Donchian Reversal Signals with LabelsOverview:
This indicator is designed to identify potential reversal signals based on price action relative to two Donchian Channels. It plots **"BUY"** and **"SELL"** labels on the chart when specific conditions are met, helping traders spot potential trend reversals.
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Key Features:
1. Dual Donchian Channels:
- The indicator uses two Donchian Channels with user-defined lengths (`length1` and `length2`).
- The upper band of each channel is the highest high over the specified period.
- The lower band of each channel is the lowest low over the specified period.
2. Reversal Signals:
- A yellow "BUY" label appears below a green (bullish) candle if:
- The previous candle is red (bearish).
- The previous red candle touches or breaches either of the lower Donchian Channels.
- A green "SELL" label appears above a red (bearish) candle if:
- The previous candle is green (bullish).
- The previous green candle touches or breaches either of the upper Donchian Channels.
3. Visual Clarity:
- The labels are placed above or below the candles for easy visibility.
- The use of colors (yellow for buy, green for sell) makes it intuitive to interpret the signals.
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How It Works:
1. Donchian Channel Calculation:
- The upper and lower bands of the two Donchian Channels are calculated using the highest high and lowest low over the specified periods (`length1` and `length2`).
2. Candle Color Detection:
- The script identifies whether the current and previous candles are bullish (green) or bearish (red) based on their open and close prices.
3. Signal Conditions:
- For a **"BUY" signal**:
- The current candle must be green.
- The previous candle must be red and touch or breach either of the lower Donchian Channels.
- For a **"SELL" signal**:
- The current candle must be red.
- The previous candle must be green and touch or breach either of the upper Donchian Channels.
4. Label Placement:
- The labels are plotted using `shape.labelup` and `shape.labeldown` for clear visibility.
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Input Parameters:
- **Donchian Channel Length 1 (`length1`)**: The period for the first Donchian Channel (default: 20).
- **Donchian Channel Length 2 (`length2`)**: The period for the second Donchian Channel (default: 34).
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How to Use:
1. Add the indicator to your chart.
2. Adjust the lengths of the Donchian Channels if needed.
3. Look for **"BUY"** and **"SELL"** labels on the chart:
- A **yellow "BUY" label** below a green candle suggests a potential bullish reversal.
- A **green "SELL" label** above a red candle suggests a potential bearish reversal.
4. Use these signals in conjunction with other technical analysis tools for confirmation.
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Example Use Case:
- If the price touches the lower Donchian Channel and forms a red candle, followed by a green candle, a **"BUY" label** will appear, indicating a potential upward reversal.
- If the price touches the upper Donchian Channel and forms a green candle, followed by a red candle, a **"SELL" label** will appear, indicating a potential downward reversal.
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Customization:
- You can modify the lengths of the Donchian Channels to suit your trading style.
- The colors and text of the labels can also be adjusted in the script if desired.
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Disclaimer:
This indicator is designed to assist traders in identifying potential reversal signals. However, it should not be used in isolation. Always confirm signals with additional analysis and risk management strategies.
ボラティリティ
PlanDeFi: Adaptive Trend Ribbons [ATR+RSI]#### **Overview**
The **Crypto Half-Trend Pro ** is a trend-following indicator designed to identify bullish and bearish market conditions using a combination of **moving averages, volatility adjustments, and dynamic ATR bands**. This enhanced version improves on the traditional Half-Trend system by incorporating **EMA smoothing, volatility-based adjustments, and additional fakeout/reversal detection mechanisms**.
#### **Key Features**
✅ **Trend Detection:**
- Uses a combination of fast and slow moving averages (EMA/SMA) to determine trend direction.
- Implements **Hull Moving Average (HMA)** smoothing for better trend visualization.
✅ **Dynamic ATR Bands:**
- Adjusts bands based on market volatility using **RSI-based ATR multipliers**.
- Helps identify potential **breakouts and trend reversals**.
✅ **Fakeout & Reversal Detection:**
- Detects potential **fake breakouts** by analyzing price action against extended ATR bands.
- Identifies **early reversal signals** using price crossovers and volume confirmation.
✅ **Customizable Alerts & Visuals:**
- Built-in **buy & sell signals** for trend confirmation.
- Color-coded bullish/bearish trend lines and **fakeout warnings**.
- **TradingView alerts** for trend shifts and reversals.
#### **How It Works**
🔹 The indicator calculates a **smoothed trend line** using a Hull Moving Average on dynamic price levels.
🔹 ATR bands expand/contract dynamically based on **market volatility** to improve signal accuracy.
🔹 Trend direction is confirmed when price crosses the trend line **with volume confirmation**.
🔹 **Fakeouts** are detected when price temporarily exceeds extended bands but fails to hold momentum.
🔹 **Reversal signals** are generated when price breaks back into the ATR zone with volume spikes.
#### **How to Use It**
- 📈 **Buy Signal:** When price breaks above the trend line, confirmed by volume and crossover signals.
- 📉 **Sell Signal:** When price breaks below the trend line with confirmed bearish conditions.
- 🚨 **Reversal Warning:** If price sharply re-enters the ATR zone with volume confirmation, expect a potential trend shift.
- 🛑 **Fakeout Alert:** If price temporarily breaks resistance but closes back inside, it may be a false move.
#### **Ideal For**
✔️ Crypto & Forex traders looking for **dynamic trend signals**
✔️ Swing traders wanting to **avoid fakeouts & catch reversals**
✔️ Traders seeking a **customizable, volatility-adjusted trend system**
🚀 **Try PlanDeFi: Adaptive Trend Ribbons today and improve your trend analysis!**
Smart Market Bias [PhenLabs]📊 Smart Market Bias Indicator (SMBI)
Version: PineScript™ v6
Description
The Smart Market Bias Indicator (SMBI) is an advanced technical analysis tool that combines multiple statistical approaches to determine market direction and strength. It utilizes complexity analysis, information theory (Kullback Leibler divergence), and traditional technical indicators to provide a comprehensive market bias assessment. The indicator features adaptive parameters based on timeframe and trading style, with real-time visualization through a sophisticated dashboard.
