Equilibrium Candles + Pattern [Honestcowboy]The Equilibrium Candles is a very simple trend continuation or reversal strategy depending on your settings.
How an Equilibrium Candle is created:
We calculate the equilibrium by measuring the mid point between highest and lowest point over X amount of bars back.
This now is the opening price for each bar and will be considered a green bar if price closes above equilibrium.
Bars get shaded by checking if regular candle close is higher than open etc. So you still see what the normal candles are doing.
Why are they useful?
The equilibrium is calculated the same as Baseline in Ichimoku Cloud. Which provides a point where price is very likely to retrace to. This script visualises the distance between close and equilibrium using candles. To provide a clear visual of how price relates to this equilibrium point.
This also makes it more straightforward to develop strategies based on this simple concept and makes the trader purely focus on this relationship and not think of any Ichimoku Cloud theories.
Script uses a very simple pattern to enter trades:
It will count how many candles have been one directional (above or below equilibrium)
Based on user input after X candles (7 by default) script shows we are in a trend (bg colors)
On the first pullback (candle closes on other side of equilibrium) it will look to enter a trade.
Places a stop order at the high of the candle if bullish trend or reverse if bearish trend.
If based on user input after X opposite candles (2 by default) order is not filled will cancel it and look for a new trend.
Use Reverse Logic:
There is a use reverse logic in the settings which on default is turned on. It will turn long orders into short orders making the stop orders become limit orders. It will use the normal long SL as target for the short. And TP as stop for the short. This to provide a means to reverse equity curve in case your pair is mean reverting by nature instead of trending.
ATR Calculation:
Averaged ATR, which is using ta.percentile_nearest_rank of 60% of a normal ATR (14 period) over the last 200 bars. This in simple words finds a value slightly above the mean ATR value over that period.
Big Candle Exit Logic:
Using Averaged ATR the script will check if a candle closes X times that ATR from the equilibrium point. This is then considered an overextension and all trades are closed.
This is also based on user input.
Simple trade management logic:
Checks if the user has selected to use TP and SL, or/and big candle exit.
Places a TP and SL based on averaged ATR at a multiplier based on user Input.
Closes trade if there is a Big Candle Exit or an opposite direction signal from indicator.
Script can be fully automated to MT5
There are risk settings in % and symbol settings provided at the bottom of the indicator. The script will send alert to MT5 broker trying to mimic the execution that happens on tradingview. There are always delays when using a bridge to MT5 broker and there could be errors so be mindful of that. This script sends alerts in format so they can be read by tradingview.to which is a bridge between the platforms.
Use the all alert function calls feature when setting up alerts and make sure you provide the right webhook if you want to use this approach.
There is also a simple buy and sell alert feature if you don't want to fully automate but still get alerts. These are available in the dropdown when creating an alert.
Almost every setting in this indicator has a tooltip added to it. So if any setting is not clear hover over the (?) icon on the right of the setting.
The backtest uses a 4% exposure per trade and a 10 point slippage. I did not include a commission cause I'm not personaly aware what the commissions are on most forex brokers. I'm only aware of minimal slippage to use in a backtest. Trading conditions vary per broker you use so always pay close attention to trading costs on your own broker. Use a full automation at your own risk and discretion and do proper backtesting.
Phân tích Xu hướng
SuperATR 7-Step Profit - Strategy [presentTrading] Long time no see!
█ Introduction and How It Is Different
The SuperATR 7-Step Profit Strategy is a multi-layered trading approach that integrates adaptive Average True Range (ATR) calculations with momentum-based trend detection. What sets this strategy apart is its sophisticated 7-step take-profit mechanism, which combines four ATR-based exit levels and three fixed percentage levels. This hybrid approach allows traders to dynamically adjust to market volatility while systematically capturing profits in both long and short market positions.
Traditional trading strategies often rely on static indicators or single-layered exit strategies, which may not adapt well to changing market conditions. The SuperATR 7-Step Profit Strategy addresses this limitation by:
- Using Adaptive ATR: Enhances the standard ATR by making it responsive to current market momentum.
- Incorporating Momentum-Based Trend Detection: Identifies stronger trends with higher probability of continuation.
- Employing a Multi-Step Take-Profit System: Allows for gradual profit-taking at predetermined levels, optimizing returns while minimizing risk.
BTCUSD 6hr Performance
█ Strategy, How It Works: Detailed Explanation
The strategy revolves around detecting strong market trends and capitalizing on them using an adaptive ATR and momentum indicators. Below is a detailed breakdown of each component of the strategy.
🔶 1. True Range Calculation with Enhanced Volatility Detection
The True Range (TR) measures market volatility by considering the most significant price movements. The enhanced TR is calculated as:
TR = Max
Where:
High and Low are the current bar's high and low prices.
Previous Close is the closing price of the previous bar.
Abs denotes the absolute value.
Max selects the maximum value among the three calculations.
🔶 2. Momentum Factor Calculation
To make the ATR adaptive, the strategy incorporates a Momentum Factor (MF), which adjusts the ATR based on recent price movements.
Momentum = Close - Close
Stdev_Close = Standard Deviation of Close over n periods
Normalized_Momentum = Momentum / Stdev_Close (if Stdev_Close ≠ 0)
Momentum_Factor = Abs(Normalized_Momentum)
Where:
Close is the current closing price.
n is the momentum_period, a user-defined input (default is 7).
Standard Deviation measures the dispersion of closing prices over n periods.
Abs ensures the momentum factor is always positive.
🔶 3. Adaptive ATR Calculation
The Adaptive ATR (AATR) adjusts the traditional ATR based on the Momentum Factor, making it more responsive during volatile periods and smoother during consolidation.
Short_ATR = SMA(True Range, short_period)
Long_ATR = SMA(True Range, long_period)
Adaptive_ATR = /
Where:
SMA is the Simple Moving Average.
short_period and long_period are user-defined inputs (defaults are 3 and 7, respectively).
🔶 4. Trend Strength Calculation
The strategy quantifies the strength of the trend to filter out weak signals.
Price_Change = Close - Close
ATR_Multiple = Price_Change / Adaptive_ATR (if Adaptive_ATR ≠ 0)
Trend_Strength = SMA(ATR_Multiple, n)
🔶 5. Trend Signal Determination
If (Short_MA > Long_MA) AND (Trend_Strength > Trend_Strength_Threshold):
Trend_Signal = 1 (Strong Uptrend)
Elif (Short_MA < Long_MA) AND (Trend_Strength < -Trend_Strength_Threshold):
Trend_Signal = -1 (Strong Downtrend)
Else:
Trend_Signal = 0 (No Clear Trend)
🔶 6. Trend Confirmation with Price Action
Adaptive_ATR_SMA = SMA(Adaptive_ATR, atr_sma_period)
If (Trend_Signal == 1) AND (Close > Short_MA) AND (Adaptive_ATR > Adaptive_ATR_SMA):
Trend_Confirmed = True
Elif (Trend_Signal == -1) AND (Close < Short_MA) AND (Adaptive_ATR > Adaptive_ATR_SMA):
Trend_Confirmed = True
Else:
Trend_Confirmed = False
Local Performance
🔶 7. Multi-Step Take-Profit Mechanism
The strategy employs a 7-step take-profit system
█ Trade Direction
The SuperATR 7-Step Profit Strategy is designed to work in both long and short market conditions. By identifying strong uptrends and downtrends, it allows traders to capitalize on price movements in either direction.
Long Trades: Initiated when the market shows strong upward momentum and the trend is confirmed.
Short Trades: Initiated when the market exhibits strong downward momentum and the trend is confirmed.
█ Usage
To implement the SuperATR 7-Step Profit Strategy:
1. Configure the Strategy Parameters:
- Adjust the short_period, long_period, and momentum_period to match the desired sensitivity.
- Set the trend_strength_threshold to control how strong a trend must be before acting.
2. Set Up the Multi-Step Take-Profit Levels:
- Define ATR multipliers and fixed percentage levels according to risk tolerance and profit goals.
- Specify the percentage of the position to close at each level.
3. Apply the Strategy to a Chart:
- Use the strategy on instruments and timeframes where it has been tested and optimized.
- Monitor the positions and adjust parameters as needed based on performance.
4. Backtest and Optimize:
- Utilize TradingView's backtesting features to evaluate historical performance.
- Adjust the default settings to optimize for different market conditions.
█ Default Settings
Understanding default settings is crucial for optimal performance.
Short Period (3): Affects the responsiveness of the short-term MA.
Effect: Lower values increase sensitivity but may produce more false signals.
