[Top] Simple ATR TP/SLSimple TP/SL from ATR (Locked per Bar) - Advanced Position Management Tool
What This Indicator Does:
Automatically calculates and displays Take Profit (TP) and Stop Loss (SL) levels based on Average True Range (ATR)
Locks ATR values and direction signals at the start of each bar to prevent repainting and provide consistent levels
Offers multiple direction detection modes including real-time candle-based positioning for dynamic trading approaches
Displays entry, TP, and SL levels as clean horizontal lines that extend from the current bar
Original Features That Make This Script Unique:
Bar-Locked ATR System: ATR values are captured and frozen at bar open, ensuring levels remain stable throughout the bar's progression
Multi-Modal Direction Detection: Four distinct modes for determining TP/SL positioning - Trend Following (EMA-based), Bullish Only, Bearish Only, and real-time Candle Based
Real-Time Candle Flipping: In Candle Based mode, TP/SL levels flip immediately when the current candle changes from bullish to bearish or vice versa
Persistent Line Management: Uses efficient line object management to prevent ghost lines and maintain clean visual presentation
Flexible Base Price Selection: Choose between Open (static), Close (dynamic), or midpoint (H+L)/2 for entry level calculation
How The Algorithm Works:
ATR Calculation: Captures ATR value at each bar open using specified length parameter, maintaining consistency throughout the bar
Direction Determination: Uses different methods based on selected mode - EMA crossover for trend following, or real-time candle color for dynamic positioning
Level Calculation: TP level = Base Price + (Direction × TP Multiplier × ATR), SL level = Base Price - (Direction × SL Multiplier × ATR)
Visual Management: Creates persistent line objects once, then updates their positions every bar for optimal performance
Direction Modes Explained:
Trend Following: Uses 5-period and 12-period EMA relationship to determine trend direction (locked at bar open)
Bullish Only: Always places TP above and SL below entry (traditional long setup)
Bearish Only: Always places TP below and SL above entry (traditional short setup)
Candle Based: Dynamically adjusts based on current candle direction - flips in real-time as candle develops
Key Input Parameters:
ATR Length: Period for ATR calculation (default 14) - longer periods provide smoother volatility measurement
TP Multiplier: Take profit distance as multiple of ATR (default 1.0) - higher values target larger profits
SL Multiplier: Stop loss distance as multiple of ATR (default 1.0) - higher values allow more room for price movement
Base Price: Reference point for level calculations - Open for static entry, Close for dynamic tracking
Direction Mode: Method for determining whether TP goes above or below entry level
How To Use This Indicator:
For Position Sizing: Use the displayed SL distance to calculate appropriate position size based on your risk tolerance
For Entry Timing: Wait for price to approach the entry level before taking positions
For Risk Management: Set your actual stop loss orders at or near the displayed SL level
For Profit Taking: Use the TP level as initial profit target, consider scaling out at this level
Mode Selection: Choose Candle Based for scalping and quick reversals, Trend Following for swing trading
Visual Style Customization:
Line Colors: Customize TP line color (default teal) and SL line color (default orange) for easy identification
Line Widths: Adjust TP/SL line thickness (1-5) and entry line thickness (1-3) for visibility preferences
Clean Display: Lines extend 3 bars forward from current bar and update position dynamically
Best Practices:
Use on clean charts without multiple overlapping indicators for clearest visual interpretation
Combine with volume analysis and key support/resistance levels for enhanced decision making
Adjust ATR length based on your trading timeframe - shorter for scalping, longer for position trading
Test different TP/SL multipliers based on the volatility characteristics of your chosen instruments
Consider using Trend Following mode during strong trending periods and Candle Based during ranging markets
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ADR/ATR Session by LK## **Features**
1. **Custom ADR & ATR Calculation**
* Calculates **Average Daily Range (ADR)** and **Average True Range (ATR)** separately for:
* **Session timeframe** (default H4 / 06:00–13:00)
* **Daily timeframe**
* Independent smoothing method selection (**SMA, EMA, RMA, WMA**) for H4 ADR, H4 ATR, Daily ADR, and Daily ATR.
2. **Percentage Metrics**
* % of ADR / ATR covered by the **current H4 bar**.
* ADR / ATR expressed as a percentage of the **current price**.
* % of ADR already reached for the **current day**.
* % of Daily ATR vs current day’s True Range.
3. **Dynamic Chart Lines**
* Draws **3 lines for H4**: Session Open, ADR High, ADR Low.
* Draws **3 lines for Daily**: Daily Open, ADR High, ADR Low.
* Lines **extend to the right** so they stay visible across the chart.
* Colors and widths are fully customizable.
4. **Real-Time Data Table**
* Compact table displaying all ADR/ATR values and percentages.
* Adjustable table font size (**tiny, small, normal, large, huge**).
* Transparent background option for minimal chart obstruction.
5. **Flexible Session Settings**
* Select session start and end time in hours/minutes.
* Choose session timezone (chart timezone or major financial centers).
* Toggle H4 lines, Daily lines separately.
6. **Lookahead Control**
* Option to wait for higher-timeframe candle close before updating values (more accurate, less repainting).
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## **How to Use**
### **1. Adding the Indicator**
* Copy and paste the Pine Script into TradingView’s Pine Editor.
* Click **“Add to chart”**.
* Make sure your chart supports the higher timeframes you choose (e.g., H4 and Daily).
### **2. Setting Your Session**
* **Session Start Hour** & **End Hour** → Defines the intraday session to measure ADR/ATR (default: 06:00–13:00).
* **Session Timezone** → Pick “Chart” or a major financial center (e.g., New York, London, Tokyo).
### **3. Choosing Smoothing Methods**
* For each ADR/ATR (H4 and Daily), choose:
* SMA (Simple)
* EMA (Exponential)
* RMA (Wilder’s smoothing)
* WMA (Weighted)
### **4. Adjusting Chart Display**
* **Show H4 Lines** → Displays session open and ADR High/Low for the current H4 session.
* **Show Daily Lines** → Displays daily open and ADR High/Low.
* Customize line colors and widths.
### **5. Reading the Table**
* **H4 Section**
* ADR / ATR values for the selected session.
* % of ADR/ATR covered by the **current H4 bar**.
* ADR/ATR as % of the current price.
* **Daily Section**
* ADR / ATR for the daily timeframe.
* % of ADR already covered by today’s range.
* ADR/ATR as % of price.
### **6. Pro Tips**
* Use **H4 ADR %** to gauge intraday exhaustion — if current range is near 100%, market may slow or reverse.
* Use **Daily ADR %** for swing trade context — if a day has moved beyond its ADR, expect lower continuation probability.
* Combine with support/resistance to identify high-probability reversal zones.
Position Size Calculator (Fixed % or ATR-based Stop Support)Position Size Calculator (Fixed % or ATR-based Stop Support)
Purpose and Background
This indicator allows traders to calculate appropriate position sizes directly on the chart, based on a key rule:
“What percentage of your capital are you willing to risk per trade?”
While many traders focus on entries and indicators, position sizing and risk allocation are often overlooked.
This tool visualizes and simplifies the “1% risk rule” promoted by IBD (Investor’s Business Daily) and William J. O’Neil, helping both beginners and experienced traders maintain disciplined capital management.
Key Features
Automatically calculates and displays:
・ Position Size
The number of units (shares, contracts, coins) you can hold based on your stop-loss range and risk allowance.
・ Stop Price
The price level at which your stop-loss would be triggered.
・ Risk Amount
The maximum loss per trade based on your portfolio size and risk percentage.
Two stop-loss modes available:
・ Fixed % Mode
O’Neil suggests using up to 8% stop-loss in uptrends and keeping it tighter (around 4%) in corrections. This mode allows flexible manual settings.
・ ATR-Based Mode
Uses the asset’s average volatility to dynamically calculate stop-loss width using the Average True Range (ATR).
ATR Usage and Recommended Settings
ATR helps you avoid noise-based stop-outs and align your risk with market volatility.
There are two parameters you can adjust:
・ ATR Length
Defines how many bars are used to calculate the average range.
・Shorter values (5–10) respond faster for day trades
・Longer values (14–21) offer smoother ranges for swing/position trades(Default is 14)
・ATR Multiplier
Sets how wide the stop-loss is by multiplying the ATR value:
・Day trading: 1.0–1.5×
・Swing trading: 1.5–2.5×
・Position trading: 2.0–3.0×
Practical Examples: Risk % × Stop-Loss % → Max Positions
This tool helps estimate how many positions you can hold in a portfolio based on your risk per trade and stop width.
Examples:
・Risk 0.5%, Stop 8% → Max 16 positions
・Risk 0.5%, Stop 4% → Max 8 positions
・Risk 1.0%, Stop 8% → Max 8 positions
・Risk 1.0%, Stop 4% → Max 4 positions
・Risk 2.0%, Stop 8% → Max 4 positions
・Risk 2.0%, Stop 4% → Max 2 positions
These assume worst-case scenarios where all positions are stopped out simultaneously within your overall portfolio risk limit.
Display & Customization Options
・ Currency Display: USD or JPY
No currency conversion is applied. Select based on your trading region (e.g., USD for U.S. stocks, JPY for Japanese stocks).
Support for additional currencies can be added upon request.
・ Show/Hide Decimal Places
Toggle decimals for better visibility. Ideal for fractional assets like crypto and CFDs.
・ Position of Output
Choose from top-right, middle-right, or bottom-right on the chart.
・ Text Display Size: Large / Normal / Small
Choose the table size that best suits your viewing preferences.
・ Explanation of Displayed Labels
・ Position Size : Units to buy/sell based on risk
・ Stop Price : Price where stop-loss is triggered
・ Risk Amount : Max loss allowed for the trade
How to Use
１、Set your Portfolio Size
２、Choose your Currency (USD or JPY)
３、Input Risk per Trade (%) (e.g., 1%)
４、Select Stop Loss Method
・ Fixed % : Enter a manual stop-loss percent (e.g., 8%)
・ ATR : Then also enter:
・ ATR Length : Number of bars used to calculate ATR (e.g., 14)
・ ATR Multiplier : Factor applied to ATR to determine stop-loss (e.g., 2.0)
５、Adjust decimals, label position, or text size as needed
６、The result is displayed in a table directly on your chart
Notes
・ Uses the current close price (close) as the basis
Real-time bid/ask data isn't available in Pine Script, so the close price is used for consistent results.
・ No buy/sell signals are generated
This tool is for position sizing and risk calculation only, not trade entries.