🔧 Components
Complexity Analysis: Measures price movement patterns and trend strength
KL Divergence: Statistical comparison of price distributions
Technical Overlays: RSI and Bollinger Bands integration
Filter System: Volume and trend validation
Visual Dashboard: Dynamic color-coded display of all components
Simultaneous current timeframe + higher time frame analysis
🚨Important Explanation Feature🚨
By hovering over each individual cell in this comprehensive dashboard, you will get a thorough and in depth explanation of what each cells is showing you
Visualization
HTF Visualization
📌 Usage Guidelines
Based on your own trading style you should alter the timeframe length that you would like to be analyzing with your dashboard
The longer the term of the position you are planning on entering the higher timeframe you should have your dashboard set to
Bias Interpretation:
Values > 50% indicate bullish bias
Values < 50% indicate bearish bias
Neutral zone: 45-55% suggests consolidation
✅ Best Practices:
Use appropriate timeframe preset for your trading style
Monitor all components for convergence/divergence
Consider filter strength for signal validation
Use color intensity as confidence indicator
⚠️ Limitations
Requires sufficient historical data for accurate calculations
Higher computational complexity on lower timeframes
May lag during extremely volatile conditions
Best performance during regular market hours
What Makes This Unique
Multi-Component Analysis: Combines complexity theory, statistical analysis, and traditional technical indicators
Adaptive Parameters: Automatically optimizes settings based on timeframe
Triple-Layer Filtering: Uses trend, volume, and minimum strength thresholds
Visual Confidence System: Color intensity indicates signal strength
Multi-Timeframe Capabilities: Allowing the trader to analyze not only their current time frame but also the higher timeframe bias
🔧 How It Works
The indicator processes market data through four main components:
Complexity Score (40% weight): Analyzes price returns and pattern complexity
Kullback Leibler Divergence (30% weight): Compares current and historical price distributions
RSI Analysis (20% weight): Momentum and oversold/overbought conditions
Bollinger Band Position (10% weight): Price position relative to volatility
Underlying Method
Maintains rolling windows of price data for multiple calculations
Applies custom normalization using hyperbolic tangent function
Weights component scores based on reliability and importance
Generates final bias percentage with confidence visualization
💡 Note: For optimal results, use in conjunction with price action analysis and consider multiple timeframe confirmation. The indicator performs best when all components show alignment.
Auto-Adjusting Kalman Filter by TenozenNew year, new indicator! Auto-Adjusting Kalman Filter is an indicator designed to provide an adaptive approach to trend analysis. Using the Kalman Filter (a recursive algorithm used in signal processing), this algo dynamically adjusts to market conditions, offering traders a reliable way to identify trends and manage risk! In other words, it's a remaster of my previous indicator, Kalman Filter by Tenozen.
What's the difference with the previous indicator (Kalman Filter by Tenozen)?
The indicator adjusts its parameters (Q and R) in real-time using the Average True Range (ATR) as a measure of market volatility. This ensures the filter remains responsive during high-volatility periods and smooth during low-volatility conditions, optimizing its performance across different market environments.
The filter resets on a user-defined timeframe, aligning its calculations with dominant trends and reducing sensitivity to short-term noise. This helps maintain consistency with the broader market structure.
A confidence metric, derived from the deviation of price from the Kalman filter line (measured in ATR multiples), is visualized as a heatmap:
Green : Bullish confidence (higher values indicate stronger trends).
Red : Bearish confidence (higher values indicate stronger trends).
Gray : Neutral zone (low confidence, suggesting caution).
This provides a clear, objective measure of trend strength.
How it works?
The Kalman Filter estimates the "true" price by filtering out market noise. It operates in two steps, that is, prediction and update. Prediction is about projection the current state (price) forward. Update is about adjusting the prediction based on the latest price data. The filter's parameters (Q and R) are scaled using normalized ATR, ensuring adaptibility to changing market conditions. So it means that, Q (Process Noise) increases during high volatility, making the filter more responsive to price changes and R (Measurement Noise) increases during low volatility, smoothing out the filter to avoid overreacting to minor fluctuations. Also, the trend confidence is calculated based on the deviation of price from the Kalman filter line, measured in ATR multiples, this provides a quantifiable measure of trend strength, helping traders assess market conditions objectively.
How to use?
Use the Kalman Filter line to identify the prevailing trend direction. Trade in alignment with the filter's slope for higher-probability setups.
Look for pullbacks toward the Kalman Filter line during strong trends (high confidence zones)
Utilize the dynamic stop-loss and take-profit levels to manage risk and lock in profits
Confidence Heatmap provides an objective measure of market sentiment, helping traders avoid low-confidence (neutral) zones and focus on high-probability opportunities
Guess that's it! I hope this indicator helps! Let me know if you guys got some feedback! Ciao!
Market Pressure Index [AlgoAlpha]The Market Pressure Index is a cutting-edge trading tool designed to measure and visualize bullish and bearish momentum through a unique blend of volatility analysis and dynamic smoothing techniques. This indicator provides traders with an intuitive understanding of market pressure, making it easier to identify trend shifts, breakout opportunities, and key moments to take profit. Perfect for scalpers and swing traders looking for a strategic edge in volatile markets.
Key Features:
🔎 Bullish and Bearish Volatility Separation : Dynamically calculates and displays bullish and bearish momentum separately, helping traders assess market direction with precision.
🎨 Customizable Appearance: Set your preferred colors for bullish and bearish signals to match your chart's theme.
📊 Deviation-Based Upper Band : Tracks extreme volatility levels using a configurable deviation multiplier, highlighting potential breakout points.
📈 Real-Time Signal Alerts : Provides alerts for bullish and bearish crossovers, as well as take-profit signals, ensuring you never miss key market movements.
⚡ Gradient-Based Visualization : Uses color gradients to depict the intensity of market pressure, making it easy to spot changes in momentum at a glance.
How to Use:
Add the Indicator : Add the Market Pressure Index to your TradingView chart by clicking the star icon. Customize inputs like the pressure lookback period, deviation settings, and colors to fit your trading style.
Interpret the Signals : Monitor the bullish and bearish momentum columns to gauge market direction. Look for crossovers to signal potential trend changes.
Take Action : Use alerts for breakouts above the upper band or for take-profit levels to enhance your trade execution.
How It Works:
The Market Pressure Index separates bullish and bearish momentum by analyzing price movement (close vs. open) and volatility. These values are smoothed using Hull Moving Averages (HMA) to highlight trends while minimizing noise. A deviation-based upper band dynamically tracks market extremes, signaling breakout zones. Color gradients depict the intensity of momentum, offering a clear, visually intuitive representation of market pressure. Alerts are triggered when significant crossovers or take-profit conditions occur, giving traders actionable insights without constant chart monitoring.
VWAP Suite by Augur - Multi PeriodOverview
The Multi-Timeframe VWAP Suite revolutionizes price analysis by combining institutional-grade volume-weighted pricing with multi-period deviation analytics. This professional toolkit simultaneously tracks VWAP across 5 time horizons (Daily to Yearly) with smart deviation bands, offering traders unparalleled insight into market structure and volatility dynamics.
Key Features
Multi-Timeframe VWAP Matrix
Simultaneous Daily/Weekly/Monthly/Quarterly/Yearly VWAP tracking
Institutional-level volume-weighted calculations
Independent timeframe toggles for focused analysis
Smart Deviation Architecture
Dual-layer standard deviation bands (1σ & 2σ)
Separate colors for upper/lower deviation zones
Adaptive 95% transparency fills for layered visualization
Professional Visual Design
Strategic color coding per timeframe (FIXED palette)
Dark Blue/Yellow/Purple/Pink/Red VWAP hierarchy
Orange-Green-Red-Blue deviation band system
Advanced Calculation Engine
HLC3 price source integration
Cumulative volume-weighting algorithm
Real-time standard deviation updates
QT RSI [ W.ARITAS ]The QT RSI is an innovative technical analysis indicator designed to enhance precision in market trend identification and decision-making. Developed using advanced concepts in quantum mechanics, machine learning (LSTM), and signal processing, this indicator provides actionable insights for traders across multiple asset classes, including stocks, crypto, and forex.
Key Features:
Dynamic Color Gradient: Visualizes market conditions for intuitive interpretation:
Green: Strong buy signal indicating bullish momentum.