Long Period (7): Determines the trend baseline.
Effect: Higher values reduce noise but may delay signals.
Momentum Period (7): Influences adaptive ATR and trend strength.
Effect: Shorter periods react quicker to price changes.
Trend Strength Threshold (0.5): Filters out weaker trends.
Effect: Higher thresholds yield fewer but stronger signals.
ATR Multipliers: Set distances for ATR-based exits.
Effect: Larger multipliers aim for bigger moves but may reduce hit rate.
Fixed TP Levels (%): Control profit-taking on smaller moves.
Effect: Adjusting these levels affects how quickly profits are realized.
Exit Percentages: Determine how much of the position is closed at each TP level.
Effect: Higher percentages reduce exposure faster, affecting risk and reward.
Adjusting these variables allows you to tailor the strategy to different market conditions and personal risk preferences.
By integrating adaptive indicators and a multi-tiered exit strategy, the SuperATR 7-Step Profit Strategy offers a versatile tool for traders seeking to navigate varying market conditions effectively. Understanding and adjusting the key parameters enables traders to harness the full potential of this strategy.
PDF Smoothed Moving Average [BackQuant]PDF Smoothed Moving Average
Introducing BackQuant’s PDF Smoothed Moving Average (PDF-MA) — an innovative trading indicator that applies Probability Density Function (PDF) weighting to moving averages, creating a unique, trend-following tool that offers adaptive smoothing to price movements. This advanced indicator gives traders an edge by blending PDF-weighted values with conventional moving averages, helping to capture trend shifts with enhanced clarity.
Core Concept: Probability Density Function (PDF) Smoothing
The Probability Density Function (PDF) provides a mathematical approach to applying adaptive weighting to data points based on a specified variance and mean. In the PDF-MA indicator, the PDF function is used to weight price data, adding a layer of probabilistic smoothing that enhances the detection of trend strength while reducing noise.
The PDF weights are controlled by two key parameters:
Variance: Determines the spread of the weights, where higher values spread out the weighting effect, providing broader smoothing.
Mean : Centers the weights around a particular price value, influencing the trend’s directionality and sensitivity.
These PDF weights are applied to each price point over the chosen period, creating an adaptive and smooth moving average that more closely reflects the underlying price trend.
Blending PDF with Standard Moving Averages
To further improve the PDF-MA, this indicator combines the PDF-weighted average with a traditional moving average, selected by the user as either an Exponential Moving Average (EMA) or Simple Moving Average (SMA). This blended approach leverages the strengths of each method: the responsiveness of PDF smoothing and the robustness of conventional moving averages.
Smoothing Method: Traders can choose between EMA and SMA for the additional moving average layer. The EMA is more responsive to recent prices, while the SMA provides a consistent average across the selected period.
Smoothing Period: Controls the length of the lookback period, affecting how sensitive the average is to price changes.
The result is a PDF-MA that provides a reliable trend line, reflecting both the PDF weighting and traditional moving average values, ideal for use in trend-following and momentum-based strategies.
Trend Detection and Candle Coloring
The PDF-MA includes a built-in trend detection feature that dynamically colors candles based on the direction of the smoothed moving average:
Uptrend: When the PDF-MA value is increasing, the trend is considered bullish, and candles are colored green, indicating potential buying conditions.
Downtrend: When the PDF-MA value is decreasing, the trend is considered bearish, and candles are colored red, signaling potential selling or shorting conditions.
These color-coded candles provide a quick visual reference for the trend direction, helping traders make real-time decisions based on the current market trend.
Customization and Visualization Options
This indicator offers a range of customization options, allowing traders to tailor it to their specific preferences and trading environment:
Price Source : Choose the price data for calculation, with options like close, open, high, low, or HLC3.
Variance and Mean : Fine-tune the PDF weighting parameters to control the indicator’s sensitivity and responsiveness to price data.
Smoothing Method : Select either EMA or SMA to customize the conventional moving average layer used in conjunction with the PDF.
Smoothing Period : Set the lookback period for the moving average, with a longer period providing more stability and a shorter period offering greater sensitivity.
Candle Coloring : Enable or disable candle coloring based on trend direction, providing additional clarity in identifying bullish and bearish phases.
Trading Applications
The PDF Smoothed Moving Average can be applied across various trading strategies and timeframes:
Trend Following : By smoothing price data with PDF weighting, this indicator helps traders identify long-term trends while filtering out short-term noise.
Reversal Trading : The PDF-MA’s trend coloring feature can help pinpoint potential reversal points by showing shifts in the trend direction, allowing traders to enter or exit positions at optimal moments.
Swing Trading : The PDF-MA provides a clear trend line that swing traders can use to capture intermediate price moves, following the trend direction until it shifts.
Final Thoughts
The PDF Smoothed Moving Average is a highly adaptable indicator that combines probabilistic smoothing with traditional moving averages, providing a nuanced view of market trends. By integrating PDF-based weighting with the flexibility of EMA or SMA smoothing, this indicator offers traders an advanced tool for trend analysis that adapts to changing market conditions with reduced lag and increased accuracy.
Whether you’re trading trends, reversals, or swings, the PDF-MA offers valuable insights into the direction and strength of price movements, making it a versatile addition to any trading strategy.
FS Scorpion TailKey Features & Components:
1. Custom Date & Chart-Based Controls
The software allows users to define whether they want signals to start on a specific date (useSpecificDate) or base calculations on the visible chart’s range (useRelativeScreenSumLeft and useRelativeScreenSumRight).
Users can input the number of stocks to buy/sell per signal and decide whether to sell only for profit.
2. Technical Indicators Used
EMA (Exponential Moving Average): Users can define the length of the EMA and specify if buy/sell signals should occur when the EMA is rising or falling.
MACD (Moving Average Convergence Divergence): MACD crossovers, slopes of the MACD line, signal line, and histogram are used for generating buy/sell signals.
ATR (Average True Range): Signals are generated based on rising or falling ATR.
Aroon Indicator: Buy and sell signals are based on the behavior of the Aroon upper and lower lines.
RSI (Relative Strength Index): Tracks whether the RSI and its moving average are rising or falling to generate signals.
Bollinger Bands: Buy/sell signals depend on the basis, upper, and lower band behavior (rising or falling).
3. Signal Detection
The software creates arrays for each indicator to store conditions for buy/sell signals.
The allTrue() function checks whether all conditions for buy/sell signals are true, ensuring that only valid signals are plotted.
Signals are differentiated between buy-only, sell-only, and both buy and sell (dual signal).
4. Visual Indicators
Vertical Lines: When buy, sell, or dual signals are detected, vertical lines are drawn at the corresponding bar with configurable colors (green for buy, red for sell, silver for dual).
Buy/Sell Labels: Visual labels are plotted directly on the chart to denote buy or sell signals, allowing for clear interpretation of the strategy.
5. Cash Flow & Metrics Display
The software maintains an internal ledger of how many stocks are bought/sold, their prices, and whether a profit is being made.
A table is displayed at the bottom right of the chart, showing:
Initial investment
Current stocks owned
Last buy price
Market stake
Net profit
The table background turns green for profit and red for loss.
6. Dynamic Decision Making
Buy Condition: If a valid buy signal is generated, the software decrements the cash balance and adds stocks to the inventory.
Sell Condition: If the sell signal is valid (and meets the profit requirement), stocks are sold, and cash is incremented.
A fallback check ensures the sell logic prevents selling more stocks than are available and adjusts stock holding appropriately (e.g., sell half).
Customization and Usage
Indicator Adjustments: The user can choose which indicators to activate (e.g., EMA, MACD, RSI) via input controls. Each indicator has specific customizable parameters such as lengths, slopes, and conditions.
Signal Flexibility: The user can adjust conditions for buying and selling based on various technical indicators, which adds flexibility in implementing trading strategies. For example, users may require the RSI to be higher than its moving average or trigger sales only when MACD crosses under the signal line.
Profit Sensitivity: The software allows the option to sell only when a profit is assured by checking if the current price is higher than the last buy price.
Summary of Usage:
Indicator Selection: Enable or disable technical indicators like EMA, MACD, RSI, Aroon, ATR, and Bollinger Bands to fit your trading strategy.
Custom Date/Chart Settings: Choose whether to calculate based on specific time ranges or visible portions of the chart.
Dynamic Signal Plotting: Once buy or sell conditions are met, the software will visually plot signals on your chart, giving clear entry and exit points.
Investment Tracking: Real-time tracking of stock quantities, investments, and profit ensures a clear view of your trading performance.