Recommended For
・Traders who want precise, rule-based position sizing
・Users following IBD or O’Neil’s 1% risk principle
・Those incorporating ATR for stop-loss strategies
・Multi-asset traders (stocks, crypto, CFDs, etc.)
・ Anyone who wants to calculate position size and risk without using a calculator or external tool—fully inside TradingView
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.
The Ultimate ATR-BBW Market Volatility Indicator"The ATR-BBW Market Volatility Indicator combines the Average True Range (ATR) and Bollinger Bands Width (BBW) to provide a measure of market volatility. This indicator does not indicate bullish or bearish trends, but rather the magnitude of price fluctuations.
* Usage: When the indicator moves upward, it suggests increasing market volatility, indicating that prices are moving within a wider range. Conversely, a downward movement implies decreasing volatility, signifying that prices are moving within a narrower range.
* Note: This sub-indicator solely reflects market volatility and does not provide buy or sell signals.
Investing involves risk. Please conduct thorough research before making any investment decisions.
ATR and BBW Explained:
* Average True Range (ATR): ATR is a technical analysis indicator used to measure market volatility. It calculates the average of a series of true ranges, where the true range is the greatest of the following:
* The current high minus the current low
* The absolute value of the current high minus the previous close
* The absolute value of the current low minus the previous close
* A higher ATR value indicates higher volatility, while a lower value suggests lower volatility.
* Bollinger Bands Width (BBW): Bollinger Bands are plotted two standard deviations above and below a simple moving average. BBW measures the distance between the upper and lower bands. A wider BBW indicates higher volatility, as prices are moving further away from the moving average. Conversely, a narrower BBW suggests lower volatility.
Combining ATR and BBW:
By combining ATR and BBW, the ATR-BBW indicator provides a more comprehensive view of market volatility. ATR captures the overall volatility of the market, while BBW measures the volatility relative to the moving average. Together, they provide a more robust indicator of market conditions and can be used to identify potential trading opportunities.
Why ATR and BBW are Effective for Measuring Volatility:
* ATR directly measures the actual price movement, regardless of the direction.
* BBW shows how much prices are deviating from their average, indicating the strength of the current trend.
* Combined: By combining these two measures, the ATR-BBW indicator provides a more comprehensive and accurate assessment of market volatility.
In essence, the ATR-BBW indicator helps traders understand the magnitude of price fluctuations, allowing them to make more informed trading decisions.
ALT - ATR Percent Rank🔵 Description
The "ALT - ATR Percent Rank" indicator is a financial analysis tool designed to assess the volatility of an asset relative to its historical behavior, using the Average True Range (ATR) metric.
🔵 Purpose
The indicator aims to provide traders with insights into how the current volatility of an asset compares to its past levels. By evaluating the Percent Rank of the ATR, traders can determine if the current ATR value is high or low in the context of a specified historical period.
🔵 Functionality
• Asset and Timeframe Flexibility
Selectable Asset: Users can choose to apply the indicator to a different asset than the one currently displayed on the chart. This is particularly useful for comparing the volatility of multiple assets without switching charts.
Customizable Timeframe: The indicator can be set to analyze the ATR on different timeframes, regardless of the chart's current timeframe. This allows for multi-timeframe analysis without changing the view of the current chart.
• ATR Calculation
The Average True Range (ATR) is calculated over a user-defined number of bars (ATR Length). ATR is a commonly used measure of volatility that captures the degree of price movement per bar.
REF: Average True Range (ATR) Calculation
• Percent Rank Analysis
The indicator computes the Percent Rank of the current ATR value based on a specified lookback period (Percent Rank Lookback). This tells users how the current ATR compares to ATR values over the recent past, expressed as a percentile. For example, a Percent Rank of 90% indicates that the current ATR is higher than 90% of its values over the chosen lookback period, suggesting higher volatility.
• Visualization
The result is plotted as a line on a separate panel below the main trading chart, making it easy to view changes in volatility relative to historical levels.
🔵 Use Cases
• Trend Confirmation
Traders might use the indicator to confirm if a price movement is backed by significant volatility changes, which could validate the strength of a trend.
• Risk Management
Understanding when an asset is experiencing unusually high or low volatility could help in adjusting trading strategies, such as altering position sizes or setting stop-loss orders.
• Comparative Analysis
By enabling the analysis of different assets or timeframes, traders can perform comparative volatility studies, which can be essential in portfolio management or when seeking diversification opportunities.
This indicator is a valuable tool for traders who rely on volatility analysis to make informed trading decisions, providing a clear, quantifiable measure of how current market conditions compare to historical data.
Focused Average True RangeThe Focused Average True Range (FATR) is a modified version of the classic Average True Range (ATR) indicator. It is designed to provide traders with more accurate data on volatility, minimizing the impact of sharp spikes in volatility.
The main distinction between the Focused ATR and the standard ATR lies in the utilization of percentiles. Instead of calculating the average price change as the regular ATR does, the Focused ATR selects a value in the middle of the range of price changes. This makes it less sensitive to sharp changes in volatility, which can be beneficial in certain trading scenarios.
Settings:
Percentile. This parameter determines which value in the series of price changes will be used. For example, if the percentile is set to 50, the indicator will use the median value of the series of price changes. This is the default value. Imagine a class of students lined up by height, and instead of calculating the average height of all students, we take the height of the students in the middle of the line. Similarly here, we take the ATR from the middle of the series. Increasing the percentile will lead to the use of a value closer to the upper bound of the range, while decreasing the percentile will lead to the use of a value closer to the lower bound.
How to Use:
The Focused ATR is especially useful for determining the sizes of stop-losses and take-profits, thanks to its ability to consider the value in the middle of the series of price changes rather than the average value. This allows traders to more accurately assess volatility and risk, which in turn can assist in optimizing trading strategies
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Фокусированный Средний Истинный Диапазон (Focused ATR) представляет собой модифицированную версию классического индикатора ATR. Он разработан с целью предоставления трейдерам более точных данных о волатильности, минимизируя влияние резких скачков волатильности.
Основное отличие Фокусированного ATR от стандартного ATR заключается в использовании процентиля. Вместо того, чтобы рассчитывать среднее значение изменений цены, как это делает обычный ATR, Фокусированный ATR выбирает значение в середине диапазона изменений цены. Это делает его менее чувствительным к резким изменениям волатильности, что может быть полезно в некоторых торговых сценариях.
Настройки:
Процентиль. Этот параметр определяет, какое значение в ряду изменений цены будет использоваться. Например, если процентиль равен 50, то индикатор будет использовать медианное значение ряда изменений цены. Это стандартное значение. Представьте себе, что ученики класса выстроились по росту, и мы считаем не средний рост всех учеников, а берем рост учеников из середины колонны. Так и тут. Мы берем ATR из середины ряда. Увеличение процентиля приведет к использованию значения, ближе к верхней границе диапазона, в то время как уменьшение процентиля приведет к использованию значения, ближе к нижней границе.
Как использовать:
Фокусированный ATR особенно полезен для определения размеров стоп-лоссов и тейк-профитов, благодаря своей способности учитывать значение в середине ряда изменений цены, а не среднее значение. Это позволяет трейдерам более точно оценить волатильность и риск, что в свою очередь может помочь в оптимизации торговых стратегий.
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Volume Profile Auto POC📌 Overview
Volume Profile Auto POC is a trend-following strategy that uses the automatically calculated Point of Control (POC) from the volume profile, combined with ATR zones, to capture reversals and breakouts.
By basing decisions on volume concentration, it dynamically visualizes the price levels most watched by market participants.
⚠️ This strategy is provided for educational and research purposes only.
Past performance does not guarantee future results.
🎯 Strategy Objectives
Automatically detect the volume concentration area (POC) to improve entry accuracy
Optimize risk management through ATR-based volatility adjustment
Provide early and consistent signals when trends emerge
✨ Key Features
Automatic POC Detection : Updates the volume profile over a defined lookback window in real time
ATR Zone Integration : Defines a POC ± 0.5 ATR zone to clarify potential reversals/breakouts
Visual Support : Plots the POC line and zones on the chart for intuitive decision-making
📊 Trading Rules
Long Entry:
Price breaks above the POC + 0.5 ATR zone
Volume is above average to support the breakout
Short Entry:
Price breaks below the POC - 0.5 ATR zone
Volume is above average to support the downside move
Exit (or Reverse Position):
Price returns to the POC area
Or touches the ATR band
⚙️ Trading Parameters & Considerations
Indicator Name: Volume Profile Auto POC
Parameters:
Lookback Bars: 50
Bins for Volume Profile: 24
ATR Length: 14
ATR Multiplier: 2.0
🖼 Visual Support
POC line plotted in red
POC ± 0.5 ATR zone displayed as a semi-transparent box
ATR bands plotted in blue for confirmation
🔧 Strategy Improvements & Uniqueness
This strategy is inspired by traditional Volume Profile + ATR analysis,
while adding the improvement of a sliding-window mechanism for automatic POC updates.
Compared with conventional trend-following approaches,
its strength lies in combining both price and volume perspectives for decision-making.
✅ Summary
Volume Profile Auto POC automatically extracts key market levels (POC) and combines them with ATR-based zones,
providing a responsive trend-following method.
It balances clarity with practicality, aiming for both usability and reproducibility.
⚠️ This strategy is based on historical data and does not guarantee future profits.
Always use proper risk management when applying it.
Weekly/Monthly Golden ATR LevelsWeekly/Monthly Golden ATR Levels
This indicator is designed to give traders a clear, rule-based framework for identifying support and resistance zones anchored to prior period ranges and the market’s own volatility. It uses the Average True Range (ATR) as a measure of how far price can realistically stretch, then projects fixed levels from the midpoint of the prior week and prior month.
Rather than “moving targets” that repaint, these levels are frozen at the start of each new week and month and stay fixed until the next period begins. This makes them reliable rails for both intraday and swing trading.
What It Plots
Weekly Midpoint (last week’s High + Low ÷ 2)
From this mid, the script projects:
Weekly +1 / −1 ATR
Weekly +2 / −2 ATR
Monthly Midpoint (last month’s High + Low ÷ 2)
From this mid, the script projects:
Monthly +1 / −1 ATR
Monthly +2 / −2 ATR
Customization
Set ATR length & timeframe (default: 14 ATR on Daily bars).
Adjust multipliers for Level 1 (±1 ATR) and Level 2 (±2 ATR).
Choose line color, style, and width separately for weekly and monthly bands.