Blue: Neutral or observation zone, suggesting caution or lack of a clear trend.
Red: Strong sell signal indicating bearish momentum.
Quantum-Enhanced RSI: Integrates adaptive energy levels, dynamic smoothing, and quantum oscillators for precise trend detection.
Hybrid Machine Learning Model: Combines LSTM neural networks and wavelet transforms for accurate prediction and signal refinement.
Customizable Settings: Includes advanced parameters for dynamic thresholds, sensitivity adjustment, and noise reduction using Kalman and Jurik filters.
How to Use:
Interpret the Color Gradient:
Green Zone: Indicates bullish conditions and potential buy opportunities. Look for upward momentum in the RSI plot.
Blue Zone: Represents a neutral or consolidation phase. Monitor the market for trend confirmation.
Red Zone: Indicates bearish conditions and potential sell opportunities. Look for downward momentum in the RSI plot.
Follow Overbought/Oversold Boundaries:
Use the upper and lower RSI boundaries to identify overbought and oversold conditions.
Leverage Advanced Filtering:
The smoothed signals and quantum oscillator provide a robust framework for filtering false signals, making it suitable for volatile markets.
Application: Ideal for traders and analysts seeking high-precision tools for:
Identifying entry and exit points.
Detecting market reversals and momentum shifts.
Enhancing algorithmic trading strategies with cutting-edge analytics.
ZenAlgo - UltimateThe ZenAlgo - Ultimate Indicator is a premium trading tool that integrates advanced sub-indicators into a single framework, combining volume analysis, divergence detection, and market sentiment visualization. Designed for traders seeking deeper insights, it addresses the limitations of standalone free indicators by delivering a cohesive system that enhances accuracy, adaptability, and decision-making.
Why Multiple Sub-Indicators?
The integration of sub-indicators into one tool provides unique benefits not achievable with individual free indicators:
Improved Accuracy: Combining volume trends, delta volume, and divergence detection creates a multi-dimensional view of market behavior, reducing the chance of false signals.
Synergistic Insights: Free indicators like MAs or divergences work independently, while this tool integrates them into a unified framework that highlights actionable patterns, improving signal reliability.
Actionable Combinations: The tool visually aligns multi-timeframe trends, divergences, and volume states, enabling traders to confirm trades using multiple metrics in one glance, saving time and enhancing precision.
Features
This indicator introduces several customizations and integrations that distinguish it from free alternatives:
Dynamic Volume Classification: It calculates and categorizes volume states into clear signals like "Mega Buy" or "Big Sell," providing instant clarity about unusual activity levels.
Enhanced Delta Volume Analysis: Tracks delta volume trends with adjustable sensitivity, identifying subtle shifts in market pressure that standalone delta indicators might miss.
Customizable Multi-Timeframe Volume Tables: Displays volume and delta metrics across multiple timeframes, offering a holistic view of market activity that helps align short- and long-term strategies.
Real-Time Alerts: Provides instant notifications for confirmed and unconfirmed delta volume crosses, helping users stay ahead of market movements.
Divergence Detection Across Metrics: Identifies regular and hidden bullish or bearish divergences using up, down, and delta volumes, integrating price fractals for added precision.
How It Works
1. Volume and Delta Volume Integration
The indicator calculates and categorizes volume activity into specific states, such as "Mega Buy" or "Big Sell," by comparing the current volume with its 20-period average. For delta volume, it tracks the difference between buying and selling pressure, identifying shifts in market sentiment. These calculations are dynamically updated across multiple timeframes, with delta trends smoothed using user-selected moving averages (e.g., SMA, EMA, WMA, HMA) to highlight sustained market pressure changes.
2. Multi-Timeframe Volume Tables
The tool aggregates and displays volume and delta volume data across various timeframes in a visual table. Each timeframe's data includes total volume, categorized buying and selling volumes, and the net delta volume. Colors within the table provide immediate insights into the prevailing market sentiment for each timeframe, with bullish or bearish conditions emphasized using pre-defined thresholds.
3. Divergence Detection Across Metrics
Divergences are identified using fractal patterns in up volume, down volume, and delta volume. Regular and hidden bullish or bearish divergences are detected by comparing historical volume peaks and troughs with corresponding price movements. This allows the tool to highlight potential reversals or trend continuations before they are visually apparent on the chart.
4. Market State Labels
The indicator synthesizes multiple metrics, such as volume trends, delta volume movements, and histogram direction, to generate actionable market state labels. These labels, such as "Bullish," "Bearish," or "Reversal," offer a high-level summary of current market conditions, helping traders quickly adapt their strategies.
5. Real-Time Alerts
To ensure traders stay informed, the tool includes alerts for confirmed and unconfirmed delta volume crosses. These alerts consider not only the delta volume's movement relative to its average but also whether the broader buying or selling pressure supports the signal, enhancing the reliability of the alerts.
Specific Scenarios Where This Indicator Excels
Trend Confirmation: Align rising delta volume with bullish divergences across timeframes for high-confidence entries.
Reversal Identification: Use divergence labels to anticipate trend reversals before they occur.
Market Sentiment Analysis: Dynamic candle coloring helps visualize whether the market is dominated by bullish or bearish forces.
Volume Breakout Detection: Track spikes in cumulative volume and delta volume to identify breakouts with higher accuracy.
When to Be Cautious
Low-Volume Markets: In thinly traded markets, signals like divergences or delta volume shifts may produce noise due to insufficient data.
Highly Volatile Conditions: Sudden volume spikes can result in false positives for breakouts or reversals.
Session Overlaps or Data Misalignment: Variations in session timings or data discrepancies can temporarily impact cumulative volume metrics.
Overfitting Sensitivity Settings: Excessively high sensitivity settings may overfit the indicator to specific market conditions, leading to unreliable signals in broader contexts.
Why Pay for This Indicator?
This tool stands out because it doesn’t merely replicate free indicators; it integrates and enhances them into a uniquely actionable framework:
Tailored for Precision: Adjustable parameters for sensitivity, divergence detection, and timeframe analysis allow traders to adapt the indicator to their strategies.
Time-Saving Synergy: Combines the functionality of multiple tools into a single interface, eliminating the need to juggle multiple scripts.
Comprehensive Insights: Delivers a broader perspective by linking volume trends, delta volume, and divergences, ensuring more informed decisions.
Real-Time Notifications: Alerts for key events ensure you never miss a critical market movement.
Usage Examples
Volume State Monitoring: Instantly identify states like "Big Buy" or "Mega Sell" to act on significant volume surges.
Multi-Timeframe Alignment: Combine bullish divergences on a 15-minute chart with a rising daily delta volume trend for high-probability trades.
Scalping Opportunities: Use delta volume crosses and short-term trends for quick entries and exits.
Breakout Validation: Confirm volume breakouts with delta volume spikes to avoid false signals.
Settings
Volume MA Length: Adjusts the moving average period for volume trends.
Divergence Sensitivity: Fine-tunes the thresholds for divergence detection to suit different market conditions.
Multi-Timeframe Visibility: Customizes the number of timeframes displayed in the cumulative volume table.