Backtesting: Use this software for backtesting your strategy by analyzing how buy and sell signals would have performed historically based on the chosen indicators.
Conclusion
The FS Scorpion Tail software is a robust and flexible trading tool, allowing traders to develop custom strategies based on multiple well-known technical indicators. Its visual aid, coupled with real-time investment tracking, makes it valuable for systematic traders looking to automate or refine their trading approach.
Mean Trend OscillatorMean Trend Oscillator
The Mean Trend Oscillator offers an original approach to trend analysis by integrating multiple technical indicators, using statistic to get a probable signal, and dynamically adapting to market volatility.
This tool aggregates signals from four popular indicators—Relative Strength Index (RSI), Simple Moving Average (SMA), Exponential Moving Average (EMA), and Relative Moving Average (RMA)—and adjusts thresholds using the Average True Range (ATR). By using this, we can use Statistics to aggregate or take the average of each indicators signal. Mathematically, Taking an average of these indicators gives us a better probability on entering a trending state.
By consolidating these distinct perspectives, the Mean Trend Oscillator provides a comprehensive view of market direction, helping traders make informed decisions based on a broad, data-driven trend assessment. Traders can use this indicator to enter long spot or leveraged positions. The Mean Trend Oscillator is intended to be use in long term trending markets. Scalping MUST NOT be used with this indicator. (This indicator will give false signals when the Timeframe is too low. The best intended use for high-quality signals are longer timeframes).
The current price of a beginning trend series may tell us something about the next move. Thus, the Mean Trend Oscillator allows us to spot a high probability trending market and potentially exploit this information enter long or shorts strategy. (again, this indicator will give false signals when the Timeframe is too low. The best intended use for high-quality signals are longer timeframes).
Concept and Calculation and Inputs
The Mean Trend Oscillator calculates a “net trend” score as follows:
RSI evaluates market momentum, identifying overbought and oversold conditions, essential for confirming trend direction.
SMA, EMA, and RMA introduce varied smoothing methods to capture short- to medium-term trends, balancing quick price changes with smoothed averages.
ATR-Enhanced Thresholds: ATR is used as a dynamic multiplier, adjusting each indicator’s thresholds to current volatility levels, which helps reduce noise in low-volatility conditions and emphasizes significant signals when volatility spikes.
Length could be used to adjust how quickly each indicator can more or how slower each indicator can be.
Time Coherency for Inputs: Each indicator must be calculated where each signal is relatively around the same area.
For example:
Simply:
SMA, RMA, EMA, and RSI enters long around each intended trend period. Doesn't have to be perfect, but the indicators all enter long around there.
Each indicator contributes a score (+1 for bullish and -1 for bearish), and these scores are averaged to generate the final trend score:
A positive score, shown as a green line, suggests bullish conditions.
A negative score, indicated by a red line, signifies bearish conditions.
Thus, giving us a signal to long or short.
How to Use the Mean Trend Oscillator
This indicator’s output is straightforward and can fit into various trading strategies:
Bullish Signal: A green line shows that the trend is bullish, based on a positive average score across the indicators, signaling a consideration of longing an asset.
Bearish Signal: A red line indicates bearish conditions, with an overall negative trend score, signaling a consideration to shorting an asset.
By aggregating these indicators, the Mean Trend Oscillator helps traders identify strong trends while filtering out minor fluctuations, making it a versatile tool for both short- and long-term analysis. This multi-layered, adaptive approach to trend detection sets it apart from traditional single-indicator trend tools.
Alpine Predictive BandsAlpine Predictive Bands - ADX & Trend Projection is an advanced indicator crafted to estimate potential price zones and trend strength by integrating dynamic support/resistance bands, ADX-based confidence scoring, and linear regression-based price projections. Designed for adaptive trend analysis, this tool combines multi-timeframe ADX insights, volume metrics, and trend alignment for improved confidence in trend direction and reliability.
Key Calculations and Components:
Linear Regression for Price Projection:
Purpose: Provides a trend-based projection line to illustrate potential price direction.
Calculation: The Linear Regression Centerline (LRC) is calculated over a user-defined lookbackPeriod. The slope, representing the rate of price movement, is extended forward using predictionLength. This projected path only appears when the confidence score is 70% or higher, revealing a white dotted line to highlight high-confidence trends.
Adaptive Prediction Bands:
Purpose: ATR-based bands offer dynamic support/resistance zones by adjusting to volatility.
Calculation: Bands are calculated using the Average True Range (ATR) over the lookbackPeriod, multiplied by a volatilityMultiplier to adjust the width. These shaded bands expand during higher volatility, guiding traders in identifying flexible support/resistance zones.
Confidence Score (ADX, Volume, and Trend Alignment):
Purpose: Reflects the reliability of trend projections by combining ADX, volume status, and EMA alignment across multiple timeframes.
ADX Component: ADX values from the current timeframe and two higher timeframes assess trend strength on a broader scale. Strong ADX readings across timeframes boost the confidence score.
Volume Component: Volume strength is marked as “High” or “Low” based on a moving average, signaling trend participation.
Trend Alignment: EMA alignment across timeframes indicates “Bullish” or “Bearish” trends, confirming overall trend direction.
Calculation: ADX, volume, and trend alignment integrate to produce a confidence score from 0% to 100%. When the score exceeds 70%, the white projection line is activated, underscoring high-confidence trend continuations.
User Guide
Projection Line: The white dotted line, which appears only when the confidence score is 70% or higher, highlights a high-confidence trend.
Prediction Bands: Adaptive bands provide potential support/resistance zones, expanding with market volatility to help traders visualize price ranges.
Confidence Score: A high score indicates a stronger, more reliable trend and can support trend-following strategies.
Settings
Prediction Length: Determines the forward length of the projection.
Lookback Period: Sets the data range for calculating regression and ATR.
Volatility Multiplier: Adjusts the width of bands to match volatility levels.
Disclaimer: This indicator is for educational purposes and does not guarantee future price outcomes. Additional analysis is recommended, as trading carries inherent risks.
Valid Pullbacks and Trend by kpt. GonzoThis script helps identify valid pullbacks. Based on the marked pullbacks, it can draw both internal and external structure trendlines.
A pullback is marked with a small triangle above or below the candle that created the local high or low.
A new local high is marked with a red triangle above the candle if at least one subsequent candle has a low lower than the low of the candle that created the new local high.
A new local low is marked with a green triangle below the candle if at least one subsequent candle has a high higher than the high of the candle that created the new local low.
Based on the marked local highs and lows, the internal structure trendline is created by simply connecting all highs and lows with a line.
The external structure is drawn in a similar way, but only highs and lows that have broken the previous structure are connected. This helps focus on important pivots and better understand the market structure.
Weekly RSI Buy/Sell SignalsWeekly RSI Buy/Sell Signal Indicator
This indicator is designed to help traders identify high-probability buy and sell opportunities on the weekly chart by using the Relative Strength Index (RSI). By utilizing weekly RSI values, this indicator ensures signals align with broader market trends, providing a clearer view of potential price reversals and continuation.
How It Works:
Weekly RSI Calculation: This script calculates the RSI using a 14-period setting, focusing on the weekly timeframe regardless of the user’s current chart view. The weekly RSI is derived using request.security, allowing for consistent signals even on intraday charts.
Signal Conditions:
Buy Signal: A buy signal appears when the RSI crosses above the oversold threshold of 30, suggesting that price may be gaining momentum after a potential bottom.
Sell Signal: A sell signal triggers when the RSI crosses below the overbought threshold of 70, indicating a possible momentum shift downwards.
Visual Cues:
Buy/Sell Markers: Clear green "BUY" and red "SELL" markers are displayed on the chart when buy or sell conditions are met, making it easy to identify entry and exit points.
RSI Line and Thresholds: The weekly RSI value is plotted in real time with color-coded horizontal lines at 30 (oversold) and 70 (overbought), providing a visual reference for key levels.
This indicator is ideal for traders looking for reliable, trend-based signals on higher timeframes and can be a helpful tool for filtering out shorter-term market noise.
DSL Strategy [DailyPanda]
Overview
The DSL Strategy by DailyPanda is a trading strategy that synergistically combines the idea from indicators to create a more robust and reliable trading tool. By integrating these indicators, the strategy enhances signal accuracy and provides traders with a comprehensive view of market trends and momentum shifts. This combination allows for better entry and exit points, improved risk management, and adaptability to various market conditions.
Combining ideas from indicators adds value by:
Enhancing Signal Confirmation : The strategy requires alignment between trend and momentum before generating trade signals, reducing false entries.
