed system tends to increase over time.
Entropy in Information Theory
In information theory, entropy measures the uncertainty or information content of a random variable.
The entropy H of a random variable X with probability distribution P(x) is calculated as:
H(X) = -∑ P(x) log P(x)
V Derivation of the EVI
Calculation of Price Changes
Absolute price changes are calculated to serve as the basis for probability calculations.
Creation of the Histogram
A histogram is created and initialized to count the frequency of price changes.
Updating the Histogram
The histogram is updated by counting the frequency of each price change.
Calculation of Probabilities
The probabilities of the price changes are calculated based on their frequencies in the histogram.
Calculation of Entropy
Entropy is calculated using the probabilities of price changes. Higher entropy indicates higher uncertainty or disorder in the market.
Plotting the Indicator
The EVI is plotted to visually represent market volatility and uncertainty.
VI Interpretation of the EVI
High EVI Values
High Volatility: Strong and irregular price movements.
High Uncertainty: Increased market uncertainty.
Possible Market Turning Points: Indicators of potential trend changes.
Low EVI Values
Low Volatility: More consistent and predictable price movements.
Stability: More stable market phases.
Trend Consistency: Indicators of stable trends or sideways movements.
VII Conclusion
The Entropy Volatility Index (EVI) is an experimental script that applies concepts from thermodynamics and information theory to measure market volatility. It offers a new perspective on market uncertainty and can be used as an additional tool for traders.
VIII Example Use Cases
Identifying Volatile Phases: Use the EVI to identify periods of high volatility and prepare for potential rapid price movements.
Risk Management: Adjust your risk management strategy based on the EVI. During high EVI periods, consider hedging positions or adjusting position sizes.
Complementing Other Indicators: Combine the EVI with other technical indicators (e.g., RSI, MACD) for a more comprehensive view of market conditions.
I hope this experimental script provides valuable insights. Thank you for your feedback and suggestions for improvement.
Best regards,
Chervolino
RSI and MACD Composite ScoreComponents of the Indicator
RSI Settings:
The RSI is set with a length parameter, which can be adjusted by the user but defaults to 14. This measures the speed and change of price movements.
MACD Settings:
The MACD is composed of two lines: the MACD line and the signal line, which are calculated from exponential moving averages (EMAs) of different lengths (fast and slow). The default settings are 9 for the fast length, 26 for the slow length, and 3 for the signal length.
The MACD histogram, which is the difference between the MACD line and the signal line, is also calculated.
Normalization and Combination
RSI Normalization : The RSI values are normalized around 0 by subtracting 50 from the RSI and then dividing by 50. This scaling adjusts the RSI to fluctuate around 0, where positive values indicate strength and negative values indicate weakness relative to the median RSI value of 50.
MACD Normalization : The MACD histogram is normalized by dividing it by the highest absolute value of the histogram over the slow length period. This adjustment scales the MACD histogram to fall between -1 and 1, making it comparable in magnitude to the normalized RSI.
Composite Score Calculation
The composite score is simply the sum of the normalized RSI and the normalized MACD histogram. This results in a combined score that reflects both momentum (from RSI) and trend (from MACD), providing a multifaceted view of market dynamics.
Visualization
The composite score is plotted as an oscillator, with a horizontal zero line that helps identify when the score shifts from positive to negative or vice versa.
The background color changes based on the trend: green if the composite score is above zero (bullish trend) and red if below zero (bearish trend).
Monte Carlo Simulation - Your Strategy [Kioseff Trading]Hello!
This script “Monte Carlo Simulation - Your Strategy” uses Monte Carlo simulations for your inputted strategy returns or the asset on your chart!
Features
Monte Carlo Simulation: Performs Monte Carlo simulation to generate multiple future paths.
Asset Price or Strategy: Can simulate either future asset prices based on historical log returns or a specific trading strategy's future performance.
User-Defined Input: Allows you to input your own historical returns for simulation.
Statistical Methods: Offers two simulation methods—Gaussian (Normal) distribution and Bootstrapping.
Graphical Display: Provides options for graphical representation, including line plots and histograms.