Toggle labels on/off.
How to Use
Context at the Open
If price opens above last week’s midpoint, bias favors upside toward +1 / +2.
If price opens below the midpoint, bias favors downside toward −1 / −2.
Weekly Bands = Short-Term Rails
+1 / −1 ATR: Rotation pivots. Expect intraday reaction.
+2 / −2 ATR: Extreme stretch zones. Reversals or breakouts often occur here.
Monthly Bands = Big Picture Rails
Use these for swing positioning, or as “outer guardrails” on intraday charts.
When weekly and monthly bands cluster → high-confluence zone.
Trade Playbook
Trend Day: Hold above +1 → target +2. Break below −1 → target −2.
Range Day: Fade first test of ±2, scalp toward ±1 or midpoint.
Catalyst/News Day: Use with caution—levels provide context, not barriers.
Risk Management
Place stops just outside the band you’re trading against.
Scale profits at the next inner level (e.g., short from +2, cover partial at +1).
Runners can trail to the midpoint or opposite side.
Why It Works
ATR measures volatility—how far price tends to travel in a given period.
Anchoring to prior highs and lows captures where real supply/demand last clashed.
Combining the two gives levels that are statistically relevant, widely observed, and psychologically sticky.
Trading books from Mark Douglas (Trading in the Zone), Jared Tendler (The Mental Game of Trading), and Oliver Kell (Victory in Stock Trading) all stress the importance of having objective, repeatable reference points. These levels deliver that discipline—removing guesswork and reducing emotional trading
Adaptive ATR Trailing Stops█ Introduction
This script is based on the average true range (ATR) and has been improved with the HHV or LLV. The script supports the trader to have his stoploss trailed. In this case, the stoploss is dynamic and can be adjusted with each candleclose.
█ What Does This Indicator Do?
The ATR SL Trailing Indicator helps you dynamically adjust your stop-loss levels based on market movements. It uses market volatility to calculate trailing stop-loss levels, ensuring you can secure profits or minimize losses. The indicator creates two lines:
A green/red line for long positions (when you’re betting on prices going up).
A green/red line for short positions (when you’re betting on prices going down).
█ Key Concepts: How Does the Indicator Work?
The Average True Range (ATR) measures market volatility, showing how much the price moves over a specific period.
A high ATR indicates a volatile market (large price swings), while a low ATR indicates a quiet market (smaller price changes).
Why is ATR important? ATR helps dynamically adjust the distance between your stop-loss and the current price. In volatile markets, the stop-loss is placed further away to avoid being triggered by short-term fluctuations. In quieter markets, the stop-loss is set closer to the price.
The HHV is the highest price over a specific period. For long positions, the indicator uses the highest price minus an ATR-based value to determine the stop-loss level.
Why is HHV important? HHV ensures the stop-loss for long positions only moves up when the price reaches new highs. Once the price starts falling, the stop-loss remains unchanged to lock in profits or minimize losses.
The LLV is the lowest price over a specific period. For short positions, the indicator uses the lowest price plus an ATR-based value to determine the stop-loss level.
Why is LLV important? LLV ensures the stop-loss for short positions only moves down when the price reaches new lows. Once the price starts rising, the stop-loss remains unchanged to lock in profits or minimize losses.
█ How Does the Indicator Work?
For Long Positions:
The indicator sets the stop-loss below the current price, based on:
Market volatility (ATR).
The highest price over a specific period (HHV).
The line turns green when the current price is above the stop-loss.
The line turns red when the price drops below the stop-loss, signaling you may need to exit the trade.
For Short Positions:
The indicator sets the stop-loss above the current price, based on:
*Market volatility (ATR).
*The lowest price over a specific period (LLV).
*The line turns green when the current price is below the stop-loss.
*The line turns red when the price moves above the stop-loss, signaling you may need to exit the trade.
█ Advantages of the ATR SL Trailing Indicator
*Dynamic and adaptive: Automatically adjusts stop-loss levels based on market volatility.
*Visual clarity: Green and red lines clearly indicate whether your position is safe or at risk.
*Effective risk management: Helps you lock in profits and minimize losses without the need for constant manual adjustments.
█ When Should You Use This Indicator?
*If you practice trend-based trading and want your stop-losses to automatically adapt to market movements.
*In volatile markets, to avoid being stopped out by short-term fluctuations.
*When you want to implement efficient risk management without manually adjusting your positions.
█ Inputs
The user can set the indicator for both longs and shorts. This is particularly important because the calculation is different. The HHV is used for longs and the LLV for shorts. The user can therefore set the period/length for the ATR on the one hand and the HHV/LLV on the other. He also has a multiplier, which can also be customized. The multiplier multiplies the price change of each individual candle.
█ Color Change
If the SL is trailed and the price breaks a line, the color changes. In this case, it would have executed the SL on an open trade.
Intramarket Difference Index StrategyHi Traders !!
The IDI Strategy:
In layman’s terms this strategy compares two indicators across markets and exploits their differences.
note: it is best the two markets are correlated as then we know we are trading a short to long term deviation from both markets' general trend with the assumption both markets will trend again sometime in the future thereby exhausting our trading opportunity.
📍 Import Notes:
This Strategy calculates trade position size independently (i.e. risk per trade is controlled in the user inputs tab), this means that the ‘Order size’ input in the ‘Properties’ tab will have no effect on the strategy. Why ? because this allows us to define custom position size algorithms which we can use to improve our risk management and equity growth over time. Here we have the option to have fixed quantity or fixed percentage of equity ATR (Average True Range) based stops in addition to the turtle trading position size algorithm.
‘Pyramiding’ does not work for this strategy’, similar to the order size input togeling this input will have no effect on the strategy as the strategy explicitly defines the maximum order size to be 1.
This strategy is not perfect, and as of writing of this post I have not traded this algo.
Always take your time to backtests and debug the strategy.
🔷 The IDI Strategy:
By default this strategy pulls data from your current TV chart and then compares it to the base market, be default BINANCE:BTCUSD . The strategy pulls SMA and RSI data from either market (we call this the difference data), standardizes the data (solving the different unit problem across markets) such that it is comparable and then differentiates the data, calling the result of this transformation and difference the Intramarket Difference (ID). The formula for the the ID is
ID = market1_diff_data - market2_diff_data (1)
Where
market(i)_diff_data = diff_data / ATR(j)_market(i)^0.5,
where i = {1, 2} and j = the natural numbers excluding 0
Formula (1) interpretation is the following
When ID > 0: this means the current market outperforms the base market
When ID = 0: Markets are at long run equilibrium
When ID < 0: this means the current market underperforms the base market
To form the strategy we define one of two strategy type’s which are Trend and Mean Revesion respectively.
🔸 Trend Case:
Given the ‘‘Strategy Type’’ is equal to TREND we define a threshold for which if the ID crosses over we go long and if the ID crosses under the negative of the threshold we go short.
The motivating idea is that the ID is an indicator of the two symbols being out of sync, and given we know volatility clustering, momentum and mean reversion of anomalies to be a stylised fact of financial data we can construct a trading premise. Let's first talk more about this premise.
For some markets (cryptocurrency markets - synthetic symbols in TV) the stylised fact of momentum is true, this means that higher momentum is followed by higher momentum, and given we know momentum to be a vector quantity (with magnitude and direction) this momentum can be both positive and negative i.e. when the ID crosses above some threshold we make an assumption it will continue in that direction for some time before executing back to its long run equilibrium of 0 which is a reasonable assumption to make if the market are correlated. For example for the BTCUSD - ETHUSD pair, if the ID > +threshold (inputs for MA and RSI based ID thresholds are found under the ‘‘INTRAMARKET DIFFERENCE INDEX’’ group’), ETHUSD outperforms BTCUSD, we assume the momentum to continue so we go long ETHUSD.
In the standard case we would exit the market when the IDI returns to its long run equilibrium of 0 (for the positive case the ID may return to 0 because ETH’s difference data may have decreased or BTC’s difference data may have increased). However in this strategy we will not define this as our exit condition, why ?
This is because we want to ‘‘let our winners run’’, to achieve this we define a trailing Donchian Channel stop loss (along with a fixed ATR based stop as our volatility proxy). If we were too use the 0 exit the strategy may print a buy signal (ID > +threshold in the simple case, market regimes may be used), return to 0 and then print another buy signal, and this process can loop may times, this high trade frequency means we fail capture the entire market move lowering our profit, furthermore on lower time frames this high trade frequencies mean we pay more transaction costs (due to price slippage, commission and big-ask spread) which means less profit.
By capturing the sum of many momentum moves we are essentially following the trend hence the trend following strategy type.
Here we also print the IDI (with default strategy settings with the MA difference type), we can see that by letting our winners run we may catch many valid momentum moves, that results in a larger final pnl that if we would otherwise exit based on the equilibrium condition(Valid trades are denoted by solid green and red arrows respectively and all other valid trades which occur within the original signal are light green and red small arrows).
another example...