Improving Accuracy : By integrating price action with momentum analysis, the strategy captures more reliable trading opportunities.
Providing Comprehensive Market Insight : The combination offers a better perspective on the market, considering both the direction (trend) and the strength (momentum) of price movements.
How the Components Work Together
1. Trend Identification with DSL Indicator
Dynamic Signal Lines : Calculates upper and lower DSL lines based on a moving average (SMA) and dynamic thresholds derived from recent highs and lows with a specified offset. These lines adapt to market conditions, providing real-time trend insights.
ATR-Based Bands : Adds bands around the DSL lines using the Average True Range (ATR) multiplied by a width factor. These bands account for market volatility and help identify potential stop-loss levels.
Trend Confirmation : The relationship between the price, DSL lines, and bands determines the current trend. For example, if the price consistently stays above the upper DSL line, it indicates a bullish trend.
2. Momentum Analysis
RSI Calculation : Computes the RSI over a specified period to measure the speed and change of price movements.
Zero-Lag EMA (ZLEMA) : Applies a ZLEMA to the RSI to minimize lag and produce a more responsive oscillator.
DSL Application on Oscillator : Implements the DSL concept on the oscillator by calculating dynamic upper and lower levels. This helps identify overbought or oversold conditions more accurately.
Signal Generation : Detects crossovers between the oscillator and its DSL lines. A crossover above the lower DSL line signals potential bullish momentum, while a crossover below the upper DSL line signals potential bearish momentum.
3. Integrated Signal Filtering
Confluence Requirement : A trade signal is generated only when both the DSL indicator and oscillator agree. For instance, a long entry requires both an uptrend confirmation from the DSL indicator and a bullish momentum signal from the oscillator.
Risk Management Integration : The strategy uses the DSL indicator's bands for setting stop-loss levels and calculates take-profit levels based on a user-defined risk-reward ratio. This ensures that every trade has a predefined risk management plan.
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Originality and Value Added to the Community
Unique Synergy : While both indicators are available individually, this strategy is original in how it combines them to enhance their strengths and mitigate their weaknesses, offering a novel approach not present in existing scripts.
Enhanced Reliability : By requiring confirmation from both trend and momentum indicators, the strategy reduces false signals and increases the likelihood of successful trades.
Versatility : The customizable parameters allow traders to adapt the strategy to different instruments, timeframes, and trading styles, making it a valuable tool for a wide range of trading scenarios.
Educational Contribution : The script demonstrates an effective method of combining indicators for improved trading performance, providing insights that other traders can learn from and apply to their own strategies.
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How to Use the Strategy
Adding the Strategy to Your Chart
Apply the DSL Strategy to your desired trading instrument and timeframe on TradingView.
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Configuring Parameters
DSL Indicator Settings :
Length (len) : Adjusts the sensitivity of the DSL lines (default is 34).
Offset : Determines the look-back period for threshold calculations (default is 30).
Bands Width (width) : Changes the distance of the ATR-based bands from the DSL lines (default is 1).
DSL-BELUGA Oscillator Settings :
Beluga Length (len_beluga) : Sets the period for the RSI calculation in the oscillator (default is 10).
DSL Lines Mode (dsl_mode) : Chooses between "Fast" (more responsive) and "Slow" (smoother) modes for the oscillator's DSL lines.
Risk Management :
Risk Reward (risk_reward) : Defines your desired risk-reward ratio for calculating take-profit levels (default is 1.5).
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Interpreting Signals
Long Entry Conditions :
Trend Confirmation : Price is above the upper DSL line and the upper DSL band (dsl_up1 > dsl_dn).
Price Behavior : The last three candles have both their opens and closes above the upper DSL line.
Momentum Signal : The DSL-BELUGA oscillator crosses above its lower DSL line (up_signal), indicating bullish momentum.
Short Entry Conditions :
Trend Confirmation : Price is below the lower DSL line and the lower DSL band (dsl_dn < dsl_up1).
Price Behavior : The last three candles have both their opens and closes below the lower DSL band.
Momentum Signal : The DSL-BELUGA oscillator crosses below its upper DSL line (dn_signal), indicating bearish momentum.
Exit Conditions :
Stop-Loss : Automatically set at the DSL indicator's band level (upper band for longs, lower band for shorts).
Take-Profit : Calculated based on the risk-reward ratio and the initial risk determined by the stop-loss distance.
Visual Aids
Signal Arrows : Upward green arrows for long entries and downward blue arrows for short entries appear on the chart when conditions are met.
Stop-Loss and Take-Profit Lines : Red and green lines display the calculated stop-loss and take-profit levels for active trades.
Background Highlighting : The chart background subtly changes color to indicate when a signal has been generated.
Backtesting and Optimization
Use TradingView's strategy tester to backtest the strategy over historical data.
Adjust parameters to optimize performance for different instruments or market conditions.
Regularly review backtesting results to ensure the strategy remains effective.
RVI Crossover Strategy[Kopottaja]Overview of the RVI Crossover Strategy
Strategy Name: RVI Crossover Strategy
Purpose: The RVI Crossover Strategy is based on the crossover signals between the Relative Vigor Index (RVI) and its moving average signal line. This strategy aims to identify potential buy and sell signals by evaluating the market’s directional trend.
Key Indicator Features
Relative Vigor Index (RVI): This indicator measures the momentum of price changes over a specified period and helps identify the market’s current trend. The RVI is based on the idea that prices generally close higher than they open in an uptrend (and lower in a downtrend). The RVI helps provide an indication of the strength and direction of a trend.
Signal Line: A moving average (e.g., SMA) is applied to the RVI values, creating a "signal line." When the RVI crosses above or below this line, it signals a potential trading opportunity.
Calculations and Settings
Calculating the RVI: The RVI is calculated by comparing the difference between the close and open prices to the difference between high and low prices. This provides information about the direction and momentum of price movement:
RVI= Sum(SWMA(high−low))Sum(SWMA(close−open))
where SWMA is a smoothed weighted moving average over a specified period.
Signal Line Calculation: The RVI value is smoothed by applying a simple moving average (SMA) to create the signal line. This signal line helps filter crossover signals for improved accuracy.
Buy and Sell Conditions: Buy and sell conditions are identified based on crossovers between the RVI and its signal line.
Buy Signal: A buy condition is triggered when the RVI crosses above the signal line, provided that the "Bearish" condition (trend confirmation) is met.
Sell Signal: A sell condition occurs when the RVI crosses below the signal line, alongside the "Bullish" trend confirmation.
Volume-Weighted Moving Averages (VWMA): VWMA indicators are used to assess price-volume relationships over different timeframes:
Fast VWMA: A short-period volume-weighted moving average.
Slow VWMA: A longer-period volume-weighted moving average. These values are used to strengthen the buy and sell conditions by confirming trend directions (Bullish or Bearish).
Disclaimer: This is an educational and informational tool. Past performance is not indicative of future results. Always backtest before using in live markets
Standard and Camarilla pivotsHi guys, I would like too introduce to all of you my script. As the name already tell you what this script is all about. It's about pivot points.
You may ask, Tradingview already have a script for pivot points, why would I need another script?
here is the answer: This script allow you to add more than one type of pivot, sounds good right?
But there's more: You can see not just one timeframe pivots, you can see many timeframe pivots, nice huh?
let dive into it to know a bit more.
In this script you can see daily pivots include Standard pivots as R1, R2, R3 and Camarilla pivots as cR1, cR2, cR3, and I you different color for different pivots, so you don't confuse between those two.
You can see weekly pivots the same as daily pivots only has letter "w" in front of it, for examples: "wR1, wR2, wcR1, wcR2" ,nice right?
What's about month level: yes, you can see monthly pivots too, and it start with "m".
Along with pivots points above, you also can see daily open, previous day close, previous high,.., for instances: daily open as "O", previous day open as "PDO",
You are able to see previous week level, previous month levels.
have fun.
I dont wanna lock this script because open-source script help me learn how to code pine script, so that's why I keep it open. Thank to all the coders out there that shared everything they have for us to learn.
Multi-Timeframe RangeThe Multi-Timeframe Range Indicator is designed for traders looking to monitor key price levels across various timeframes (Daily, Weekly, Monthly, Quarterly, and Yearly) directly on their charts. This indicator draws boxes and mid-lines for each timeframe’s high, low, and midpoint, enabling users to visualize price ranges and assess potential areas of support and resistance more effectively.
Features:
Dynamic Range Boxes: Displays the high, low, and midpoint levels for each specified timeframe, with customizable colors for easy differentiation.