Conclusion
The Ultimate Indicator is more than a collection of sub-indicators—it’s a fully integrated system designed to address the limitations of standalone tools. By offering deeper insights into volume trends, market sentiment, and divergence analysis, it empowers traders to make better-informed decisions with enhanced confidence.
ATR BeamsATR Beams is a simple indicator that utilizes the ATR to determine levels above and below price action that can serve as stop loss or trailing visual aids across all instruments.
This indicator is preset to an ATR value of 14 and a multiplier of 1 for the ATR.
Both of these parameters can be modified to your specific trading preference, the color and indicator line style can both also be modified to your visual preference.
I hope this provides you with a good visual aid
IU Range Trading StrategyIU Range Trading Strategy
The IU Range Trading Strategy is designed to identify range-bound markets and take trades based on defined price ranges. This strategy uses a combination of price ranges and ATR (Average True Range) to filter entry conditions and incorporates a trailing stop-loss mechanism for better trade management.
User Inputs:
- Range Length: Defines the number of bars to calculate the highest and lowest price range (default: 10).
- ATR Length: Sets the length of the ATR calculation (default: 14).
- ATR Stop-Loss Factor: Determines the multiplier for the ATR-based stop-loss (default: 2.00).
Entry Conditions:
1. A range is identified when the difference between the highest and lowest prices over the selected range is less than or equal to 1.75 times the ATR.
2. Once a valid range is formed:
- A long trade is triggered at the range high.
- A short trade is triggered at the range low.
Exit Conditions:
1. Trailing Stop-Loss:
- The stop-loss adjusts dynamically using ATR targets.
- The strategy locks in profits as the trade moves in your favor.
2. The stop-loss and take-profit levels are visually plotted for transparency and easier decision-making.
Features:
- Automated box creation to visualize the trading range.
- Supports one position at a time, canceling opposite-side entries.
- ATR-based trailing stop-loss for effective risk management.
- Clear visual representation of stop-loss and take-profit levels with colored bands.
This strategy works best in markets with defined ranges and can help traders identify breakout opportunities when the price exits the range.
Volatility & Big Market MovesThis indicator shows the volatility per candle, and highlights candles where volatility exceeds a defined threshold.
Data shown:
Furthest %-distance from the previous candle's closing price to the top (positive histogram).
Furthest %-distance from the previous candle's closing price to the bottom (negative histogram).
Weighted Close SumWeighted Close Sum Indicator - Overview
The Weighted Close Sum Indicator is a dynamic and adaptive technical tool designed to analyze price action by incorporating a volatility-adjusted weighted smoothing approach. Unlike traditional moving averages, this indicator adjusts its smoothing length based on market volatility, making it highly responsive to price fluctuations while maintaining accuracy in trend detection.
How It Works
Dynamic Length Adjustment Using ATR:
The indicator calculates the Average True Range (ATR) over a default period of 14 to gauge market volatility.
A dynamic smoothing length is computed based on the user-defined length and a volatility multiplier, allowing the indicator to adapt to changing market conditions.
Formula:
Dynamic Length=Length×(1+ATRClose Price×Multiplier)
Dynamic Length=Length×(1+Close PriceATR×Multiplier)
Cosine-Weighted Smoothing:
A set of weights is calculated using a cosine function to create a smooth and responsive weighting curve.
These weights are then applied to past closing prices, emphasizing recent data while retaining a natural tapering effect for older data points.
Weighted Close Sum Calculation:
The final value, known as the Cumulative Sum of Moving Averages (CSMA), is computed by multiplying the closing prices with their corresponding weights and summing them up.
This results in a smooth representation of price trends that dynamically adjusts based on market conditions.
How to Use the Indicator
Trend Identification:
Rising values of the Weighted Close Sum indicate an uptrend, while declining values suggest a downtrend.
Volatility Sensitivity:
The adaptive length ensures that the indicator responds faster during high volatility and smooths out during calmer periods, making it suitable for trend-following strategies.
Customizable Parameters:
Length: Controls the base period for calculation. A higher length provides smoother outputs, while a lower value makes the indicator more sensitive.
Volatility Multiplier: Adjusts the sensitivity of the indicator to price fluctuations. A higher multiplier increases responsiveness during volatile periods.
Sharpe and Sortino Ratios with Date RangeThis indicator calculates the Sharpe and Sortino ratios using a chart symbol's periodic price returns.
I added the ability to calculate SORTINO and Sharpe based on CUSTOM DATES within the option menu.
It builds on the script here: by adding this feature.
A little about the Sortino Ratio.
www.nasdaq.com
I want equity market returns, but I don’t want equity market volatility. This is the sentiment many investors naturally feel. This sentiment often grows stronger as one approaches or is in the phase where they desire distributions from their savings to improve lifestyle. This is why there is a need for active management in the investment arena. The desire to control downside volatility, but also participate in the upside growth is a very fundamental human desire. The Sortino Ratio measures how well a particular investment meets this fundamental human desire.
There is the old adage, “volatility is the price you pay for returns.” However, what if we could measure the historical performance of an investment and see if it has given above average returns compared to the downside volatility. This is a simple division problem. It will tell us if the volatility “price we are paying for returns” is good. We can then compare that to other investments to see how they compare.
Let us take the return and subtract the risk-free interest rate and then simply divide that by the downside movement from the average. A basic division problem yielding a number that measures a very basic human desire: How well did this investment do compared to the downside risk it experienced.
In the world of financial analysis and investment management, ratios are abundant. There are many ratios that are truly important to a particular analysis. However, the sheer abundance of ratios that are available often overwhelms the casual investor, leading them to disregard ratios altogether. I would argue for those investors that desire a way to rank an investment by its ability to satisfy this very fundamental human desire, the Sortino Ratio is the number they need to consider.
Disappointing in the marketplace for research, the Sortino Ratio is not featured prominently. It is much easier to find the inflows a particular ETF has experienced than the Sortino Ratio. Inflows are important. They measure how much people are investing into an ETF. However, they are mostly only important to the fund manager, not the investor. What investors care about is the Risk-Adjusted Return. This is the Sortino Ratio.
Engulfing and ATR-Imbalance [odnac]This Pine Script indicator combines two powerful concepts—Engulfing Candlestick Patterns and ATR Imbalance—to identify potential market reversal points with increased precision.
Engulfing Candlestick Patterns:
Bullish Engulfing: Identified when a candle closes higher than it opens, and it completely engulfs the previous candle (previous close is lower than the current open, and previous high is lower than the current close).
Bearish Engulfing: Identified when a candle closes lower than it opens, and it completely engulfs the previous candle (previous close is higher than the current open, and previous low is higher than the current close).
Bar Coloring: These patterns are highlighted with a customizable color (light gray by default) to make them easily identifiable.
ATR-Based Imbalance:
The Average True Range (ATR) is used to measure market volatility, and this script checks if the current candle’s range (difference between high and low) exceeds a defined multiple of the ATR, indicating a possible imbalance.
Imbalance Detection: If the current candle’s range is greater than ATR * imbalance multiplier (default multiplier: 1.5), it is marked as an ATR imbalance.
Bar Coloring: Candles with a significant imbalance (greater range than the ATR-based threshold) are highlighted in yellow, indicating an outlier or extreme price movement.