Note: if you would like to plot the IDI separately copy and paste the following code in a new Pine Script indicator template.
indicator("IDI")
// INTRAMARKET INDEX
var string g_idi = "intramarket diffirence index"
ui_index_1 = input.symbol("BINANCE:BTCUSD", title = "Base market", group = g_idi)
// ui_index_2 = input.symbol("BINANCE:ETHUSD", title = "Quote Market", group = g_idi)
type = input.string("MA", title = "Differrencing Series", options = , group = g_idi)
ui_ma_lkb = input.int(24, title = "lookback of ma and volatility scaling constant", group = g_idi)
ui_rsi_lkb = input.int(14, title = "Lookback of RSI", group = g_idi)
ui_atr_lkb = input.int(300, title = "ATR lookback - Normalising value", group = g_idi)
ui_ma_threshold = input.float(5, title = "Threshold of Upward/Downward Trend (MA)", group = g_idi)
ui_rsi_threshold = input.float(20, title = "Threshold of Upward/Downward Trend (RSI)", group = g_idi)
//>>+----------------------------------------------------------------+}
// CUSTOM FUNCTIONS |
//<<+----------------------------------------------------------------+{
// construct UDT (User defined type) containing the IDI (Intramarket Difference Index) source values
// UDT will hold many variables / functions grouped under the UDT
type functions
float Close // close price
float ma // ma of symbol
float rsi // rsi of the asset
float atr // atr of the asset
// the security data
getUDTdata(symbol, malookback, rsilookback, atrlookback) =>
indexHighTF = barstate.isrealtime ? 1 : 0
= request.security(symbol, timeframe = timeframe.period,
expression = [close , // Instentiate UDT variables
ta.sma(close, malookback) ,
ta.rsi(close, rsilookback) ,
ta.atr(atrlookback) ])
data = functions.new(close_, ma_, rsi_, atr_)
data
// Intramerket Difference Index
idi(type, symbol1, malookback, rsilookback, atrlookback, mathreshold, rsithreshold) =>
threshold = float(na)
index1 = getUDTdata(symbol1, malookback, rsilookback, atrlookback)
index2 = getUDTdata(syminfo.tickerid, malookback, rsilookback, atrlookback)
// declare difference variables for both base and quote symbols, conditional on which difference type is selected
var diffindex1 = 0.0, var diffindex2 = 0.0,
// declare Intramarket Difference Index based on series type, note
// if > 0, index 2 outpreforms index 1, buy index 2 (momentum based) until equalibrium
// if < 0, index 2 underpreforms index 1, sell index 1 (momentum based) until equalibrium
// for idi to be valid both series must be stationary and normalised so both series hae he same scale
intramarket_difference = 0.0
if type == "MA"
threshold := mathreshold
diffindex1 := (index1.Close - index1.ma) / math.pow(index1.atr*malookback, 0.5)
diffindex2 := (index2.Close - index2.ma) / math.pow(index2.atr*malookback, 0.5)
intramarket_difference := diffindex2 - diffindex1
else if type == "RSI"
threshold := rsilookback
diffindex1 := index1.rsi
diffindex2 := index2.rsi
intramarket_difference := diffindex2 - diffindex1
//>>+----------------------------------------------------------------+}
// STRATEGY FUNCTIONS CALLS |
//<<+----------------------------------------------------------------+{
// plot the intramarket difference
= idi(type,
ui_index_1,
ui_ma_lkb,
ui_rsi_lkb,
ui_atr_lkb,
ui_ma_threshold,
ui_rsi_threshold)
//>>+----------------------------------------------------------------+}
plot(intramarket_difference, color = color.orange)
hline(type == "MA" ? ui_ma_threshold : ui_rsi_threshold, color = color.green)
hline(type == "MA" ? -ui_ma_threshold : -ui_rsi_threshold, color = color.red)
hline(0)
Note it is possible that after printing a buy the strategy then prints many sell signals before returning to a buy, which again has the same implication (less profit. Potentially because we exit early only for price to continue upwards hence missing the larger "trend"). The image below showcases this cenario and again, by allowing our winner to run we may capture more profit (theoretically).
This should be clear...
🔸 Mean Reversion Case:
We stated prior that mean reversion of anomalies is an standerdies fact of financial data, how can we exploit this ?
We exploit this by normalizing the ID by applying the Ehlers fisher transformation. The transformed data is then assumed to be approximately normally distributed. To form the strategy we employ the same logic as for the z score, if the FT normalized ID > 2.5 (< -2.5) we buy (short). Our exit conditions remain unchanged (fixed ATR stop and trailing Donchian Trailing stop)
🔷 Position Sizing:
If ‘‘Fixed Risk From Initial Balance’’ is toggled true this means we risk a fixed percentage of our initial balance, if false we risk a fixed percentage of our equity (current balance).
Note we also employ a volatility adjusted position sizing formula, the turtle training method which is defined as follows.
Turtle position size = (1/ r * ATR * DV) * C
Where,
r = risk factor coefficient (default is 20)
ATR(j) = risk proxy, over j times steps
DV = Dollar Volatility, where DV = (1/Asset Price) * Capital at Risk
🔷 Risk Management:
Correct money management means we can limit risk and increase reward (theoretically). Here we employ
Max loss and gain per day
Max loss per trade
Max number of consecutive losing trades until trade skip
To read more see the tooltips (info circle).
🔷 Take Profit:
By defualt the script uses a Donchain Channel as a trailing stop and take profit, In addition to this the script defines a fixed ATR stop losses (by defualt, this covers cases where the DC range may be to wide making a fixed ATR stop usefull), ATR take profits however are defined but optional.
ATR SL and TP defined for all trades
🔷 Hurst Regime (Regime Filter):
The Hurst Exponent (H) aims to segment the market into three different states, Trending (H > 0.5), Random Geometric Brownian Motion (H = 0.5) and Mean Reverting / Contrarian (H < 0.5). In my interpretation this can be used as a trend filter that eliminates market noise.
We utilize the trending and mean reverting based states, as extra conditions required for valid trades for both strategy types respectively, in the process increasing our trade entry quality.
🔷 Example model Architecture:
Here is an example of one configuration of this strategy, combining all aspects discussed in this post.
Future Updates
- Automation integration (next update)
Advanced EMA Cross with Normalized ATR Filter, Controlling ADX
Description:
This strategy is based on EMA cross strategy and additional filters are used to get better results, a normalized ATR filter, and ADX control...
It aims to provide traders with a code base that generates signals for long positions based on market conditions defined by various indicators.
How it Works:
1. EMA: Uses short (8 periods) and long (20 periods) EMAs to identify crossovers.
2. ATR: Uses a 14-period ATR, normalized to its 20-period historical range, to filter out noise.
3. ADX: Uses a 14-period RMA to identify strong trends.
4. Volume: Filters trades based on a 14-period SMA of volume.
5. Super Trend: Uses a Super Trend indicator to identify the market direction.
How to Use:
- Buy Signal: Generated when EMA short crosses above EMA long, and other conditions like ATR and market direction are met.
- Sell Signal: Generated based on EMA crossunder and high ADX value.
Originality and Usefulness:
This script combines EMA, ATR, ADX, and Super Trend indicators to filter out false signals and identify more reliable trading opportunities.
USD Strength in the code is not working, just simulated it as PSEUDO CODE:
Strategy Results:
- Account Size: $1000
- Commission: Not considered
- Slippage: Not considered
- Risk: Manageable through parameters, now less than 5% per trade
- Dataset: Aim for more than 100 trades for a sufficient sample size
- Test Conditions: Test in 30 min chart for BTCUSDT
IMPORTANT NOTE: This script should be used for educational purposes and should not be considered as financial advice.
Chart:
- The script's output is plotted as Buy and Sell signals on the chart.
- No other scripts are included for clarity.
- Have tested with 30mins period
- You are encouraged to play with parameters, let me know if it helps you and/or if you can upgrade the code to a better level.
WHY DID I USE ATR AND ADX?
ATR filter is usually used for the following purposes.
Market Volatility: ATR measures how volatile the market is. High ATR values indicate that the price is experiencing significant fluctuations.
Filtering: Crossing a certain ATR threshold may indicate that the market is active enough to present trading opportunities.
Risk Management: ATR can also be used to set stop-loss and take-profit levels, helping to manage risk effectively.
And ADX is usually used for;
Trend Strength: ADX measures the strength of a trend. High ADX values indicate a strong trend.
Filtering: An ADX value above a certain level suggests that the trend is strong and it might be safer to trade.
Versatility: ADX does not indicate the direction of the trend, only its strength. This makes it useful in both bullish and bearish markets.
Using these indicators together can help filter out false signals and produce more reliable trading signals. While ATR helps to determine if the market is active enough, ADX measures the strength of the trend. Combined, they can create a more complex and effective trading strategy.
I've used ADX data to support generating a buy signal after a golden cross (bullish trend) and waiting until this is a strong trend. It sounds good to check for different trend strengths for bullish and bearish markets to decide a buy signal. Additionally I used ATR to check if the market has enough fluctuations.
[JL] Fractals ATR BlockI decided to combine Fractal ROC , ATR Break, and Order Blocks to an Indicator
The Fractal ROC , ATR Break, and Order Blocks indicator combines three concepts to help traders identify potential trade opportunities and manage risk. By using a combination of Fractal ROC , ATR Break, and Order Blocks, traders can gain a deeper understanding of market dynamics and make more informed trading decisions.
Fractal ROC is a momentum-based indicator that calculates the rate of change of the price between fractals, which are turning points in the market. It is calculated by taking the difference between the closing price and the lowest price in the previous n+1 periods, and dividing it by the difference between the open price 2n periods ago and the lowest price in the previous n+1 periods. This calculation is done for both up and down fractals. When the Fractal ROC value is greater than the ROC Break Level (as determined by the input variable roclevel), it indicates a potential momentum shift in the market. This can be used to identify potential trade entries or exits, depending on your trading strategy.
ATR Break is an indicator that helps traders identify significant price movements in the market. It measures the distance between the price and the Average True Range (ATR), which is a measure of the volatility of the market. ATR Break is calculated by taking the difference between the close and high/low, and dividing it by the previous ATR value. This calculation is done for both up and down movements. When the ATR Break value is greater than the ATR Break Level (as determined by the input variable atrlevel), it indicates a significant move in the market. This can be used to identify potential breakouts or breakdowns, and can be used to set stop-loss and take-profit levels.
An Order Block is a price level where significant buying or selling activity has taken place. The order blocks made by ATR Break and Fractal ROC are drawn using boxes on the chart. When the ATR or Fractal ROC level is breached, a box is drawn with the high and low of the candle that breached the level as the top and bottom of the box, respectively. The box is then extended to the right until the end of the chart or until another ATR or Fractal ROC level is breached, at which point a new box is drawn. This allows traders to easily identify significant price movements and potential support and resistance levels on the chart. When an Order Block is identified, it can be used as a potential support or resistance level . If price approaches an Order Block from below, it is likely to bounce off this level and continue in an upward direction. Similarly, if price approaches an Order Block from above, it is likely to bounce off this level and continue in a downward direction. Traders can use these levels to identify potential trade entries or exits, as well as to set stop-loss and take-profit levels.
Overall, the Fractal ROC , ATR Break, and Order Blocks indicator is a powerful tool for traders who want to identify potential trade opportunities and manage risk. By combining these three concepts, traders can gain a deeper understanding of market dynamics and make more informed trading decisions. As with any indicator, it is important to use it in conjunction with other analysis tools and to have a clear trading plan in place.
BB SPY Mean Reversion Investment StrategySummary
Mean reversion first, continuation second. This strategy targets equities and ETFs on daily timeframes. It waits for price to revert from a Bollinger location with candle and EMA agreement, then manages risk with ATR based exits. Uniqueness comes from two elements working together. One, an adaptive band multiplier driven by volatility of volatility that expands or contracts the envelope as conditions change. Two, a bias memory that re arms the same direction after any stop, target, or time exit until a true opposite signal appears. Add it to a clean chart, use the markers and levels, and select on bar close for conservative alerts. Shapes can move while the bar is open and settle on close.