Visual Cues for Monday’s Levels: Highlights Monday’s high, low, and midpoint levels each week to support intraday trading setups and weekly trend analysis.
Multi-Timeframe Flexibility: Easily toggle between timeframes to view ranges from daily to yearly, making this indicator suitable for both short-term and long-term traders.
Ideal Use Cases:
Identify key support and resistance zones based on multiple timeframes.
Assess weekly and monthly trends using the Monday range levels.
Gain insights into market structure across various timeframes.
Rolling ATR Bands | Flux Charts💎 GENERAL OVERVIEW
Introducing the Rolling ATR Bands indicator! This indicator overlays adaptive bands around the price, using the Average True Range (ATR) to define dynamic support and resistance levels. The Rolling ATR Bands are color-coded to visually indicate potential trend strength, shifting between bearish, neutral, and bullish colors. This tool can help traders interpret price volatility, as well as identify probable trend changes, continuations, or reversals. For more information about the process, check the "HOW DOES IT WORK ?" section.
Features of the new Rolling ATR Bands:
ATR Bands With Customizable ATR Length & Multiplier
Smooth Trend Strength With Adjustable Smoothing Options
Color-coded bands Representing Bearish, Neutral, or Bullish Trends
Alerts for Retests & Breaks
Customizable Visuals
📌 HOW DOES IT WORK?
The Rolling ATR Bands indicator calculates the ATR based on the specified length and multiplier to form upper and lower bands around the price. These bands adapt with market volatility, widening during high volatility and contracting during lower volatility periods.
In addition, the indicator calculates a "trend strength" score by combining an interpolated RSI, Supertrend, and EMA crossover. This score is smoothed with a customizable length, and a color gradient is applied to visually denote the strength of bearish, neutral, or bullish conditions.
Here's how to interpret the bands:
Upper Band: Acts as dynamic resistance; when price approaches or touches it, this often suggests potential overbought conditions.
Lower Band: Acts as dynamic support; touching or nearing this band might indicate potential oversold conditions.
Color Shifts: Color changes indicate shifts in trend direction. For example, a green color suggests a bullish trend, while red hints at bearish tendencies.
🚩 UNIQUENESS
What sets the Rolling ATR Bands apart is the combined use of interpolated RSI, Supertrend, and EMA cross values, creating a weighted trend strength score. This integration allows for nuanced, color-coded visual cues that respond quickly to trend changes without excessive noise, offering traders an intuitive view of both trend direction and potential momentum. You can also set up alerts for retest & alerts for upper and lower bands to get informed of potential movements.
⚙️ SETTINGS
1. General Configuration
ATR Length : Controls the ATR calculation length for the bands.
Smoothing: Adjusts the trend strength smoothing to control sensitivity to trend changes.
ATR Multiplier : Sets the width of the bands by multiplying the ATR value.
Trend Smoothing : Higher settings will result in longer periods of time required for trend to change direction from bullish to bearish and vice versa.
FibExtender [tradeviZion]FibExtender : A Guide to Identifying Resistance with Fibonacci Levels
Introduction
Fibonacci levels are essential tools in technical analysis, helping traders identify potential resistance and support zones in trending markets. FibExtender is designed to make this analysis accessible to traders at all levels, especially beginners, by automating the process of plotting Fibonacci extensions. With FibExtender, you can visualize potential resistance levels quickly, empowering you to make more informed trading decisions without manually identifying every pivot point. In this article, we’ll explore how FibExtender works, guide you step-by-step in using it, and share insights for both beginner and advanced users.
What is FibExtender ?
FibExtender is an advanced tool that automates Fibonacci extension plotting based on significant pivot points in price movements. Fibonacci extensions are percentages based on prior price swings, often used to forecast potential resistance zones where price might reverse or consolidate. By automatically marking these Fibonacci levels on your chart, FibExtender saves time and reduces the complexity of technical analysis, especially for users unfamiliar with calculating and plotting these levels manually.
FibExtender not only identifies Fibonacci levels but also provides a customizable framework where you can adjust anchor points, colors, and level visibility to suit your trading strategy. This customization allows traders to tailor the indicator to fit different market conditions and personal preferences.
Key Features of FibExtender
FibExtender offers several features to make Fibonacci level analysis easier and more effective. Here are some highlights:
Automated Fibonacci Level Identification : The script automatically detects recent swing lows and pivot points to anchor Fibonacci extensions, allowing you to view potential resistance levels with minimal effort.
Customizable Fibonacci Levels : Users can adjust the specific Fibonacci levels they want to display (e.g., 0.618, 1.0, 1.618), enabling a more focused analysis based on preferred ratios. Each level can be color-coded for visual clarity.
Dual Anchor Points : FibExtender allows you to choose between anchoring levels from either the last pivot low or a recent swing low, depending on your preference. This flexibility helps in aligning Fibonacci levels with key market structures.
Transparency and Visual Hierarchy : FibExtender automatically adjusts the transparency of levels based on their "sequence age," creating a subtle visual hierarchy. Older levels appear slightly faded, helping you focus on more recent, potentially impactful levels.
Connection Lines for Context : FibExtender draws connecting lines from recent lows to pivot highs, allowing users to visualize the price movements that generated each Fibonacci extension level.
Step-by-Step Guide for Beginners
Let’s walk through how to use the FibExtender script on a TradingView chart. This guide will ensure that you’re able to set it up and interpret the key information displayed by the indicator.
Step 1: Adding FibExtender to Your Chart
Open your TradingView chart and select the asset you wish to analyze.
Search for “FibExtender ” in the Indicators section.
Click to add the indicator to your chart, and it will automatically plot Fibonacci levels based on recent pivot points.
Step 2: Customizing Fibonacci Levels
Adjust Levels : Under the "Fibonacci Settings" tab, you can enable or disable specific levels, such as 0.618, 1.0, or 1.618. You can also change the color for each level to improve visibility.
Set Anchor Points : Choose between "Last Pivot Low" and "Recent Swing Low" as your Fibonacci anchor point. If you want a broader view, choose "Recent Swing Low"; if you prefer tighter levels, "Last Pivot Low" may be more suitable.
Fib Line Length : Modify the line length for Fibonacci levels to make them more visible on your chart.
Step 3: Spotting Visual Clusters (Manual Analysis)
Identify Potential Resistance Clusters : Look for areas on your chart where multiple Fibonacci levels appear close together. For example, if you see 1.0, 1.272, and 1.618 levels clustered within a small price range, this may indicate a stronger resistance zone.
Why Clusters Matter : Visual clusters often signify areas where traders expect heightened price reaction. When levels are close, it suggests that resistance may be reinforced by multiple significant ratios, making it harder for price to break through. Use these clusters to anticipate potential pullbacks or consolidation areas.
Step 4: Observing the Price Action Around Fibonacci Levels
As price approaches these identified levels, watch for any slowing momentum or reversal patterns, such as doji candles or bearish engulfing formations, that might confirm resistance.
Adjust Strategy Based on Resistance : If price hesitates or reverses at a clustered resistance zone, it may be a signal to secure profits or tighten stops on a long position.
Advanced Insights (for Intermediate to Advanced Users)
For users interested in the technical workings of FibExtender, this section provides insights into how the indicator functions on a code level.
Pivot Point and Swing Detection
FibExtender uses a pivot-high and pivot-low detection function to identify significant price points. The upFractal and dnFractal variables detect these levels based on recent highs and lows, creating the basis for Fibonacci extension calculations. Here’s an example of the code used for this detection:
// Fractal Calculations
upFractal = ta.pivothigh(n, n)
dnFractal = ta.pivotlow(n, n)
By setting the number of periods for n, users can adjust the sensitivity of the script to recent price swings.
Fibonacci Level Calculation
The following function calculates the Fibonacci levels based on the selected pivot points and applies each level’s specific ratio (e.g., 0.618, 1.618) to project extensions above the recent price swing.
calculateFibExtensions(float startPrice, float highPrice, float retracePrice) =>
fibRange = highPrice - startPrice
var float levels = array.new_float(0)
array.clear(levels)
if array.size(fibLevels) > 0
for i = 0 to array.size(fibLevels) - 1
level = retracePrice + (fibRange * array.get(fibLevels, i))
array.push(levels, level)
levels
This function iterates over each level enabled by the user, calculating extensions by multiplying the price range by the corresponding Fibonacci ratio.