Cumulative Probability Target: Enables setting a user-defined cumulative probability target to quantify simulation results.
Adjustable Parameters: Offers numerous user-adjustable settings like number of simulations, forecast length, and more.
Historical Data Points: Option to specify the amount of historical data to be used in the simulation (price).
Custom Binning: Allows you to select the binning method for histograms, with options like Sturges, Rice, and Square Root.
Best/Worst Case: Allows you to show only the best case / worst case outcome (range) for all simulations!
Scatterplot: allows you to show up to 1000 potential outcomes for a specified trade number (or bars forward price endpoint) using a scatter plot.
The image above shows the primary components of the indicator!
The image above shows the best/worst case outcome feature in action!
The image above shows a "fun feature" where 1000 simulated end points for a 15-bar price trajectory are shown as a scatter plot!
How To Perform a Monte Carlo Simulation On Your Strategy
Really, you can input any data into the indicator it will perform a Monte Carlo Simulation on it :D
The following instructions show how to export your strategy results from TradingView to an Excel File, copy the data, and input it into the indicator.
However , you are not limited to following this method!
Wherever your strategy results are stored, simply copy and paste them into the indicator text area in the settings and simulations will begin.
Returns Should Follow This Format
1
3
-3
2
-5
The numbers are presented as a single column. No commas or separators used.
The numbers above are in sequential order. A return of "1" for the first trade and a return of "-5" for the last trade. Your strategy returns will likely be in sequential order already so don't worry too much about this (:
How To Perform a Monte Carlo Simulation On Your TradingView Strategy With Excel Data
Export your strategy returns to an excel file using TradingView
Navigate to your downloads folder to column G "Profit"
Click the column and press CTRL + SPACE to highlight the entire column
Press CTRL + C to copy the entire column
Open this indicator's settings and paste the returns into the text area
The image above illustrates the process!
Notes on Inputting Returns
*Must input your returns without a separate as a vertical list
*The initial text area can only hold so many return values. If your list of trades is large you can input additional returns into two additional text areas at the bottom of the indicator settings.
That should be it; thank you for checking this out!
Sudden increase in volume [PINESCRIPTLABS]The indicator plots buying and selling histograms on the price chart, as well as graphical signals in the form of triangles to highlight buying and selling conditions. Buying conditions are based on a sudden increase in volume and oversold RSI, while selling conditions are based on a sudden increase in volume and overbought RSI.
In summary, this strategy aims to identify moments when there is a significant surge in trading volume along with overbought or oversold conditions in the RSI. These moments are considered potential signals for buying or selling in the market.
Sudden Volume Surge: It checks if the current volume is greater than a multiple of the exponential moving average of volume (EMA) calculated with a specific length (ema_length). This indicates a sudden surge in trading volume.
RSI Overbought and Oversold Levels: Two RSI values, rsi_overbought and rsi_oversold, are used as references. If the RSI value is below the rsi_oversold level, it is considered to be in oversold territory, and if the RSI value is above the rsi_overbought level, it is considered to be in overbought territory.
El indicador plotea histogramas de compra y venta en el gráfico de precios, así como señales gráficas en forma de triángulos para resaltar las condiciones de compra y venta. Las condiciones para la compra se basan en un aumento brusco de volumen y un RSI en sobreventa, mientras que las condiciones para la venta se basan en un aumento brusco de volumen y un RSI en sobrecompra.
En resumen, esta estrategia busca identificar momentos en los que haya un aumento significativo en el volumen de operaciones junto con condiciones de sobrecompra o sobreventa en el RSI. Estos momentos se consideran señales potenciales de compra o venta en el mercado.
Aumento brusco de volumen: Se verifica si el volumen actual es mayor que un múltiplo del promedio móvil exponencial del volumen (EMA) calculado con una longitud específica (ema_length). Esto indica un aumento repentino en el volumen de operaciones.
Niveles de RSI en sobrecompra y sobreventa: Se utilizan dos valores de RSI como referencia, rsi_overbought y rsi_oversold. Si el valor del RSI está por debajo del nivel rsi_oversold, se considera que está en territorio de sobreventa, y si el valor del RSI está por encima del nivel rsi_overbought, se considera que está en territorio de sobrecompra.