Scope and intent
• Markets. Currently adapted for SPY, needs to be optimized for other assets
• Timeframes. Daily primary. Other frames are possible but not the default
• Default demo. SPY on daily
• Purpose. Trade mean reversion entries that can chain into a longer swing by splitting holds into ATR or time segments
Originality and usefulness
• Novelty. Adaptive band width from volatility of volatility plus a persistent bias array that keeps the original direction alive across sequential entries until an opposite setup is confirmed
• Failure modes mitigated. False starts in chop are reduced by candle color and EMA location. Missed continuation after a take profit or stop is addressed by the re arm engine. Oversized envelopes during quiet regimes are avoided by the adaptive multiplier
• Testability. Every module has Inputs and visible levels so users can see why a suggestion appears
• Portable yardstick. All risk and targets are expressed in ATR units
Method overview in plain language
The engine measures where price sits relative to Bollinger bands, confirms with candle color and EMA location, requires ADX for shorts(in our case long close since we use it currently as long only), and optionally requires a trend or mean reversion regime using band width percent rank and basis slope. Risk uses ATR for stop, target, and optional breakeven. A small array stores the last confirmed direction. While flat, the engine keeps a pending order in that direction. The array flips only when a true opposite setup appears.
Base measures
• Range basis. True Range smoothed over a user defined ATR Length
• Return basis. Not required
Components
• Bollinger envelope. SMA length and standard deviation multiplier. Entry is based on cross of close through the band with location bias
• Candle and EMA filter. Close relative to open and close relative to EMA align direction
• ADX gate for shorts. Requires minimum trend strength for short trades
• Adaptive multiplier. Band width scales using volatility of volatility so envelopes breathe with conditions
• Regime gate optional. Band width percent rank and basis slope identify trend or mean reversion regimes
• Risk manager. ATR stop, ATR target, optional breakeven, optional time exit
• Bias memory. Array stores last confirmed direction and re arms entries while flat
Fusion rule
Minimum satisfied gates count style. All required gates must be true. Optional gates are controlled in Inputs. Bias memory never overrides an opposite confirmed setup.
Signal rule
• Long setup when close crosses up through the lower band, the bar closes green, and close is above the long EMA
• Short setup when close crosses down through the upper band, the bar closes red, close is below the short EMA, and ADX is above the minimum
• While flat the model keeps a pending order in the stored direction until a true opposite setup appears
• IN LONG or IN SHORT describes states between entry and exit
What you will see on the chart
• Markers for Long and Short setups
• Exit markers from ATR or time rules
• Reference levels for entry, stop, and target
• Bollinger bands and optional adaptive bands
Inputs with guidance
Setup
• Signal timeframe. Uses the chart timeframe
• Invert direction optional. Flips long and short
Logic
• BB Length. Typical 10 to 50. Higher smooths more
• BB Mult. Typical 1.0 to 2.5. Higher widens entries
• EMA Length long. Typical 10 to 50
• EMA Length short. Typical 5 to 30
• ADX Minimum for short. Typical 15 to 35
Filters
• Regime Type. none or trend or mean reversion
• Rank Lookback. Typical 100 to 300
• Basis Slope Length and Threshold. Larger values reduce false trends
Risk
• ATR Length. Typical 10 to 21
• ATR Stop Mult. Typical 1.0 to 3.0
• ATR Take Profit Mult. Typical 2.0 to 5.0
• Breakeven Trigger R. Move stop to entry after the chosen multiple
• Time Exit. Minimum bars and extension when profit exceeds a fraction of ATR
Bias and rearm
• Bias flips kept. Array depth
• Keep rearm when flat. Maintain a pending order while flat
UI
• Show markers and levels. Clean defaults
Usage recipes
Alerts update in real time and can change while the bar forms. Select on bar close for conservative workflows.
Properties visible in this publication
• Initial capital 25000
• Base currency USD
• If any higher timeframe calls are enabled, request.security uses lookahead off
• Commission 0.03 percent
• Slippage 3 ticks
• Default order size method Percent of equity with value 5
• Pyramiding 0
• Process orders on close On
• Bar magnifier Off
• Recalculate after order is filled Off
• Calc on every tick Off
Realism and responsible publication
No performance claims. Costs and fills vary by venue. Shapes can move intrabar and settle on close. Strategies use standard candles only.
Honest limitations and failure modes
High impact releases and thin liquidity can break assumptions. Gap heavy symbols may require larger ATR. Very quiet regimes can reduce contrast in the mean reversion signal. If stop and target can both be touched inside one bar, outcome follows the TradingView order model for that bar path.
Regimes with extreme one sided trend and very low volatility can reduce mean reversion edges. Results vary by symbol and venue. Past results never guarantee future outcomes.
Open source reuse and credits
None.
Backtest realism
Costs are realistic for liquid equities. Sizing does not exceed five percent per trade by default. Any departure should be justified by the user.
If you got any questions please le me know
Apex Edge Sentinel - Stop Loss HUDApex Edge – ATR Sentinel Stop Loss HUD
The Apex Edge – ATR Sentinel is a complete stop-loss intelligence system built as a clean, always-on HUD.
It delivers institutional-level risk guidance by calculating and displaying live ATR-based stop levels for both long and short trades at multiple risk tolerances.
Forget cluttered charts and repainting lines — Sentinel gives you a clear stop-loss reference panel that updates dynamically with every bar.
✅ Features
• Triple ATR Multipliers
User-defined (e.g. x1.5 / x2.0 / x2.5). Compare tight, medium, and wide stops instantly.
• Dual-Side SL Levels
Both Long and Short safe stop prices displayed side by side. No more guessing trend
bias.
• ATR Transparency
HUD shows ATR(length) so you always know the calculation basis. Default = 14, adjustable
to your style.
• ATR Regime Meter
Detects volatility conditions (LOW / NORMAL / HIGH) by comparing ATR to its SMA. Helps
you avoid over-tight stops in high-volatility markets.
• Tick-Aware Rounding
Stop levels auto-rounded to the instrument’s tick size (Gold = 0.10, FX = 0.0001, indices =
whole points).
Custom HUD Design
• Location: Top/Bottom, Left/Right
• Sizes: Compact / Medium / Large (desktop or mobile)
• Opacity control (25% default Apex styling)
How to Use
1. Load Sentinel on your chart.
2. Check the HUD:
• ATR(14): 2.6 → base volatility measure.
• x1.5 / x2.0 / x2.5 → instant SL levels for both long & short trades.
3. Before entering a trade → decide which multiplier matches your style (tight scalper vs wider swing).
4. Manually place your SL at the level displayed in the HUD.
Sentinel works as both:
• A pre-trade check (is ATR stop too wide for my RR?).
• A live risk compass (updated stop levels every bar).
Why Apex Sentinel?
Most ATR stop indicators clutter charts with lagging lines or repainting trails. Sentinel strips it back to what matters:
• The numbers.
• The risk levels.
• The context.
It’s a pure stop-loss HUD, designed for serious traders who want clarity, discipline, and instant reference points across any market or timeframe.
Notes
• This is a HUD-only system (no automatic SL line). Traders manually apply the SL level
shown in the panel.
• Defaults: ATR(14), multipliers 1.5 / 2.0 / 2.5. Adjust to your trading style.
• Best used on intraday pairs like XAUUSD, EURUSD, indices, but works universally.
Apex Edge Philosophy: Clean. Smart. Institutional.
No clutter. No gimmicks. Just precision tools for modern markets.
Trendline Breakout Strategy [KedArc Quant] Description
A single, rule-based system that builds two trendlines from confirmed swing pivots and trades their breakouts, with optional retest, trend-regime gates (EMA / HTF EMA), and ATR-based risk. All parts serve one decision flow: structure → breakout → gated entry → managed risk.
What it does (for traders)
Draws Up line (teal) through the last two Higher Lows and Down line (red) through the last two Lower Highs, then extends them forward.
Long when price breaks above red; Short when price breaks below teal.
Optional Retest entry: after a break, wait for a pullback toward the broken line within an ATR-scaled buffer.
Uses ATR stop and R-multiple target so risk is consistent across symbols/timeframes.
Labels HL1/HL2/LH1/LH2 so non-coders can verify which pivots built each line.
Why these components are combined
Pure breakout systems on trendlines suffer from three practical issues:
False breaks in chop → solved by trend-regime gates (EMA / HTF EMA) that only allow trades aligned with the prevailing trend.
Uneven volatility across markets/timeframes → solved by ATR-based stop/target, normalizing distance so R-multiples are comparable.
First break whipsaws near wedge apices → mitigated by the optional retest rule that demands a pullback/hold before entry.
These modules are not separate indicators with their own signals. They are support roles inside one method.
The pivot engine defines structure, the breakout detector defines signal, the regime gates decide if we’re allowed to take that signal, and the ATR module sizes risk.
Together they make the trendline breakout usable, testable, and explainable.
How it works (mechanism; each component explained)
1) Pivot engine (structure, non-repainting)
Swings are confirmed with ta.pivotlow/high(L, R). A pivot only exists after R bars (no look-ahead), so once plotted, the line built from those pivots will not repaint.
2) Trendline builder (geometry)
Teal line updates when two consecutive pivot lows satisfy HL2.price > HL1.price (and HL2 occurs after HL1).
Red line updates when two consecutive pivot highs satisfy LH2.price < LH1.price.
Lines are extended right and their current value is read every bar via line.get_price().
3) Breakout detector (signal)
On every bar, compute:
crossover(close, redLine) ⇒ Long breakout
crossunder(close, tealLine) ⇒ Short breakdown
4) Regime gates (trend filters, not separate signals)
EMA gate: allow longs only if close > EMA(len), shorts only if close < EMA(len).
HTF EMA gate (optional): same rule on a higher timeframe to avoid fighting the larger trend.
These do not create entries; they simply permit or block the breakout signal.
5) Retest module (optional confirmation)
After a breakout, record the line price. A valid retest occurs if price pulls back within an ATR-scaled buffer toward that broken line and then closes back in the breakout direction.
This reduces first-tick fakeouts.
6) Risk module (position exit)
Initial stop = ATR(len) × atrMult from entry.
Target = tpR × (ATR × atrMult) (e.g., 2R).
This keeps results consistent across instruments/timeframes.