Example Use Case: Identifying Resistance in Microsoft (MSFT)
To better understand how FibExtender highlights resistance, let’s look at Microsoft’s stock chart (MSFT), as shown in the image. The chart displays several Fibonacci levels extending upward from a recent pivot low around $408.17. Here’s how you can interpret the chart:
Clustered Resistance Levels : In the chart, note the grouping of several Fibonacci levels in the range of $450–$470. These levels, particularly when tightly packed, suggest a zone where Microsoft may encounter stronger resistance, as multiple Fibonacci levels signal potential barriers.
Applying Trading Strategies : As price approaches this clustered resistance, traders can watch for weakening momentum. If price begins to stall, it may be wise to lock in profits on long positions or set tighter stop-loss orders.
Observing Momentum Reversals : Look for specific candlestick patterns as price nears these levels, such as bearish engulfing candles or doji patterns. Such patterns can confirm resistance, helping you make informed decisions on whether to exit or manage your position.
Conclusion: Harnessing Fibonacci Extensions with FibExtender
FibExtender is a powerful tool for identifying potential resistance levels without the need for manual Fibonacci calculations. It automates the detection of key swing points and projects Fibonacci extensions, offering traders a straightforward approach to spotting potential resistance zones. For beginners, FibExtender provides a user-friendly gateway to technical analysis, helping you visualize levels where price may react.
For those with a bit more experience, the indicator offers insight into pivot points and Fibonacci calculations, enabling you to fine-tune the analysis for different market conditions. By carefully observing price reactions around clustered levels, users can identify areas of stronger resistance and refine their trade management strategies accordingly.
FibExtender is not just a tool but a framework for disciplined analysis. Using Fibonacci levels for guidance can support your trading decisions, helping you recognize areas where price might struggle or reverse. Integrating FibExtender into your trading strategy can simplify the complexity of Fibonacci extensions and enhance your understanding of resistance dynamics.
Note: Always practice proper risk management and thoroughly test the indicator to ensure it aligns with your trading strategy. Past performance is not indicative of future results.
Trade smarter with TradeVizion—unlock your trading potential today!
Quick scan for drift🙏🏻
ML based algorading is all about detecting any kind of non-randomness & exploiting it, kinda speculative stuff, not my way, but still...
Drift is one of the patterns that can be exploited, because pure random walks & noise aint got no drift.
This is an efficient method to quickly scan tons of timeseries on the go & detect the ones with drift by simply checking wherther drift < -0.5 or drift > 0.5. The code can be further optimized both in general and for specific needs, but I left it like dat for clarity so you can understand how it works in a minute not in an hour
^^ proving 0.5 and -0.5 are natural limits with no need to optimize anything, we simply put the metric on random noise and see it sits in between -0.5 and 0.5
You can simply take this one and never check anything again if you require numerous live scans on the go. The metric is purely geometrical, no connection to stats, TSA, DSA or whatever. I've tested numerous formulas involving other scaling techniques, drift estimates etc (even made a recursive algo that had a great potential to be written about in a paper, but not this time I gues lol), this one has the highest info gain aka info content.
The timeseries filtered by this lil metric can be further analyzed & modelled with more sophisticated tools.
Live Long and Prosper
P.S.: there's no such thing as polynomial trend/drift, it's alwasy linear, these curves you see are just really long cycles
P.S.: does cheer still work on TV? @admin
Volume-Adjusted Schaff Trend Cycle (VASTC)Volume-Adjusted Schaff Trend Cycle (VASTC)
The VASTC is a fairly fast-moving oscillator designed to identify trends early and signal when trends may be nearing their end. While it can be used for both trend-following and mean-reversion strategies , it shines in trend-following setups. It’s particularly useful for catching the start of a trend and giving early warnings that a trend might end soon, making it a valuable addition to a multi-indicator system.
How It Works:
The VASTC adapts the traditional Schaff Trend Cycle by adjusting the MACD component with volume data. This volume-adjusted MACD is run through two stochastic processes , applying exponential smoothing to enhance responsiveness. Volume sensitivity allows the VASTC to adapt dynamically to periods of high or low trading activity, providing more reliable trend signals.
Recommended Use:
Use VASTC in confluence with other indicators to confirm trend entries and exits. It’s best for identifying early trend setups rather than sustaining prolonged trend trades. When used alongside other indicators, especially those with a longer-term outlook or momentum based trend indicators, you’ll gain a clearer signal for potential exits or entries. Always backtest the VASTC on your chosen assets to determine the most effective input parameters, as the defaults may not suit all markets or assets. Different assets behave differently, and adjustments in parameters can improve its ability to analyze the assets you're looking at.
Parameters:
Length : Sets the primary smoothing length.
Fast/Slow Length : Adjust the speed of the volume-adjusted MACD component.
Factor : Controls the final smoothing applied to the STC.
Overbought/Oversold Levels : Defines overbought/oversold levels.
Experiment with these settings to customize the VASTC to your trading strategy and asset.
Disclaimer : This indicator is a tool to complement your trading analysis and should not be used in isolation. Always backtest and use other confluence signals for best results. The assets I looked at when making this indicator are almost certainly different than what you're looking at.
Dema Percentile Standard DeviationDema Percentile Standard Deviation
The Dema Percentile Standard Deviation indicator is a robust tool designed to identify and follow trends in financial markets.
How it works?
This code is straightforward and simple:
The price is smoothed using a DEMA (Double Exponential Moving Average).
Percentiles are then calculated on that DEMA.
When the closing price is below the lower percentile, it signals a potential short.
When the closing price is above the upper percentile and the Standard Deviation of the lower percentile, it signals a potential long.
Settings
Dema/Percentile/SD/EMA Length's: Defines the period over which calculations are made.
Dema Source: The source of the price data used in calculations.
Percentiles: Selects the type of percentile used in calculations (options include 60/40, 60/45, 55/40, 55/45). In these settings, 60 and 55 determine percentile for long signals, while 45 and 40 determine percentile for short signals.
Features
Fully Customizable
Fully Customizable: Customize colors to display for long/short signals.
Display Options: Choose to show long/short signals as a background color, as a line on price action, or as trend momentum in a separate window.
EMA for Confluence: An EMA can be used for early entries/exits for added signal confirmation, but it may introduce noise—use with caution!
Built-in Alerts.
Indicator on Diffrent Assets
INDEX:BTCUSD 1D Chart (6 high 56 27 60/45 14)
CRYPTO:SOLUSD 1D Chart (24 open 31 20 60/40 14)
CRYPTO:RUNEUSD 1D Chart (10 close 56 14 60/40 14)
Remember no indicator would on all assets with default setting so FAFO with setting to get your desired signal.
Trend Levels [ChartPrime]The Trend Levels indicator is designed to identify key trend levels (High, Mid, and Low) during market trends, based on real-time calculations of highest, lowest, and mid-level values over a customizable length. Additionally, the indicator calculates trend strength by measuring the ratio of candles closing above or below the midline, providing a clear view of the ongoing trend dynamics and strength.
⯁ KEY FEATURES AND HOW TO USE
⯌ Trend Shift Signals :
Trend shifts, based on highest and lowest values during input length. When high is == to highest it will change trend to up when low == lowest value it will be shift to down trend.
// Calculate highest and lowest over the specified length
h = ta.highest(length)
l = ta.lowest(length)
// Determine trend direction: if the current high is the highest value, set trend to true
if h == high
trend := true
// If the current low is the lowest value, set trend to false
if l == low
trend := false
Whenever the trend changes direction (from uptrend to downtrend or vice versa), the indicator provides visual cues in the form of arrows. This gives traders clear signals to identify potential trend reversals, enabling them to adjust their strategies accordingly.
⯌ Trend Level Calculation :
As soon as a trend is detected (uptrend or downtrend), the indicator starts calculating the highest, lowest, and mid-level values over the defined period. These levels are plotted on the chart as color-coded lines for easy visualization, allowing traders to quickly spot the key levels within a trend.
⯌ Midline Retests :
Throughout the trend, the mid-level line is often retested, acting as a potential zone for pullbacks or rejections. Traders can use these retests as opportunities for entering positions or confirming trend continuation. The chart shows how price frequently interacts with the midline, helping to identify important reaction levels.
⯌ Trend Strength Calculation :
The indicator measures the trend strength by calculating the delta between the number of candles closing above and below the midline. This percentage-based delta is displayed in real-time, providing a clear indication of whether the trend is gaining or losing momentum.
⯁ USER INPUTS
Length : Specifies the lookback period for calculating the highest and lowest values, which determines the key trend levels.
Candle Counting : Measures the number of candles closing above and below the midline to calculate the trend strength delta.