Engulfing + ATR Imbalance:
When both a Bullish Engulfing pattern and an ATR Imbalance are detected, a green triangle up is plotted below the bar, signaling a potential bullish reversal.
Conversely, when both a Bearish Engulfing pattern and an ATR Imbalance occur, a red triangle down is plotted above the bar, signaling a potential bearish reversal.
User Inputs:
Engulfing Plot: Enable or disable the plotting of Engulfing Candles.
ATR Length: Set the period used to calculate the ATR (default is 5).
Imbalance Multiplier: Adjust the multiplier to define the threshold for ATR imbalance detection (default is 1.5).
Bar Colors: Customizable color for both Engulfing candles and Imbalance candles.
Engulfing & Imbalance Plot: Enable or disable plotting of the combined conditions (Engulfing + ATR Imbalance) with arrows.
How This Indicator Helps:
By combining price action patterns with volatility analysis, this indicator highlights high-probability reversal points where significant price movement (imbalance) coincides with a clear Engulfing pattern. Traders can use these signals to time entries or exits based on both price action and market volatility.
hector mena Breakout Trading with ATR, RSI and MA CrossTitle: Breakout Trading Strategy with ATR, RSI, and Moving Average Cross
Description (English):
This script combines key technical indicators—ATR (Average True Range), RSI (Relative Strength Index), and Moving Averages—to provide a comprehensive breakout trading strategy. It is designed to help traders identify significant breakout levels and confirm signals with momentum and trend analysis.
How It Works:
ATR for Breakout Levels:
The ATR is used to calculate dynamic breakout levels by adjusting the highest resistance and lowest support levels with a customizable multiplier. This ensures that breakout levels adapt to market volatility.
RSI for Momentum Confirmation:
The RSI identifies overbought and oversold conditions, providing an additional layer of confirmation for breakouts. A breakout accompanied by an RSI signal can indicate stronger momentum.
Moving Average Cross for Trend Validation:
Two simple moving averages (short-term and long-term) are included to validate the trend. A crossover suggests a potential change in trend, aligning with breakout signals.
Why Combine These Indicators?
The ATR ensures breakout levels are realistic and volatility-adjusted.
The RSI avoids false signals by confirming if the price has momentum during a breakout.
Moving Average crossovers add trend-following confirmation, helping traders align with market direction.
The combination provides a robust framework to filter out false signals and improve the reliability of trading decisions.
Key Features:
Breakout Levels: Upper and lower breakout levels dynamically calculated using ATR.
RSI Confirmation: Visual overbought (70) and oversold (30) levels and RSI plot.
Trend Validation: Short and long-term moving averages plotted on the chart with crossover signals.
Visual Alerts: Clear "BUY" and "SELL" labels for actionable signals.
Custom Alerts: Configurable alerts for breakouts and moving average crossovers.
How to Use It:
Adjust the parameters (ATR length, multiplier, RSI length, and moving averages) based on your trading strategy.
Look for "BUY" signals when:
Price breaks above the resistance level, and RSI indicates oversold conditions.
Moving averages cross bullishly.
Look for "SELL" signals when:
Price breaks below the support level, and RSI indicates overbought conditions.
Moving averages cross bearishly.
Use alerts for automated notifications about potential trades.
Notes:
This script is intended for educational purposes. Use it alongside proper risk management techniques and backtesting.
Always test in demo mode before applying it to live trading.
Dawud Range Rover BarsThe Dawud Range Rover Bars indicator is a dynamic technical analysis tool designed to normalize price movements into a 0-100 range, helping traders identify overbought and oversold conditions while incorporating adaptive signal tracking. This indicator utilizes multiple smoothing techniques, including EMA, RMA, SMA, and TMA, allowing traders to filter price movements based on their preferred method. By applying a rolling min-max scaling approach, the script converts price action into a normalized range, making it easier to detect potential trend reversals or continuations.
A key feature of this indicator is its dynamic signal line, which smooths the normalized value to help confirm trend shifts. Traders can adjust the length and smoothing strength of both the primary normalization process and the signal line to fine-tune the sensitivity of the indicator. Overbought and oversold levels are marked with customizable thresholds, providing visual cues to identify key trading opportunities. Additionally, background highlights dynamically change color when the price enters extreme zones, making trend shifts more apparent.
The indicator also incorporates a unique threshold-based bar plotting system that displays colored bars below the price when the normalized value crosses the upper or lower custom thresholds. This provides an additional visual confirmation of extreme price conditions. To ensure accuracy and avoid repainting, historical values are stored in arrays, preventing future bars from influencing past signals. This non-repainting approach makes the Dawud Range Rover Bars a reliable tool for traders looking for consistent signals without the risk of misleading historical data.
By combining trend smoothing, normalization, adaptive signal lines, and threshold-based visual cues, the Dawud Range Rover Bars indicator offers a comprehensive approach to market analysis. It helps traders identify key reversal zones, trend strengths, and breakout opportunities with greater clarity. With its flexibility in customization and non-repainting methodology, this indicator is suitable for traders across different timeframes and asset classes who are looking for a structured and visually intuitive method to assess market conditions.
Liquidity Trap Detector (LTD)The Liquidity Trap Detector is an advanced trading tool designed to identify liquidity zones and potential traps set by institutional players. It provides traders with a comprehensive framework to align with smart money movements, helping them avoid common retail pitfalls such as bull and bear traps.
The indicator focuses on detecting liquidity sweeps, breaker blocks, and areas of institutional accumulation/distribution. It integrates multiple technical analysis methods to offer high-probability signals and insights into how liquidity dynamics unfold in the market.
Note : This indicator is not designed for beginners; it is intended for traders who already have a solid understanding of trading fundamentals. It is tailored for individuals who are familiar with concepts like liquidity, order blocks, and traps. Traders with at least 6 months to 1 year of trading experience will fully appreciate the power and potential of this indicator, as they will have the necessary knowledge to leverage its features effectively. Beginners may find it challenging to grasp the advanced concepts embedded in this tool.
Why Combine These Elements?
The components of the Liquidity Trap Detector are carefully chosen to address the core challenges of identifying institutional activity and liquidity traps. Here’s why each element is included and how they work together:
1. Order Blocks:
• Purpose: Identify zones where large institutional players accumulate or distribute positions.
• Role in the Indicator: These zones act as primary liquidity areas, where price is likely to reverse or consolidate due to significant order flow.
2. Breaker Blocks:
• Purpose: Highlight areas where liquidity has been swept, leading to potential price reversals or continuations.
• Role in the Indicator: Confirms whether a liquidity trap has occurred and provides actionable levels for entry or exit.
3. ATR-Based Volatility Zones:
• Purpose: Filter signals based on market volatility to ensure trades align with statistically significant price movements.
• Role in the Indicator: Defines dynamic support and resistance zones, improving the accuracy of signal generation.
4. Volume Delta:
• Purpose: Measure the imbalance between aggressive buyers and sellers, often indicating institutional activity.
• Role in the Indicator: Validates whether a liquidity trap is backed by smart money absorption or retail-driven momentum.
5. Trend Confirmation (EMA):
• Purpose: Align liquidity trap signals with the broader market trend, reducing false positives.