Entries & exits
Long entry
Base: close breaks above red and passes EMA/HTF gates.
Retest (if enabled): after the break, price pulls back near the broken red line (within the ATR buffer) and holds; then enter.
Short entry
Mirror logic with teal (break below & gates), optionally with a retest.
Exit
strategy.exit places ATR stop & R-multiple target automatically.
Optional “flip”: close if the opposite base signal triggers.
How to use it (step-by-step)
Timeframe: 1–15m for intraday, 1–4h for swing.
Start defaults: Pivot L/R = 5, EMA len = 200, ATR len = 14, ATR mult = 2, TP = 2R, Retest = ON.
Tune sensitivity:
Faster lines (more trades): set L/R = 3–4.
Fewer counter-trend trades: enable HTF EMA (e.g., 60-min or Daily).
Visual audit: labels HL1/HL2 & LH1/LH2 show which pivots built each line—verify by eye.
Alerts: use Long breakout, Short breakdown, and Retest alerts to automate.
Originality (why it merits publication)
Trades the visualization: many “auto-trendline” tools only draw lines; this one turns them into testable, alertable rules.
Integrated design: each component has a defined role in the same pipeline—no unrelated indicators bolted together.
Transparent & non-repainting: pivot confirmation removes look-ahead; labels let non-coders understand the setup that produced each signal.
Notes & limitations
Lines update only after pivot confirmation; that lag is intentional to avoid repainting.
Breakouts near an apex can whipsaw; prefer Retest and/or HTF gate in choppy regimes.
Backtests are idealized; forward-test and size risk appropriately.
⚠️ Disclaimer
This script is provided for educational purposes only.
Past performance does not guarantee future results.
Trading involves risk, and users should exercise caution and use proper risk management when applying this strategy.
Turtle Trading System + ATR Trailing StopIndicator Description: Turtle ATR Trailing Stop
The **Turtle ATR Trailing Stop** is a technical indicator designed to enhance the classic Turtle Trading System by incorporating a dynamic trailing stop based on the Average True Range (ATR). This indicator is ideal for traders seeking to manage risk and lock in profits on both long and short positions in trending markets.
Key Features:
- Turtle Trading Levels: Calculates the 20-day highest high and lowest low to identify potential breakout points, a core principle of the Turtle Trading System.
- ATR-Based Trailing Stop: Utilizes a trailing stop that adjusts dynamically based on a multiple of the ATR (default multiplier: 2.0), providing a volatility-adjusted exit mechanism.
- Position Flexibility: Supports both long and short positions, with the trailing stop positioned below the highest price for long trades and above the lowest price for short trades.
- Smooth Updates: The trailing stop updates on each bar, ensuring a more responsive adjustment to price movements, rather than only on new highs or lows.
- Reset Mechanism: Automatically resets the trailing stop when the price deviates significantly (configurable threshold, default 0.1%), adapting to major trend reversals.
- Alerts: Includes customizable alerts that trigger when the price reaches the trailing stop level, notifying traders of potential exit points.
- Debugging Tools: Features an on-chart debug table displaying ATR, Close, Highest Price, Lowest Price, Potential Stop, and Trailing Stop values for real-time analysis.
How It Works:
- For **Long Positions**: The trailing stop starts below the initial close price (minus 2*ATR) and moves up as the highest price increases, locking in profits while trailing at a fixed ATR distance.
- For **Short Positions**: The trailing stop starts above the initial close price (plus 2*ATR) and moves down as the lowest price decreases, protecting against upward price movements.
- The stop resets if the price falls (for long) or rises (for short) beyond the set threshold, ensuring adaptability to new market conditions.
Customization:
- Period Settings: Adjust the length for highs/lows (default 20) and ATR period (default 14).
- ATR Multiplier: Modify the distance of the trailing stop (default 2.0).
- Reset Threshold: Fine-tune the percentage at which the stop resets (default 0.1%).
- Position Type: Switch between "Long" and "Short" modes via input settings.
Usage:
Apply this indicator to any chart in TradingView, set your preferred parameters, and monitor the trailing stop line (yellow) alongside the Turtle highs (red) and lows (blue). Use the debug table to validate calculations and set alerts to stay informed of stop triggers.
This indicator combines the trend-following strength of the Turtle System with a flexible, ATR-based stop-loss strategy, making it a powerful tool for both manual and automated trading strategies.
NY Open Breakout [ATR-5000]# **New York Open Breakout Indicator **
## **📌 Overview**
This **Pine Script** indicator identifies high-probability breakout opportunities at the **New York market open (13:30 UTC)** based on **volatility filters** using **customizable ATR periods and thresholds**.
### **🔹 Key Features**
✅ **Fully Customizable ATR Periods** (2 to **5000** bars)
✅ **Adjustable Thresholds** (0.01% to 5.00%)
✅ **Opening Range (OR) Filter** (0.01% to 5.00%)
✅ **Clean Visuals** – Only highlights the **13:30 UTC candle** when conditions are met
✅ **Real-Time Info Panel** – Displays current ATR & threshold settings
✅ **Automatic Daily Reset** – Fresh signals every trading day
---
## **📊 How It Works**
### **1️⃣ Volatility Check (13:25 UTC)**
- Calculates **two ATR values** (user-defined periods)
- Compares them against **custom % thresholds**
- Only proceeds if **both ATRs exceed** their required volatility levels
### **2️⃣ Opening Range Confirmation (13:30 UTC)**
- Measures the **high-low range** of the 13:30 candle
- Validates if the range meets the **minimum % threshold**
- If all conditions pass → **Highlights the candle** in your chosen color
### **3️⃣ Visual Feedback**
- **🟣 Colored Candle** → Valid breakout signal
- **📊 Info Table** → Shows current ATR settings & thresholds
---
## **⚙️ Customization Options**
| **Setting** | **Default** | **Adjustable Range** |
|---------------------------|------------|----------------------|
| **First ATR Period** | 14 | **2–5000** bars |
| **Second ATR Period** | 161 | **2–5000** bars |
| **First ATR Threshold** | 0.42% | **0.01%–5.00%** |
| **Second ATR Threshold** | 0.40% | **0.01%–5.00%** |
| **OR Range Threshold** | 0.42% | **0.01%–5.00%** |
| **Candle Color** | Purple | **Any color** |
---
## **📈 Best Use Cases**
✔ **Forex (EURUSD, GBPUSD)** – Captures NY session momentum
✔ **Indices (SPX, NASDAQ)** – Works well with opening volatility
✔ **Commodities (Gold, Oil)** – Filters out low-energy days
---
## **🔧 How to Adjust Settings**
1. **Click the gear icon (⚙️)** on your TradingView chart
2. **Modify ATR periods & thresholds** as needed
3. **Change the candle color** for better visibility
---
## **🚀 Why This Indicator?**
- **No repainting** – Signals lock in after candle close
- **No clutter** – Only marks valid 13:30 candles
- **Adaptable** – Works on **any market & timeframe**
- **Fully automated** – No manual adjustments needed
---
### **📥 Apply & Start Trading!**
Simply **load the script** on TradingView and customize it to fit your strategy! 🚀
Smart Market Matrix Smart Market Matrix
This indicator is designed for intraday, scalping, providing automated detection of price pivots, liquidity traps, and breakout confirmations, along with a context dashboard featuring volatility, trend, and volume.
## Summary Description
### Menu Settings & Their Roles
- **Swing Pivot Strength**: Controls the sensitivity for detecting High/Low pivots.
- **Show Pivot Points**: Toggles the display of HH/LL markers on the chart.
- **VWMA Length for Trap Volume** & **Volume Spike Multiplier**: Identify concentrated volume spikes for liquidity traps.
- **Wick Ratio Threshold** & **Max Body Size Ratio**: Detect candles with disproportionate wicks and small bodies (doji-ish) for traps.
- **ATR Length for Trap**: Measures volatility specific to trap detection.
- **VWMA Length for Breakout Volume**, **ATR Multiplier for Breakout**, **ATR Length for Breakout**, **Min Body/Range Ratio**: Set adaptive breakout thresholds based on volatility and volume.
- **OBV Smooth Length**: Smooths OBV momentum for breakout confirmation.
- **Enable VWAP Filter for Confirmations**: Optionally validate breakouts against the VWAP.
- **Enable Higher-TF Trend Filter** & **Trend Filter Timeframe**: Align breakout signals with the 1h/4h/Daily trend.
- **ADX Length**, **EMA Fast/Slow Length for Context**: Parameters for the context dashboard (Volatility, Trend, Volume).
- **Show Intraday VWAP Line**, **VWAP Line Color/Width**: Display the intraday VWAP line with custom style.
### Signal Interpretation Map
| Signal | Description | Recommended Action |
|--------------------------------|-----------------------------------------------------------|-------------------------------------------|
| 📌 **HH / LL (pivot)** | Market structure (support/resistance) | Note key levels |
| **Bull Trap(green diamond)** | Sweep down + volume spike + wick + rejection | Go long with trend filter
| **Bear Trap(red diamond)** | Sweep up + volume spike + wick + rejection | Go short with trend filter
| 🔵⬆️ **Breakout Confirmed Up** | Close > ATR‑scaled high + volume + OBV↑ | Go long with trend filter |
| 🔵⬇️ **Breakout Confirmed Down** | Close < ATR‑scaled low + volume + OBV↓ | Go short with trend filter |
| 📊 **VWAP Line** | Intraday reference to guide price | Use as dynamic support/resistance |
| ⚡ **Volatility** | ATR ratio High/Med/Low | Adjust position size |
| 📈 **Trend Context** | ADX+EMA Strong/Moderate/Weak | Confirm trend direction |
| 🔍 **Volume Context** | Breakout / Rising / Falling / Calm | Check volume momentum |
*This summary gives you a quick overview of the key settings and how to interpret signals for efficient intraday scalping.*
### Suggested Settings
- **Intraday Scalping (5m–15m)**
- `Swing Pivot Strength = 5`
- `VWMA Length for Trap Volume = 10`, `Volume Spike Multiplier = 1.6`
- `ATR Length for Trap = 7`
- `VWMA Length for Breakout Volume = 12`, `ATR Length for Breakout = 9`, `ATR Multiplier for Breakout = 0.5`
- `Min Body/Range Ratio for Breakout = 0.5`, `OBV Smooth Length = 7`
- `Enable Higher-TF Trend Filter = true` (TF = 60)
- `Show Intraday VWAP Line = true` (Color = orange, Width = 2)
- **Swing Trading (4h–Daily)**
- `Swing Pivot Strength = 10`
- `VWMA Length for Trap Volume = 20`, `Volume Spike Multiplier = 2.0`
- `ATR Length for Trap = 14`
- `VWMA Length for Breakout Volume = 30`, `ATR Length for Breakout = 14`, `ATR Multiplier for Breakout = 0.8`
- `Min Body/Range Ratio for Breakout = 0.7`, `OBV Smooth Length = 14`
- `Enable Higher-TF Trend Filter = true` (TF = D)
- `Show Intraday VWAP Line = false`
*Adjust these values based on the symbol and market volatility for optimal performance.*
TEMA OBOS Strategy PakunTEMA OBOS Strategy
Overview
This strategy combines a trend-following approach using the Triple Exponential Moving Average (TEMA) with Overbought/Oversold (OBOS) indicator filtering.