⯁ CONCLUSION
The Trend Levels indicator provides traders with a powerful tool for visualizing trend dynamics, key levels of support and resistance, and real-time trend strength. By identifying midline retests, tracking candle counts, and providing trend shift signals, this indicator can help traders make well-informed decisions during market trends.
VWAP it GOODWhy: Instead of having 5 individual VWAP indicators, I found it beneficial for one view with a clean display. This VWAP indicator combines the daily, weekly, monthly, quarterly and annual into one color coded view. These colors and styles can be modified by the user.
A user can turn any timeframe off, but this is how I personally like to trade since it helps me better understand potential bounce or pullback areas.
Do your own research for what is best for you.
Percent Trend Change [BigBeluga]The Percent Trend Change indicator is a trend-following tool that provides real-time percentage changes during trends based on entry prices. Using John Ehlers’ Ultimate Smoother filter, it detects trend direction, identifies uptrends and downtrends, and tracks percentage changes during the trend. Additionally, it has a channel that can be toggled on or off, and the width can be customized, adding an extra visual layer to assess trend strength and direction.
NIFTY50:
META:
🔵 IDEA
The Percent Trend Change indicator helps traders visualize the progression of a trend with percentage changes from entry points. It identifies trends and marks percentage changes during the trend, making it easier to assess the strength and sustainability of the ongoing trend.
The use of John Ehlers' Ultimate Smoother filter helps detect trend changes based on consecutive price movements over five bars, making it highly responsive to short- and medium-term trends.
🔵 KEY FEATURES & USAGE
◉ Ultimate Smoother Filter for Trend Detection:
The trend is detected using the Ultimate Smoother filter. If the smoothed line rises five times in a row, the indicator identifies an uptrend. If it falls five times in a row, it identifies a downtrend.
◉ Trend Entry with Price Labels:
The indicator marks trend entry points with up (green) and down (red) triangles. These triangles are labeled with the entry price, allowing traders to track the starting price of the trend.
◉ Percentage Change Labels During Trends:
During a trend, the indicator periodically plots percentage change labels based on the bar period set in the settings.
In an uptrend, positive changes are marked in green, while negative changes are marked in orange. In a downtrend, negative changes are marked in red, while positive changes are marked in orange.
Each plotted percentage label also includes a count of the trend points, allowing traders to track how many times the percentage labels have been plotted during the current trend.
These percentage labels help traders understand how much the price has changed since the trend began and can be used to define potential take-profit targets.
◉ Channel Toggle and Width Customization:
The indicator includes a channel that visually highlights the trend. Traders can toggle this channel on or off, and the width of the channel can be adjusted to match individual preferences. The channel helps visualize the overall trend direction and the range within which price fluctuations occur.
🔵 CUSTOMIZATION
Smoother Length: Adjusts the length of the Ultimate Smoother filter, affecting how responsive the indicator is to price fluctuations.
Bars Percent: Defines how many bars must pass before a new percentage label is plotted. A smaller value plots labels more frequently, while a higher value shows fewer labels.
Channel Width & Show Channel: The width of the channel can be customized, and traders can toggle the channel on or off depending on their preferences.
Color Customization: Traders can customize the colors for the uptrend, downtrend, and percentage labels, providing flexibility in how the indicator is displayed on the chart.
By combining trend-following capabilities with percentage change tracking, the Percent Trend Change indicator offers a powerful tool for identifying trend direction and setting potential take-profit targets. The ability to customize the channel and percentage labels makes it adaptable to various trading strategies.
Advanced VWAP [CryptoSea]The Advanced VWAP is a comprehensive volume-weighted average price (VWAP) tool designed to provide traders with a deeper understanding of market trends through multi-layered VWAP analysis. This indicator is ideal for those who want to track price movements in relation to VWAP bands and detect key market levels with greater precision.
Key Features
Multi-Timeframe VWAP Bands: Includes multiple VWAP bands with different lookback periods (5, 10, 25, and 50), allowing traders to observe short-term and long-term price behavior.
Smoothed Band Options: Offers optional smoothing of VWAP bands to reduce noise and highlight significant trends more clearly.
Dynamic Median Line Display: Plots the median line of the VWAP bands, providing a reference for price movements and potential reversal zones.
VWAP Trend Strength Calculation: Measures the strength of the trend based on the price's position relative to the VWAP bands, normalized between -1 and 1 for easier interpretation.
In the example below we can see the VWAP Forecastd Cloud, which consists of multiple layers of VWAP bands with varying lookback periods, creating a dynamic forecast visualization. The cloud structure represents potential future price ranges by projecting VWAP-based bands outward, with darker areas indicating higher density and overlap of the bands, suggesting stronger support or resistance zones. This approach helps traders anticipate price movement and identify areas of potential consolidation or breakout as the price interacts with different layers of the forecast cloud.
How it Works
VWAP Calculation: Utilizes multiple VWAP calculations based on various lookback periods to capture a broad range of price behaviors. The indicator adapts to different market conditions by switching between short-term and long-term VWAP references.
Smoothing Algorithms: Provides the ability to smooth the VWAP bands using different moving average types (SMA, EMA, SMMA, WMA, VWMA) to suit various trading strategies and reduce market noise.
Trend Strength Analysis: Computes the trend strength based on the price's distance from the VWAP bands, with a value range of -1 to 1. This feature helps traders identify the intensity of uptrends and downtrends.
Alert Conditions: Includes alert options for crossing above or below the smoothed median line, as well as touching the smoothed upper or lower bands, providing timely notifications for potential trading opportunities.
This image below illustrates the use of smoothed VWAP bands, which provide a cleaner representation of the price's relationship to the VWAP by reducing market noise. The smoothed bands create a flowing cloud-like structure, making it easier to observe significant trends and potential reversal points. The circles highlight areas where the price interacts with the smoothed bands, indicating potential key levels for trend continuation or reversal. This setup helps traders focus on meaningful movements and filter out minor fluctuations, improving the identification of strategic entry and exit points based on smoother trend signals.
Application
Strategic Entry and Exit Points: Helps traders identify optimal entry and exit points based on the interaction with VWAP bands and trend strength readings.
Trend Confirmation: Assists in confirming trend strength by analyzing price movements relative to the VWAP bands and detecting significant breaks or touches.
Customized Analysis: Supports a wide range of trading styles by offering adjustable smoothing, band settings, and alert conditions to meet specific trading needs.
The Advanced VWAP by is a valuable addition to any trader's toolkit, offering versatile features to navigate different market scenarios with confidence. Whether used for day trading or longer-term analysis, this tool enhances decision-making by providing a robust view of price behavior relative to VWAP levels.
ARMORE Capital: Support–Resistance Levels v2.0 [Enhanced]Enhanced S/R Levels with Signals
The "Enhanced S R Levels with Signals" indicator is designed to help traders and investors identify key Support and Resistance levels on a price chart. It also includes LONG and SHORT signals to help you see potential buy and sell opportunities. Here's a beginner-friendly breakdown of how it works and how to use it:
How it Works
Support and Resistance Levels:
Support Levels (blue lines) are prices where the stock tends to find a "floor" or buying interest, potentially pushing the price up. These levels are calculated based on the lowest prices over a period, with the sensitivity setting helping adjust the distance between each support level.
Resistance Levels (red lines) are prices where the stock often encounters a "ceiling" or selling interest, which could push the price down. These levels are calculated based on the highest prices over a period, with sensitivity adjusting the distance between each resistance level.
The indicator plots up to five support and five resistance lines, giving you a layered view of price levels where the market may react.
LONG and SHORT Signals:
LONG Signal (green arrow pointing up): When the closing price goes above the closest support level, the indicator shows a LONG signal below the bar, suggesting a potential upward trend.
SHORT Signal (red arrow pointing down): When the closing price goes below the closest resistance level, the indicator shows a SHORT signal above the bar, indicating a potential downward trend.
Background Ribbons:
When a LONG condition is met, a faint green background appears on the chart as a visual cue.
When a SHORT condition is met, a faint red background appears to signal potential bearish pressure.
How to Use It
1. Finding Entry and Exit Points: Use the LONG and SHORT signals as a guide, but remember to consider other factors before making trading decisions. A LONG signal suggests that price may rise, while a SHORT signal indicates potential downside.
2. Support & Resistance Levels: Treat these levels as potential points of interest. Prices often react at support or resistance, so you can look for confirmation (e.g., reversal patterns, volume spikes) around these levels.
3. Experiment with Sensitivity: Adjust the "Sensitivity" setting to see how it changes the spacing of support and resistance levels. Higher sensitivity may show more frequent support/resistance levels, which can be helpful for short-term traders.