• Role in the Indicator: Ensures trades are executed in the direction of the prevailing trend.
What Makes It Unique?
1. Gen 1 Liquidity Zones and Traps:
• The indicator identifies Gen 1 Liquidity Zones, which represent the first areas where liquidity is accumulated or swept. While these zones often lead to reversals, they can sometimes fail, resulting in continuation moves. The indicator highlights these scenarios, helping traders adapt.
• For example, a bull trap identified in a Gen 1 Zone may see price move higher after an initial red candle, completing a secondary liquidity sweep before reversing.
2. Multi-Layer Signal Validation:
• Signals are only generated when liquidity, volume, trend, and volatility align. This ensures high-probability setups and reduces noise in choppy markets.
3. Dynamic Adaptability:
• ATR-based zones and volume delta filtering allow the indicator to adapt to different market conditions, from trending to range-bound environments.
4. Institutional Insights:
• By focusing on liquidity sweeps, order blocks, and volume imbalances, the indicator helps traders align with institutional strategies rather than retail behavior.
How It Works
The Liquidity Trap Detector uses a step-by-step process to identify and validate liquidity traps:
1. Identifying Liquidity Zones:
• Order Blocks: Mark key zones of institutional activity where price is likely to reverse.
• Breaker Blocks: Highlight areas where liquidity sweeps have occurred, signaling potential traps.
2. Filtering with Volatility (ATR):
• ATR defines dynamic support and resistance zones, ensuring signals are only generated near significant price levels.
3. Validating Traps with Volume Delta:
• Volume delta shows whether liquidity sweeps are backed by aggressive buying/selling from institutions, confirming the trap’s validity.
4. Aligning with Market Trends:
• EMA ensures signals align with the broader trend to reduce false positives.
5. Monitoring Gen 1 Liquidity Zones:
• The indicator highlights Gen 1 Liquidity Zones where price may initially reverse or sweep further before a true reversal. Traders are alerted to potential continuation scenarios if volume or momentum suggests unmet liquidity above/below the zone.
How to Use It
Buy Signal:
• Triggered when:
• Price sweeps below an order block and forms a breaker block, indicating a liquidity trap.
• Volume delta confirms aggressive selling absorption.
• ATR volatility zone supports the reversal.
• EMA confirms a bullish trend.
• Action: Enter a Buy trade and set:
• Stop Loss (SL): Below the order block.
• Take Profit (TP): Near the next resistance or liquidity zone.
Sell Signal:
• Triggered when:
• Price sweeps above an order block and forms a breaker block, indicating a liquidity trap.
• Volume delta confirms aggressive buying absorption.
• ATR volatility zone supports the reversal.
• EMA confirms a bearish trend.
• Action: Enter a Sell trade and set:
• SL: Above the order block.
• TP: Near the next support or liquidity zone.
Timeframes:
• Best suited for scalping and intraday trading on lower timeframes (5m, 15m, 1H).
• Can also be applied to swing trading on higher timeframes.
Example Scenarios:
1. Bull Trap in a Gen 1 Zone:
• Price sweeps above a resistance order block, forms a breaker block, and reverses sharply. However, if momentum persists, price may continue higher after a minor pullback. The indicator helps traders anticipate this by monitoring volume and trend shifts.
2. Bear Trap with Secondary Sweep:
• Price sweeps below a support order block but fails to reverse immediately, instead forming a secondary liquidity sweep before turning bullish. The indicator highlights both scenarios, allowing for flexible trade management.
Why Use It?
The Liquidity Trap Detector offers:
1. Precision: Combines multiple filters to identify institutional liquidity traps with high accuracy.
2. Adaptability: Works across trending and range-bound markets.
3. Smart Money Alignment: Helps traders avoid retail traps by focusing on liquidity sweeps and institutional behavior.
Choppiness IndexThis Pine Script v6 indicator calculates the Choppiness Index over a user-defined length and segments it based on user-defined thresholds for choppy and trending market conditions. The indicator allows users to toggle the visibility of choppy, trending, and neutral segments using checkboxes.
Here's how it works:
Inputs: Users can set the length for the Choppiness Index calculation and thresholds for choppy and trending conditions. They can also choose which segments to display.
Choppiness Index Calculation: The script calculates the Choppiness Index using the ATR and the highest-high and lowest-low over the specified length.
Segment Determination: The script determines which segment the current Choppiness Index value falls into based on the thresholds. The color changes exactly at the threshold values.
Dynamic Plotting: The Choppiness Index is plotted with a color that changes based on the segment. The plot is only visible if the segment is "turned on" by the user.
Threshold Lines: Dashed horizontal lines are plotted at the choppy and trending thresholds for reference.
This indicator helps traders visualize market conditions and identify potential transitions between choppy and trending phases, with precise color changes at the threshold values.
Dynamic Ticks Oscillator Model (DTOM)The Dynamic Ticks Oscillator Model (DTOM) is a systematic trading approach grounded in momentum and volatility analysis, designed to exploit behavioral inefficiencies in the equity markets. It focuses on the NYSE Down Ticks, a metric reflecting the cumulative number of stocks trading at a lower price than their previous trade. As a proxy for market sentiment and selling pressure, this indicator is particularly useful in identifying shifts in investor behavior during periods of heightened uncertainty or volatility (Jegadeesh & Titman, 1993).
Theoretical Basis
The DTOM builds on established principles of momentum and mean reversion in financial markets. Momentum strategies, which seek to capitalize on the persistence of price trends, have been shown to deliver significant returns in various asset classes (Carhart, 1997). However, these strategies are also susceptible to periods of drawdown due to sudden reversals. By incorporating volatility as a dynamic component, DTOM adapts to changing market conditions, addressing one of the primary challenges of traditional momentum models (Barroso & Santa-Clara, 2015).
Sentiment and Volatility as Core Drivers
The NYSE Down Ticks serve as a proxy for short-term negative sentiment. Sudden increases in Down Ticks often signal panic-driven selling, creating potential opportunities for mean reversion. Behavioral finance studies suggest that investor overreaction to negative news can lead to temporary mispricings, which systematic strategies can exploit (De Bondt & Thaler, 1985). By incorporating a rate-of-change (ROC) oscillator into the model, DTOM tracks the momentum of Down Ticks over a specified lookback period, identifying periods of extreme sentiment.
In addition, the strategy dynamically adjusts entry and exit thresholds based on recent volatility. Research indicates that incorporating volatility into momentum strategies can enhance risk-adjusted returns by improving adaptability to market conditions (Moskowitz, Ooi, & Pedersen, 2012). DTOM uses standard deviations of the ROC as a measure of volatility, allowing thresholds to contract during calm markets and expand during turbulent ones. This approach helps mitigate false signals and aligns with findings that volatility scaling can improve strategy robustness (Barroso & Santa-Clara, 2015).
Practical Implications
The DTOM framework is particularly well-suited for systematic traders seeking to exploit behavioral inefficiencies while maintaining adaptability to varying market environments. By leveraging sentiment metrics such as the NYSE Down Ticks and combining them with a volatility-adjusted momentum oscillator, the strategy addresses key limitations of traditional trend-following models, such as their lagging nature and susceptibility to reversals in volatile conditions.