By utilizing TEMA crossovers to determine trend direction and OBOS as a filter, it aims to improve entry precision.
This strategy can be applied to markets such as Forex, Stocks, and Crypto, and is particularly designed for mid-term timeframes (5-minute to 1-hour charts).
Strategy Objectives
Identify trend direction using TEMA
Use OBOS to filter out overbought/oversold conditions
Implement ATR-based dynamic risk management
Key Features
1. Trend Analysis Using TEMA
Uses crossover of short-term EMA (ema3) and long-term EMA (ema4) to determine entries.
ema4 acts as the primary trend filter.
2. Overbought/Oversold (OBOS) Filtering
Long Entry Condition: up > down (bullish trend confirmed)
Short Entry Condition: up < down (bearish trend confirmed)
Reduces unnecessary trades by filtering extreme market conditions.
3. ATR-Based Take Profit (TP) & Stop Loss (SL)
Adjustable ATR multiplier for TP/SL
Default settings:
TP = ATR × 5
SL = ATR × 2
Fully customizable risk parameters.
4. Customizable Parameters
TEMA Length (for trend calculation)
OBOS Length (for overbought/oversold detection)
Take Profit Multiplier
Stop Loss Multiplier
EMA Display (Enable/Disable TEMA lines)
Bar Color Change (Enable/Disable candle coloring)
Trading Rules
Long Entry (Buy Entry)
ema3 crosses above ema4 (Golden Cross)
OBOS indicator confirms up > down (bullish trend)
Execute a buy position
Short Entry (Sell Entry)
ema3 crosses below ema4 (Death Cross)
OBOS indicator confirms up < down (bearish trend)
Execute a sell position
Take Profit (TP)
Entry Price + (ATR × TP Multiplier) (Default: 5)
Stop Loss (SL)
Entry Price - (ATR × SL Multiplier) (Default: 2)
TP/SL settings are fully customizable to fine-tune risk management.
Risk Management Parameters
This strategy emphasizes proper position sizing and risk control to balance risk and return.
Trading Parameters & Considerations
Initial Account Balance: $7,000 (adjustable)
Base Currency: USD
Order Size: 10,000 USD
Pyramiding: 1
Trading Fees: $0.94 per trade
Long Position Margin: 50%
Short Position Margin: 50%
Total Trades (M5 Timeframe): 128
Deep Test Results (2024/11/01 - 2025/02/24)BTCUSD-5M
Total P&L：+1638.20USD
Max equity drawdown：694.78USD
Total trades：128
Profitable trades:44.53
Profit factor:1.45
These settings aim to protect capital while maintaining a balanced risk-reward approach.
Visual Support
TEMA Lines (Three EMAs)
Trend direction is indicated by color changes (Blue/Orange)
ema3 (short-term) and ema4 (long-term) crossover signals potential entries
OBOS Histogram
Green → Strong buying pressure
Red → Strong selling pressure
Blue → Possible trend reversal
Entry & Exit Markers
Blue Arrow → Long Entry Signal
Red Arrow → Short Entry Signal
Take Profit / Stop Loss levels displayed
Strategy Improvements & Uniqueness
This strategy is based on indicators developed by "l_lonthoff" and "jdmonto0", but has been significantly optimized for better entry accuracy, visual clarity, and risk management.
Enhanced Trend Identification with TEMA
Detects early trend reversals using ema3 & ema4 crossover
Reduces market noise for a smoother trend-following approach
Improved OBOS Filtering
Prevents excessive trading
Reduces unnecessary risk exposure
Dynamic Risk Management with ATR-Based TP/SL
Not a fixed value → TP/SL adjusts to market volatility
Fully customizable ATR multiplier settings
(Default: TP = ATR × 5, SL = ATR × 2)
Summary
The TEMA + OBOS Strategy is a simple yet powerful trading method that integrates trend analysis and oscillators.
TEMA for trend identification
OBOS for noise reduction & overbought/oversold filtering
ATR-based TP/SL settings for dynamic risk management
Before using this strategy, ensure thorough backtesting and demo trading to fine-tune parameters according to your trading style.
VolatilityIndicatorsLibrary "VolatilityIndicators"
This is a library of Volatility Indicators .
It aims to facilitate the grouping of this category of indicators, and also offer the customized supply of
the parameters and sources, not being restricted to just the closing price.
@Thanks and credits:
1. Dynamic Zones: Leo Zamansky, Ph.D., and David Stendahl
2. Deviation: Karl Pearson (code by TradingView)
3. Variance: Ronald Fisher (code by TradingView)
4. Z-score: Veronique Valcu (code by HPotter)
5. Standard deviation: Ronald Fisher (code by TradingView)
6. ATR (Average True Range): J. Welles Wilder (code by TradingView)
7. ATRP (Average True Range Percent): millerrh
8. Historical Volatility: HPotter
9. Min-Max Scale Normalization: gorx1
10. Mean Normalization: gorx1
11. Standardization: gorx1
12. Scaling to unit length: gorx1
13. LS Volatility Index: Alexandre Wolwacz (Stormer), Fabrício Lorenz, Fábio Figueiredo (Vlad) (code by me)
14. Bollinger Bands: John Bollinger (code by TradingView)
15. Bollinger Bands %: John Bollinger (code by TradingView)
16. Bollinger Bands Width: John Bollinger (code by TradingView)
dev(source, length, anotherSource)
Deviation. Measure the difference between a source in relation to another source
Parameters:
source (float)
length (simple int) : (int) Sequential period to calculate the deviation
anotherSource (float) : (float) Source to compare
Returns: (float) Bollinger Bands Width
variance(src, mean, length, biased, degreesOfFreedom)
Variance. A statistical measurement of the spread between numbers in a data set. More specifically,
variance measures how far each number in the set is from the mean (average), and thus from every other number in the set.
Variance is often depicted by this symbol: σ2. It is used by both analysts and traders to determine volatility and market security.
Parameters:
src (float) : (float) Source to calculate variance
mean (float) : (float) Mean (Moving average)
length (simple int) : (int) The sequential period to calcule the variance (number of values in data set)
biased (simple bool) : (bool) Defines the type of standard deviation. If true, uses biased sample variance (n),
degreesOfFreedom (simple int) : (int) Degrees of freedom. The number of values in the final calculation of a statistic that are free to vary.
Default value is n-1, where n here is length. Only applies when biased parameter is defined as true.
Returns: (float) Standard deviation
stDev(src, length, mean, biased, degreesOfFreedom)
Measure the Standard deviation from a source in relation to it's moving average.
In this implementation, you pass the average as a parameter, allowing a more personalized calculation.
Parameters:
src (float) : (float) Source to calculate standard deviation
length (simple int) : (int) The sequential period to calcule the standard deviation
mean (float) : (float) Moving average.
biased (simple bool) : (bool) Defines the type of standard deviation. If true, uses biased sample variance (n),
else uses unbiased sample variance (n-1 or another value, as long as it is in the range between 1 and n-1), where n=length.
degreesOfFreedom (simple int) : (int) Degrees of freedom. The number of values in the final calculation of a statistic that are free to vary.
Default value is n-1, where n here is length.
Returns: (float) Standard deviation
zscore(src, mean, length, biased, degreesOfFreedom)
Z-Score. A z-score is a statistical measurement that indicates how many standard deviations a data point is from
the mean of a data set. It is also known as a standard score. The formula for calculating a z-score is (x - μ) / σ,
where x is the individual data point, μ is the mean of the data set, and σ is the standard deviation of the data set.
Z-scores are useful in identifying outliers or extreme values in a data set. A positive z-score indicates that the
data point is above the mean, while a negative z-score indicates that the data point is below the mean. A z-score of
0 indicates that the data point is equal to the mean.
Z-scores are often used in hypothesis testing and determining confidence intervals. They can also be used to compare
data sets with different units or scales, as the z-score standardizes the data. Overall, z-scores provide a way to
measure the relative position of a data point in a data
Parameters:
src (float) : (float) Source to calculate z-score
mean (float) : (float) Moving average.
length (simple int) : (int) The sequential period to calcule the standard deviation
biased (simple bool) : (bool) Defines the type of standard deviation. If true, uses biased sample variance (n),
else uses unbiased sample variance (n-1 or another value, as long as it is in the range between 1 and n-1), where n=length.
degreesOfFreedom (simple int) : (int) Degrees of freedom. The number of values in the final calculation of a statistic that are free to vary.
Default value is n-1, where n here is length.
Returns: (float) Z-score
atr(source, length)
ATR: Average True Range. Customized version with source parameter.
Parameters:
source (float) : (float) Source
length (simple int) : (int) Length (number of bars back)
Returns: (float) ATR
atrp(length, sourceP)
ATRP (Average True Range Percent)
Parameters:
length (simple int) : (int) Length (number of bars back) for ATR
sourceP (float) : (float) Source for calculating percentage relativity
Returns: (float) ATRP
atrp(source, length, sourceP)
ATRP (Average True Range Percent). Customized version with source parameter.
Parameters:
source (float) : (float) Source for ATR
length (simple int) : (int) Length (number of bars back) for ATR
sourceP (float) : (float) Source for calculating percentage relativity
Returns: (float) ATRP
historicalVolatility(lengthATR, lengthHist)
Historical Volatility
Parameters:
lengthATR (simple int) : (int) Length (number of bars back) for ATR
lengthHist (simple int) : (int) Length (number of bars back) for Historical Volatility
Returns: (float) Historical Volatility
historicalVolatility(source, lengthATR, lengthHist)
Historical Volatility
Parameters:
source (float) : (float) Source for ATR
lengthATR (simple int) : (int) Length (number of bars back) for ATR
lengthHist (simple int) : (int) Length (number of bars back) for Historical Volatility
Returns: (float) Historical Volatility
minMaxNormalization(src, numbars)
Min-Max Scale Normalization. Maximum and minimum values are taken from the sequential range of
numbars bars back, where numbars is a number defined by the user.