HT Momentum Indicator [ ZCrypto ]
The HT Momentum Indicator is a technical analysis tool that uses the Hyperbolic Tangent (tanh) function to measure momentum in a trading instrument.
This indicator is plotted as a histogram, with positive values indicating bullish momentum and negative values indicating bearish momentum.
Here are the main features and settings of the HT Momentum Indicator:
Source: This setting allows you to choose the price data used to calculate the momentum indicator. By default, the indicator uses the (High+Low+Close)/3 price, but you can select other options such as the open, high, or low prices.
Period: This setting determines the number of periods used in the momentum calculation. By default, the indicator uses a period of 14, but you can adjust this to suit your trading style and the market you are trading.
Show Fast/Slow/VWAP: These settings allow you to choose whether or not to display the fast and slow exponential moving averages (EMAs) and the volume-weighted average price (VWAP) on the chart.
Fast Length/Slow Length/VWAP Length: These settings allow you to adjust the length of the fast and slow EMAs and the VWAP calculation.
Bull Color/Bear Color: These settings allow you to choose the colors for the bullish and bearish histograms.
Zero Line: This indicator also includes a horizontal line at the zero level to help you identify when momentum is transitioning from bullish to bearish or vice versa.
The HT Momentum Indicator can be used to identify trends, momentum shifts, and potential buy/sell signals.
you can use the fast and slow EMAs to identify short-term and long-term trends, respectively, and the VWAP to gauge the strength of buying or selling pressure.
Additionally, the HT Momentum Indicator includes four pre-programmed alert conditions, which can notify you
when the fast EMA crosses above the slow EMA,
when the VWAP crosses above the zero line,
when the histogram transitions from negative to positive values.
when the histogram transitions from negative to positive values and VWAP above zero line
Cheat Code's RedemptionWELCOME TO THE CHEAT CODE REDEMPTION PACK!!!!
I want to take a deep dive into what this indicator consists of and how you can use it to improve your trading strategy.
-What does the CCR consist of?
The Oscillator:
The oscillator is a combination of a true strength index sampled from on-balance volume and a regular RSI at default settings. The reason I added the on-balance volume is that it does not tend to remain at overbought or oversold conditions as traditional momentum oscillators do.
The Histogram:
The histogram is copied to a tee from the MACD histogram, the only difference here is that I extended the moving averages to depict a special pairing; the ema55 slow and ema21 fast. I then converted it into another true strength index, as the calculations fit all time frames.
The Divergences:
The divergences of an indicator can be extremely useful in catching scalp opportunities, a DARK RED/GREEN represents a REGULAR divergence, while a SALMON/LIGHT GREEN color represents a HIDDEN divergence.
The moving average:
The moving average built into this indicator is depicted as an aqua or yellow line, when the oscillator is moving in an uptrend, the moving average will appear aqua, when the oscillator is in a downtrend it will appear yellow. Use this as confirmation bias or as the third derivative of market position.
Oscillator Colors:
The Oscillator color is an important thesis of this indicator. When the line is green, it means the market is effectively in an uptrend, when it is red, it means the market is in a downtrend. Use this to prevent longing in a serious downtrend and vice versa.
If you have any questions regarding the indicator(s), feel free to reach out to me in the comments or through Direct Message!!!
Safe Trading, Don't get Rekt
- CheatCode1 <3
Kase Peak Oscillator w/ Divergences [Loxx]Kase Peak Oscillator is unique among first derivative or "rate-of-change" indicators in that it statistically evaluates over fifty trend lengths and automatically adapts to both cycle length and volatility. In addition, it replaces the crude linear mathematics of old with logarithmic and exponential models that better reflect the true nature of the market. Kase Peak Oscillator is unique in that it can be applied across multiple time frames and different commodities.
As a hybrid indicator, the Peak Oscillator also generates a trend signal via the crossing of the histogram through the zero line. In addition, the red/green histogram line indicates when the oscillator has reached an extreme condition. When the oscillator reaches this peak and then turns, it means that most of the time the market will turn either at the present extreme, or (more likely) at the following extreme.