References
• Barroso, P., & Santa-Clara, P. (2015). Momentum Has Its Moments. Journal of Financial Economics, 116(1), 111–120.
• Carhart, M. M. (1997). On Persistence in Mutual Fund Performance. The Journal of Finance, 52(1), 57–82.
• De Bondt, W. F., & Thaler, R. (1985). Does the Stock Market Overreact? The Journal of Finance, 40(3), 793–805.
• Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65–91.
• Moskowitz, T. J., Ooi, Y. H., & Pedersen, L. H. (2012). Time Series Momentum. Journal of Financial Economics, 104(2), 228–250.
Smart Money Breakout Signals [AlgoAlpha]Introducing the Smart Money Breakout Signals, a cutting-edge trading indicator designed to identify key structural shifts and breakout opportunities in the market. This tool leverages a blend of smart money concepts like Break of Structure (BOS) and Change of Character (CHoCH) to provide traders with actionable insights into market direction and potential entry or exit points.
Key Features :
✨ Market Structure Analysis : Automatically detects and labels BOS and CHoCH for trend confirmation and reversals.
🎨 Customizable Visualization : Tailor bullish and bearish colors for breakout lines and signals to suit your preferences.
📊 Dynamic Take-Profit Targets : Displays three tiered take-profit levels based on breakout volatility.
🔔 Real-Time Alerts : Stay ahead of the game with notifications for bullish and bearish breakouts.
📋 Performance Dashboard : Monitor signal statistics, including win rates and total signals, directly on your chart.
How to Use :
Add the Indicator : Add the script to your favourites ⭐ and customize settings like market structure horizon and confirmation type.
Monitor Breakouts : Observe BOS and CHoCH labels to identify potential trend shifts. Use the breakout lines and tiered take-profit levels to plan trades effectively.
Set Alerts : Enable alerts for bullish or bearish breakouts to act on opportunities without constant monitoring.
How It Works :
The indicator identifies market structure by analyzing pivot highs and lows over a user-defined time horizon. A breakout is confirmed based on either candle closes or wicks surpassing previous pivot points. Upon detection, the script generates signals with breakout lines and calculates take-profit targets based on the distance from the breakout level. A built-in dashboard tracks performance metrics like total signals and win rates, giving traders real-time feedback on strategy effectiveness.
TVMC - Composite Indicator with Technical RatingsDescription:
The TVMC (Trend, Volume, Momentum, Composite) indicator is a powerful multi-component tool designed to provide traders with a comprehensive understanding of market conditions. By combining four essential technical analysis components—trend, momentum, volume, and volatility—this indicator offers clear and actionable insights to assist in decision-making.
Key Features:
1. Trend Component (TC):
* Based on MACD (Moving Average Convergence Divergence), this component analyzes the relationship between two exponential moving averages (fast and slow) to determine the prevailing market trend.
* The MACD signal is normalized to a range of -1 to +1 for consistency and clarity.
2. Momentum Component (MC):
* Utilizes RSI (Relative Strength Index) to measure the strength and speed of price movements.
* This component highlights overbought or oversold conditions, which may indicate potential market reversals.
3. Volume Confirmation (VC):
* Compares the current trading volume to its moving average over a specified period.
* High volume relative to the average confirms the validity of the current trend.
4. Volatility Filter (VF):
* Uses ATR (Average True Range) to gauge market volatility.
* Adjusts and smooths signals to reduce noise during periods of high volatility.
5. Technical Ratings Integration:
* Incorporates TradingView’s Technical Ratings, allowing users to validate signals using moving averages, oscillators, or a combination of both.
* Users can choose their preferred source of ratings for enhanced signal confirmation.
How It Works:
The TVMC indicator combines the weighted contributions of the Trend, Momentum, and Volume components, further refined by the Volatility Filter. Each component plays a specific role:
* Trend: Identifies whether the market is bullish, bearish, or neutral.
* Momentum: Highlights the strength of price action.
* Volume: Confirms whether the current price action is supported by sufficient trading activity.
* Volatility: Filters out excessive noise in volatile market conditions, providing a smoother and more reliable output.
Visualization:
1. Bullish Signals:
* The indicator line turns green and remains above the zero line, indicating upward momentum.
2. Bearish Signals:
* The indicator line turns red and falls below the zero line, signaling downward momentum.
3. Neutral Signals:
* The line is orange and stays near zero, indicating a lack of strong trend or momentum.
4. Zones:
* Horizontal lines at +30 and -30 mark strong bullish and bearish zones, respectively.
* A zero line is included for clear separation between bullish and bearish signals.
Recommended Usage:
* Best Timeframes: The indicator is optimized for higher timeframes such as 4-hour (H4) and daily (D1) charts.
* Trading Style: Suitable for swing and positional trading.
* Customization: The indicator allows users to adjust all major parameters (e.g., MACD, RSI, volume, and ATR settings) to fit their trading preferences.
Customization Options:
* Adjustable weights for Trend, Momentum, and Volume components.
* Fully configurable settings for MACD, RSI, Volume SMA, and ATR periods.
* Timeframe selection for multi-timeframe analysis.
Important Notes:
1. Originality: The TVMC indicator combines multiple analysis methods into a unique framework. It does not replicate or minimally modify existing indicators.
2. Transparency: The description is detailed enough for users to understand the methodology without requiring access to the code.
3. Clarity: The indicator is explained in a way that is accessible even to users unfamiliar with complex technical analysis tools.
Compliance with TradingView Rules:
* The indicator is written in Pine Script version 5, adhering to TradingView’s language standards.
* The description is written in English to ensure accessibility to the global community, with a clear explanation of all components and functionality.
* No promotional content, links, or unrelated references are included.
* The chart accompanying the indicator is clean and demonstrates its intended use clearly, with no additional indicators unless explicitly explained.
Volatility-Adjusted Rate of Change (VARC) ModelThe Volatility-Adjusted Rate of Change (VARC) Model is a dynamic trading strategy designed to identify potential market opportunities by incorporating volatility and skewness data. The model relies on the CBOE Skew Index (CBOE:SKEW) and adjusts the traditional Rate of Change (ROC) indicator based on market volatility, offering a more refined approach to trading based on price momentum.
1. CBOE Skew Index (SKEW) and ROC Calculation
At its core, the VARC model uses the CBOE Skew Index as a measure of market sentiment. The SKEW index represents the perceived risk of extreme negative movements in the S&P 500, providing insight into the balance of risks in the market (CBOE, 2021). This sentiment-based index is often used by traders and analysts to gauge the likelihood of a market downturn.
The Rate of Change (ROC) is applied to the Skew Index, calculated over a specified lookback period (rocLength = 29). The ROC measures the percentage change in price from one period to another and is widely used to gauge the momentum of an asset (Chande & Kroll, 1994). In the VARC model, the ROC of the Skew Index is employed to assess shifts in market sentiment that may signal turning points or potential volatility.
2. Volatility Adjustment
Volatility plays a significant role in market behavior and risk management. The VARC model uses a volatility-adjusted threshold to dynamically adjust the sensitivity of the trading signals. This is achieved by calculating the standard deviation of the ROC over a defined volatility lookback period (volatilityLookback = 20) and applying a volatility multiplier (volatilityMultiplier = 1.5). These parameters define upper and lower thresholds for trade entry and exit.