DISCLAIMER : This is purely experimental and shouldn't be considered a blatant Buy-Sell Indicator. Please feel free to use it to supplement your research, share it with your friends, iterate and improve upon it, and use it to build better, more powerful tools!
Remember, always combine technical indicators with other analysis methods and manage your risk responsibly. Happy Trading!
Z-Score Weighted Trend System I [InvestorUnknown]The Z-Score Weighted Trend System I is an advanced and experimental trading indicator designed to utilize a combination of slow and fast indicators for a comprehensive analysis of market trends. The system is designed to identify stable trends using slower indicators while capturing rapid market shifts through dynamically weighted fast indicators. The core of this indicator is the dynamic weighting mechanism that utilizes the Z-score of price , allowing the system to respond effectively to significant market movements.
Dynamic Z-Score-Based Weighting System
The Z-Score Weighted Trend System I utilizes the Z-score of price to assign weights dynamically to fast indicators. This mechanism is designed to capture rapid market shifts at potential turning points, providing timely entry and exit signals.
Traders can choose from two primary weighting mechanisms:
Threshold-Based Weighting: The fast indicators are given weight only when the absolute Z-score exceeds a user-defined threshold. Below this threshold, fast indicators have no impact on the final signal.
Continuous Weighting: By setting the threshold to zero, fast indicators always contribute to the final signal, regardless of Z-score levels. However, this increases the likelihood of false signals during ranging or low-volatility markets
// Calculate weight for Fast Indicators based on Z-Score (Slow Indicator weight is kept to 1 for simplicity)
f_zscore_weights(series float z, simple float weight_thre) =>
float fast_weight = na
float slow_weight = na
if weight_thre > 0
if math.abs(z) <= weight_thre
fast_weight := 0
slow_weight := 1
else
fast_weight := 0 + math.sqrt(math.abs(z))
slow_weight := 1
else
fast_weight := 0 + math.sqrt(math.abs(z))
slow_weight := 1
Choice of Z-Score Normalization
Traders have the flexibility to select different Z-score processing methods to better suit their trading preferences:
Raw Z-Score or Moving Average: Traders can opt for either the raw Z-score or a moving average of the Z-score to smooth out fluctuations.
Normalized Z-Score (ranging from -1 to 1) or Z-Score Percentile: The normalized Z-score is simply the raw Z-score divided by 3, while the Z-score percentile utilizes a normal distribution for transformation.
f_zscore_perc(series float zscore_src, simple int zscore_len, simple string zscore_a, simple string zscore_b, simple string ma_type, simple int ma_len) =>
z = (zscore_src - ta.sma(zscore_src, zscore_len)) / ta.stdev(zscore_src, zscore_len)
zscore = switch zscore_a
"Z-Score" => z
"Z-Score MA" => ma_type == "EMA" ? (ta.ema(z, ma_len)) : (ta.sma(z, ma_len))
output = switch zscore_b
"Normalized Z-Score" => (zscore / 3) > 1 ? 1 : (zscore / 3) < -1 ? -1 : (zscore / 3)
"Z-Score Percentile" => (f_percentileFromZScore(zscore) - 0.5) * 2
output
Slow and Fast Indicators
The indicator uses a combination of slow and fast indicators:
Slow Indicators (constant weight) for stable trend identification: DMI (Directional Movement Index), CCI (Commodity Channel Index), Aroon
Fast Indicators (dynamic weight) to identify rapid trend shifts: ZLEMA (Zero-Lag Exponential Moving Average), IIRF (Infinite Impulse Response Filter)
Each indicator is calculated using for-loop methods to provide a smoothed and averaged view of price data over varying lengths, ensuring stability for slow indicators and responsiveness for fast indicators.
Signal Calculation
The final trading signal is determined by a weighted combination of both slow and fast indicators. The slow indicators provide a stable view of the trend, while the fast indicators offer agile responses to rapid market movements. The signal calculation takes into account the dynamic weighting of fast indicators based on the Z-score:
// Calculate Signal (as weighted average)
float sig = math.round(((DMI*slow_w) + (CCI*slow_w) + (Aroon*slow_w) + (ZLEMA*fast_w) + (IIRF*fast_w)) / (3*slow_w + 2*fast_w), 2)
Backtest Mode and Performance Metrics
The indicator features a detailed backtesting mode, allowing traders to compare the effectiveness of their selected settings against a traditional Buy & Hold strategy. The backtesting provides:
Equity calculation based on signals generated by the indicator.
Performance metrics comparing Buy & Hold metrics with the system’s signals, including: Mean, positive, and negative return percentages, Standard deviations, Sharpe, Sortino, and Omega Ratios
// Calculate Performance Metrics
f_PerformanceMetrics(series float base, int Lookback, simple float startDate, bool Annualize = true) =>
// Initialize variables for positive and negative returns
pos_sum = 0.0
neg_sum = 0.0
pos_count = 0
neg_count = 0
returns_sum = 0.0
returns_squared_sum = 0.0
pos_returns_squared_sum = 0.0
neg_returns_squared_sum = 0.0
// Loop through the past 'Lookback' bars to calculate sums and counts
if (time >= startDate)
for i = 0 to Lookback - 1
r = (base - base ) / base
returns_sum += r
returns_squared_sum += r * r
if r > 0
pos_sum += r
pos_count += 1
pos_returns_squared_sum += r * r
if r < 0
neg_sum += r
neg_count += 1
neg_returns_squared_sum += r * r
float export_array = array.new_float(12)
// Calculate means
mean_all = math.round((returns_sum / Lookback), 4)
mean_pos = math.round((pos_count != 0 ? pos_sum / pos_count : na), 4)
mean_neg = math.round((neg_count != 0 ? neg_sum / neg_count : na), 4)
// Calculate standard deviations
stddev_all = math.round((math.sqrt((returns_squared_sum - (returns_sum * returns_sum) / Lookback) / Lookback)) * 100, 2)
stddev_pos = math.round((pos_count != 0 ? math.sqrt((pos_returns_squared_sum - (pos_sum * pos_sum) / pos_count) / pos_count) : na) * 100, 2)
stddev_neg = math.round((neg_count != 0 ? math.sqrt((neg_returns_squared_sum - (neg_sum * neg_sum) / neg_count) / neg_count) : na) * 100, 2)
// Calculate probabilities
prob_pos = math.round((pos_count / Lookback) * 100, 2)
prob_neg = math.round((neg_count / Lookback) * 100, 2)
prob_neu = math.round(((Lookback - pos_count - neg_count) / Lookback) * 100, 2)
// Calculate ratios
sharpe_ratio = math.round((mean_all / stddev_all * (Annualize ? math.sqrt(Lookback) : 1))* 100, 2)
sortino_ratio = math.round((mean_all / stddev_neg * (Annualize ? math.sqrt(Lookback) : 1))* 100, 2)
omega_ratio = math.round(pos_sum / math.abs(neg_sum), 2)
// Set values in the array
array.set(export_array, 0, mean_all), array.set(export_array, 1, mean_pos), array.set(export_array, 2, mean_neg),
array.set(export_array, 3, stddev_all), array.set(export_array, 4, stddev_pos), array.set(export_array, 5, stddev_neg),
array.set(export_array, 6, prob_pos), array.set(export_array, 7, prob_neu), array.set(export_array, 8, prob_neg),
array.set(export_array, 9, sharpe_ratio), array.set(export_array, 10, sortino_ratio), array.set(export_array, 11, omega_ratio)
// Export the array
export_array
//}
Calibration Mode
A Calibration Mode is included for traders to focus on individual indicators, helping them fine-tune their settings without the influence of other components. In Calibration Mode, the user can visualize each indicator separately, making it easier to adjust parameters.
Alerts
The indicator includes alerts for long and short signals when the indicator changes direction, allowing traders to set automated notifications for key market events.
// Alert Conditions
alertcondition(long_alert, "LONG (Z-Score Weighted Trend System)", "Z-Score Weighted Trend System flipped ⬆LONG⬆")
alertcondition(short_alert, "SHORT (Z-Score Weighted Trend System)", "Z-Score Weighted Trend System flipped ⬇Short⬇")
Important Note:
The default settings of this indicator are not optimized for any particular market condition. They are generic starting points for experimentation. Traders are encouraged to use the calibration tools and backtesting features to adjust the system to their specific trading needs.
The results generated from the backtest are purely historical and are not indicative of future results. Market conditions can change, and the performance of this system may differ under different circumstances. Traders and investors should exercise caution and conduct their own research before using this indicator for any trading decisions.