This is both a reversal and breakout/breakdown indicator. Crosses above/below zero line can be used for breakouts/breakdowns, while the thick green/red bars can be used to detect reversals
The indicator consists of three indicators:
The PeakOscillator itself is rendered as a gray histogram.
Max is a red/green solid line within the histogram signifying a market extreme.
Yellow line is max peak value of two (by default, you can change this with the deviations input settings) standard deviations of the Peak Oscillator value
White line is the min peak value of two (by default, you can change this with the deviations input settings) standard deviations of the PeakOscillator value
The PeakOscillator is used two ways:
Divergence: Kase Peak Oscillator may be used to generate traditional divergence signals. The difference between it and traditional divergence indicators lies in its accuracy.
PeakOut: The second use is to look for a Peak Out. A Peak Out occurs when the histogram breaks beyond the PeakOut line and then pulls back. A Peak Out through the maximum line will be displayed magenta. A Peak Out, which only extends through the Peak Min line is called a local Peak Out, and is less significant than a normal Peak Out signal. These local Peak Outs are to be relied upon more heavily during sideways or corrective markets. Peak Outs may be based on either the maximum line or the minimum line. Maximum Peak Outs, however, are rarer and thus more significant than minimum Peak Outs. The magnitude of the price move may be greater following the maximum Peak Out, but the likelihood of the break in trend is essentially the same. Thus, our research indicates that we should react equally to a Peak Out in a trendy market and a Peak Min in a choppy or corrective market.
Included:
Bar coloring
Alerts
MAConverging + QQE Threshold This trading script is a trading strategy that is made up of 2 public indicators so credit goes to LuxAlgo and Jose5770. I have the 2 indicators listed below.
1) Moving Average Converging (LuxAlgo)
2) QQE Threshold (Jose5770)
This trading strategy is buying when the two indicators align, and then the take profit is the first red bar on the QQE Threshold histogram. It is not a set risk reward but instead a variable take profit strategy. I have the rules of the strategy listed below in order of how it works.
Long Position :
1. Wait for Moving Average Converging to be green
2. Candlestick is green from the QQE Threshold indicator
3. QQE Threshold histogram is green as well, then it enters the trade once we have these criteria met.
Take profit is the first red bar on the QQE Threshold histogram that appears and the trade will close.
Short Position :
1. Wait for Moving Average Converging to be red
2. Candlestick is red from the QQE Threshold indicator
3. QQE Threshold histogram is red as well, then it enters the trade once we have these criteria met.
Take profit is the first green bar on the QQE Threshold histogram that appears and the trade will close.
I hope everyone enjoys!
SL and TP - ATRThis indicator is using ATR ( Average True Range ) to set the Target point and Stop loss.
Use the pink number as target, always.
If you are in Long position, use the green number as stop loss, so the red number is not useful in Buys.
If you are in Short position, use the Red number as stop loss, so the green number is not useful in Sells.
** Need to enter the numbers in ticks --> VERY IMPORTANT: Write it completely, even the numbers after the point sign but DO NOT WRITE the point sign itself. e.g. : if the target tick on indicator is 123.75, you have to write 12375 ticks for your TP. ( one more example: If the number is 0.0001203 , write 1203 ticks. )
Enter the information of the opening candle.
Most of the times, risk/reward ratio is a bit higher than 1.
Works on multi timeframes. P.S: Haven't checked the weekly timeframe.
Not trying to oversell the indicator, but this is perhaps the best TP/SL specifier.
For beauty purposes, change (Sl @ buy) and (TP @ sell) to histograms.
Histograms are only for visual purposes. Customize the indicator as you want :)) Hope you enjoy
BBPBΔ(OBV-PVT)BB - Time Series Decomposition & Volume WeightedThis is an indicator that shows 5 different points of information:
#1 The Trendline is uses a time-series decomposition to remove noise and seasonality data to provide a trendline without using moving averages. This is then further processed by a custom VWAP block that weights it based on the time frame you're currently using.
#2 BB%B - This is the blue histogram that's partially transparent. This is used to find when a security is overbought or oversold.