The model adjusts the sensitivity of the ROC signals based on market volatility, ensuring that the strategy adapts to changing market conditions. When volatility is high, the thresholds are widened, allowing the model to filter out noise and avoid unnecessary trades. Conversely, during periods of low volatility, the thresholds tighten, enabling the model to capture smaller price movements.
3. Entry and Exit Conditions
The VARC model generates trading signals based on the behavior of the ROC relative to the dynamically adjusted volatility thresholds. A long position is initiated when the ROC crosses below the lower threshold, indicating that the market is becoming oversold or showing signs of excessive pessimism. The position is closed when the ROC exceeds the upper threshold, signaling a potential reversal or a return to normal market conditions. These entry and exit conditions are defined as follows:
• Long Condition: The ROC is below the lower threshold (roc < dynamicThresholdLow).
• Exit Condition: The ROC is above the upper threshold (roc > dynamicThresholdHigh).
This approach provides a systematic method for entering and exiting positions based on volatility-adjusted momentum, helping traders to capitalize on shifts in market sentiment.
4. Visualization and Signal Highlighting
The model includes several visual aids to help traders interpret the signals. The ROC, dynamic thresholds, and a zero line are plotted on the chart to provide a clear representation of market momentum and the current trading range. Furthermore, a background color is used to highlight periods when a position is open, visually reinforcing the model’s decisions.
5. Conclusion
The VARC model offers a robust framework for trading by combining momentum (through the ROC) with a volatility-adjusted approach that refines trade signals based on market conditions. The use of the CBOE Skew Index adds an additional layer of market sentiment analysis, providing context to the ROC values. This volatility-adaptive strategy offers traders a more nuanced way to navigate the markets, making it suitable for both short-term and longer-term trading horizons.
References:
• CBOE. (2021). CBOE Skew Index (SKEW). Chicago Board Options Exchange. Retrieved from www.cboe.com
• Chande, T., & Kroll, J. (1994). The New Technical Trader: Boost Your Profit by Plugging into the Latest Indicators. Wiley.
This model can be particularly useful in volatile markets, where traditional fixed thresholds may not perform as well. By adjusting the thresholds dynamically based on the underlying volatility, the VARC model offers a more flexible and responsive approach to market trading.
PDF-MA Supertrend [BackQuant]PDF-MA Supertrend
The PDF-MA Supertrend combines the innovative Probability Density Function (PDF) smoothing with the widely popular Supertrend methodology, creating a robust tool for identifying trends and generating actionable trading signals. This indicator is designed to provide precise entries and exits by dynamically adapting to market volatility while visualizing long and short opportunities directly on the chart.
Core Feature: PDF Smoothing
At the foundation of this indicator is the PDF smoothing technique, which applies a Probability Density Function to calculate a smoothed moving average. This method allows the indicator to assign adaptive weights to data points, making it responsive to market changes without overreacting to short-term volatility.
Key parameters include:
Variance: Controls the spread of the PDF weighting. A smaller variance results in sharper responses, while a larger variance smooths out the curve.
Mean: Shifts the PDF’s center, allowing traders to tweak how weights are distributed around the data points.
Smoothing Method: Offers the choice between EMA (Exponential Moving Average) and SMA (Simple Moving Average) for blending the PDF-smoothed data with traditional moving average methods.
By combining these parameters, the PDF smoothing creates a moving average that effectively captures underlying trends.
Supertrend: Adaptive Trend and Volatility Tracking
The Supertrend is a well-known volatility-based indicator that dynamically adjusts to market conditions using the ATR (Average True Range). In this script, the PDF-smoothed moving average acts as the price input, making the Supertrend calculation more adaptive and precise.
Key Supertrend Features:
ATR Period: Determines the lookback period for calculating market volatility.
Factor: Multiplies the ATR to set the distance between the Supertrend and the price. A higher factor creates wider bands, filtering out smaller price movements, while a lower factor captures tighter trends.
Dynamic Direction: The Supertrend flips its direction based on price interactions with the calculated upper and lower bands:
Uptrend : When the price is above the Supertrend, the direction turns bullish.
Downtrend : When the price is below the Supertrend, the direction turns bearish.
This combination of PDF smoothing and Supertrend calculation ensures that trends are detected with greater accuracy, while volatility filters out market noise.
Long and Short Signal Generation
The PDF-MA Supertrend generates actionable trading signals by detecting transitions in the trend direction:
Long Signal (𝕃): Triggered when the trend transitions from bearish to bullish. This is visually represented with a green triangle below the price bars.
Short Signal (𝕊): Triggered when the trend transitions from bullish to bearish. This is marked with a red triangle above the price bars.
These signals provide traders with clear entry and exit points, ensuring they can capitalize on emerging trends while avoiding false signals.
Customizable Visualization Options
The indicator offers a range of visualization settings to help traders interpret the data with ease:
Show Supertrend: Option to toggle the visibility of the Supertrend line.
Candle Coloring: Automatically colors candlesticks based on the trend direction:
Green for long trends.
Red for short trends.
Long and Short Signals (𝕃 + 𝕊): Displays long (𝕃) and short (𝕊) signals directly on the chart for quick identification of trade opportunities.
Line Color Customization: Allows users to customize the colors for long and short trends.
Alert Conditions
To ensure traders never miss an opportunity, the PDF-MA Supertrend includes built-in alerts for trend changes:
Long Signal Alert: Notifies when a bullish trend is identified.
Short Signal Alert: Notifies when a bearish trend is identified.
These alerts can be configured for real-time notifications via SMS, email, or push notifications, making it easier to stay updated on market movements.
Suggested Parameter Adjustments
The indicator’s effectiveness can be fine-tuned using the following guidelines:
Variance:
For low-volatility assets (e.g., indices): Use a smaller variance (1.0–1.5) for smoother trends.
For high-volatility assets (e.g., cryptocurrencies): Use a larger variance (1.5–2.0) to better capture rapid price changes.
ATR Factor:
A higher factor (e.g., 2.0) is better suited for long-term trend-following strategies.
A lower factor (e.g., 1.5) captures shorter-term trends.
Smoothing Period:
Shorter periods provide more reactive signals but may increase noise.
Longer periods offer stability and better alignment with significant trends.
Experimentation is encouraged to find the optimal settings for specific assets and trading strategies.
Trading Applications
The PDF-MA Supertrend is a versatile indicator suited to a variety of trading approaches:
Trend Following : Use the Supertrend line and signals to follow market trends and ride sustained price movements.
Reversal Trading : Spot potential trend reversals as the Supertrend flips direction.
Volatility Analysis : Adjust the ATR factor to filter out minor price fluctuations or capture sharp movements.
Final Thoughts
The PDF-MA Supertrend combines the precision of Probability Density Function smoothing with the adaptability of the Supertrend methodology, offering traders a powerful tool for identifying trends and volatility. With its customizable parameters, actionable signals, and built-in alerts, this indicator is an excellent choice for traders seeking a robust and reliable system for trend detection and entry/exit timing.
As always, backtesting and incorporating this indicator into a broader strategy are recommended for optimal results.