#3 BB%B of the Δ(OBV-PVT). This is the green histogram. We took the OBV and subtracted the PVT from it, then we found the delta of that compared to the previous candle. This output a line, which we wrapped in bollinger bands to find the BB%B of this line. This line is represented as a histogram, for visual clarity.
#4 Long and Short Indicators: Long is represented by a green dot, and short is represented by a red dot.
#5 Zones - there are multiple zones, which are used to identify overbought and oversold zones.
How to use the indicator:
Simple way: Long on green dot, Short on red dot. Use stop losses and take profits.
Slightly More Complex: Same as above, but also close out longs, when the green histogram drops but the blue does not. As this means price action hasn't caught up with volume. Use stop losses and take profits.
Full Usage: Long only when both the green, blue and yellow lines are below 0, and sell when the blue or green histogram rises above 1. Perform the opposite for the shorting. Ignore the dots if you use this method, they are for simple reference points til you get used to this indicator. Use stop losses and take profits.
MACD BTC Long/Short Strategy v1.0This strategy will use only default MACD with Simple MA(Signal Line) mode 'ON' to determine when it's time to long/short using its histogram value.
Current version has 2 more entries added to increase more trades and profits along the way while maintaining low 'max drawdown' and high returns.
Entry will be opened when macd line(blue) crossed with signal line(red).
Entry will be closed when histogram increased/decreased opposite its previous histogram.
Re-enter will opened a position when histogram continues after X delay (Re-enter Delay setting).
Sculp will opened a position when histogram is still in light colors for X delay (Sculp Delay setting).
macd xoverThe MACD XOver indicator was developed by John Bruns to predict the price point at which MACD Histogram will reverse the direction of its slope.
The indicator is plotted one day ahead into the future, allowing, if your strategy depends on MACD Histogram, to predict its reversal point for tomorrow (or the next bar in any timeframe). If the closing price tomorrow is above the value of this indicator, then MACD Histogram will tick up. If the closing price tomorrow is below the value of this indicator, then MACD Histogram will tick down. This is especially useful on the charts of the longer timeframes and when using the Impulse system whose color depends in part on the slope of MACD Histogram.
Use the same values as the MACD Combo which you want to anticipate. If you use the default values, then accept the values below.
Parameters:
MACD_Short_Period(12) – The short EMA for the MACD calculation;
MACD_Long_Period (26) – The long EMA for the MACD calculation;
MACD_Smoothing_Period (9) – The smoothing value for the Signal line;
Time_Ratio (1) – The default here is set to 5 (weekly)
Triple Coppock CurveThe Coppock Curve is a zero-centered momentum oscillator that relies primarily on rate of change calculations. The Coppock Curve in its most basic form is already a great indicator, especially for spotting shifts in momentum. But, we wanted to see how we could modify it to get some better performance out of it.
As the ‘cop’ function demonstrates, the Coppock Curve has a pretty simple calculation. The first step is to calculate the rate of change at a longer and shorter window length. Next, the sum of the two rate of change values is calculated and finally a weighted moving average of a user defined length is calculated(this is the Coppock Curve).
The ‘cop()’ function set the foundation to allow us to implement our modifications. As you can see in the graph, there are 3 different lines (2 histogram and 1 normal line) comprising the Coppock values based on the rate of change of high, low, and closing prices. We liked this layout because it allows traders to easily identify the curve’s pivots and the balance of negative vs. positive momentum.
The Coppock Curve based on high prices is plotted as the teal histogram, wile the pink histogram represents the Coppock Curve of low prices. The curve based on closing prices is the red and green alternating line plotted on top of the two histograms.
We included some notes on the chart to help with interpreting the three curves.
There are two common approaches traders can take when trading with the indicator:
1. Trade based on closing price curve: Go long when line changes from bearish(red) to bullish(green). Then, go short when same line changes from bullish to bearish.
2. Trade based on crossings of the zero-line. This could be based on the high, low, or closing price curves, but closing price is the safest bet. So, go long when it crosses from negative into positive territory and short when it crosses under the zero line from positive into negative territory.