Parameters:
src (float) : (float) Source to normalize
numbars (simple int) : (int) Numbers of sequential bars back to seek for lowest and hightest values.
Returns: (float) Normalized value
minMaxNormalization(src, numbars, minimumLimit, maximumLimit)
Min-Max Scale Normalization. Maximum and minimum values are taken from the sequential range of
numbars bars back, where numbars is a number defined by the user.
In this implementation, the user explicitly provides the desired minimum (min) and maximum (max) values for the scale,
rather than using the minimum and maximum values from the data.
Parameters:
src (float) : (float) Source to normalize
numbars (simple int) : (int) Numbers of sequential bars back to seek for lowest and hightest values.
minimumLimit (simple float) : (float) Minimum value to scale
maximumLimit (simple float) : (float) Maximum value to scale
Returns: (float) Normalized value
meanNormalization(src, numbars, mean)
Mean Normalization
Parameters:
src (float) : (float) Source to normalize
numbars (simple int) : (int) Numbers of sequential bars back to seek for lowest and hightest values.
mean (float) : (float) Mean of source
Returns: (float) Normalized value
standardization(src, mean, stDev)
Standardization (Z-score Normalization). How "outside the mean" values relate to the standard deviation (ratio between first and second)
Parameters:
src (float) : (float) Source to normalize
mean (float) : (float) Mean of source
stDev (float) : (float) Standard Deviation
Returns: (float) Normalized value
scalingToUnitLength(src, numbars)
Scaling to unit length
Parameters:
src (float) : (float) Source to normalize
numbars (simple int) : (int) Numbers of sequential bars back to seek for lowest and hightest values.
Returns: (float) Normalized value
lsVolatilityIndex(movingAverage, sourceHvol, lengthATR, lengthHist, lenNormal, lowerLimit, upperLimit)
LS Volatility Index. Measures the volatility of price in relation to an average.
Parameters:
movingAverage (float) : (float) A moving average
sourceHvol (float) : (float) Source for calculating the historical volatility
lengthATR (simple int) : (float) Length for calculating the ATR (Average True Range)
lengthHist (simple int) : (float) Length for calculating the historical volatility
lenNormal (simple int) : (float) Length for normalization
lowerLimit (simple int)
upperLimit (simple int)
Returns: (float) LS Volatility Index
lsVolatilityIndex(sourcePrice, movingAverage, sourceHvol, lengthATR, lengthHist, lenNormal, lowerLimit, upperLimit)
LS Volatility Index. Measures the volatility of price in relation to an average.
Parameters:
sourcePrice (float) : (float) Source for measure the distance
movingAverage (float) : (float) A moving average
sourceHvol (float) : (float) Source for calculating the historical volatility
lengthATR (simple int) : (float) Length for calculating the ATR (Average True Range)
lengthHist (simple int) : (float) Length for calculating the historical volatility
lenNormal (simple int)
lowerLimit (simple int)
upperLimit (simple int)
Returns: (float) LS Volatility Index
bollingerBands(src, length, mult, basis)
Bollinger Bands. A Bollinger Band is a technical analysis tool defined by a set of lines plotted
two standard deviations (positively and negatively) away from a simple moving average (SMA) of the security's price,
but can be adjusted to user preferences. In this version you can pass a customized basis (moving average), not only SMA.
Parameters:
src (float) : (float) Source to calculate standard deviation used in Bollinger Bands
length (simple int) : (int) The time period to be used in calculating the standard deviation
mult (simple float) : (float) Multiplier used in standard deviation. Basically, the upper/lower bands are standard deviation multiplied by this.
basis (float) : (float) Basis of Bollinger Bands (a moving average)
Returns: (float) A tuple of Bollinger Bands, where index 1=basis; 2=basis+dev; 3=basis-dev; and dev=multiplier*stdev
bollingerBands(src, length, aMult, basis)
Bollinger Bands. A Bollinger Band is a technical analysis tool defined by a set of lines plotted
two standard deviations (positively and negatively) away from a simple moving average (SMA) of the security's price,
but can be adjusted to user preferences. In this version you can pass a customized basis (moving average), not only SMA.
Also, various multipliers can be passed, thus getting more bands (instead of just 2).
Parameters:
src (float) : (float) Source to calculate standard deviation used in Bollinger Bands
length (simple int) : (int) The time period to be used in calculating the standard deviation
aMult (float ) : (float ) An array of multiplies used in standard deviation. Basically, the upper/lower bands are standard deviation multiplied by this.
This array of multipliers permit the use of various bands, not only 2.
basis (float) : (float) Basis of Bollinger Bands (a moving average)
Returns: (float ) An array of Bollinger Bands, where:
index 1=basis; 2=basis+dev1; 3=basis-dev1; 4=basis+dev2, 5=basis-dev2, 6=basis+dev2, 7=basis-dev2, Nup=basis+devN, Nlow=basis-devN
and dev1, dev2, devN are ```multiplier N * stdev```
bollingerBandsB(src, length, mult, basis)
Bollinger Bands %B - or Percent Bandwidth (%B).
Quantify or display where price (or another source) is in relation to the bands.
%B can be useful in identifying trends and trading signals.
Calculation:
%B = (Current Price - Lower Band) / (Upper Band - Lower Band)
Parameters:
src (float) : (float) Source to calculate standard deviation used in Bollinger Bands
length (simple int) : (int) The time period to be used in calculating the standard deviation
mult (simple float) : (float) Multiplier used in standard deviation
basis (float) : (float) Basis of Bollinger Bands (a moving average)
Returns: (float) Bollinger Bands %B
bollingerBandsB(src, length, aMult, basis)
Bollinger Bands %B - or Percent Bandwidth (%B).
Quantify or display where price (or another source) is in relation to the bands.
%B can be useful in identifying trends and trading signals.
Calculation
%B = (Current Price - Lower Band) / (Upper Band - Lower Band)
Parameters:
src (float) : (float) Source to calculate standard deviation used in Bollinger Bands
length (simple int) : (int) The time period to be used in calculating the standard deviation
aMult (float ) : (float ) Array of multiplier used in standard deviation. Basically, the upper/lower bands are standard deviation multiplied by this.
This array of multipliers permit the use of various bands, not only 2.
basis (float) : (float) Basis of Bollinger Bands (a moving average)
Returns: (float ) An array of Bollinger Bands %B. The number of results in this array is equal the numbers of multipliers passed via parameter.
bollingerBandsW(src, length, mult, basis)
Bollinger Bands Width. Serve as a way to quantitatively measure the width between the Upper and Lower Bands
Calculation:
Bollinger Bands Width = (Upper Band - Lower Band) / Middle Band
Parameters:
src (float) : (float) Source to calculate standard deviation used in Bollinger Bands
length (simple int) : (int) Sequential period to calculate the standard deviation
mult (simple float) : (float) Multiplier used in standard deviation
basis (float) : (float) Basis of Bollinger Bands (a moving average)
Returns: (float) Bollinger Bands Width
bollingerBandsW(src, length, aMult, basis)
Bollinger Bands Width. Serve as a way to quantitatively measure the width between the Upper and Lower Bands
Calculation
Bollinger Bands Width = (Upper Band - Lower Band) / Middle Band
Parameters:
src (float) : (float) Source to calculate standard deviation used in Bollinger Bands
length (simple int) : (int) Sequential period to calculate the standard deviation
aMult (float ) : (float ) Array of multiplier used in standard deviation. Basically, the upper/lower bands are standard deviation multiplied by this.
This array of multipliers permit the use of various bands, not only 2.
basis (float) : (float) Basis of Bollinger Bands (a moving average)
Returns: (float ) An array of Bollinger Bands Width. The number of results in this array is equal the numbers of multipliers passed via parameter.
dinamicZone(source, sampleLength, pcntAbove, pcntBelow)
Get Dynamic Zones
Parameters:
source (float) : (float) Source
sampleLength (simple int) : (int) Sample Length
pcntAbove (simple float) : (float) Calculates the top of the dynamic zone, considering that the maximum values are above x% of the sample
pcntBelow (simple float) : (float) Calculates the bottom of the dynamic zone, considering that the minimum values are below x% of the sample
Returns: A tuple with 3 series of values: (1) Upper Line of Dynamic Zone;
(2) Lower Line of Dynamic Zone; (3) Center of Dynamic Zone (x = 50%)
Examples:
SuperTrend OptimizerHello!
This indicator attempts to optimize Supertrend parameters. To achieve this, 102 parameter combinations are tested concurrently - the top three performers are listed in descending order.
Parameters,
Factor: Changes to this parameter shifts the tested factor range. For instance, increasing the factor measure from 3.00 to 3.01 (+0.01) will remove 3.00 from the tested range - this setting controls the lower threshold of the range. The upper threshold, in all instances, is the lower Factor threshold + 3.3 (i.e. 3.0(lower) - 6.3(upper), 4.0(lower) - 7.3(upper), 2.5(lower) - 5.8(upper))
ATR period: Changes to this parameter shifts the tested ATR period range. For instance, increasing the ATR measure from 10 to 11 (+1) will remove 10 from the tested range - this setting controls the lower threshold of the range. The upper threshold, in all instances, is the lower threshold + 2 (i.e. 10(lower) - 12(upper), 11(lower) - 13(upper), 9(lower), - 11(upper))
The Factor parameter is modifiable to any positive decimal number; the ATR parameter is modifiable to any positive integer. Changing either parameter shifts the tested parameter combination range. Both parameters can be changed in the settings, to which you control the lower threshold of the range. If, for instance, you were to change the Factor measurement from 3.0 to 4.1 (+1.1) the 4.0 Factor measurement, and all Factor measures less than 4.0, will be excluded from the performance test.
Consequently, a Supertrend test will be performed with a Factor of 4.1 and an ATR period of 10 (default). This test repeats at 0.1 Factor intervals and 1.0 ATR intervals.
Therefore, assume you modify the Factor lower threshold to 3.1 and the ATR lower threshold to 10. The indicator will test three Supertrend systems with a Factor of 3.1 and an ATR period of 10.. then 11.. 12, then three systems with a Factor of 3.2 and an ATR period of 10.. then 11.. 12... until (lower Factor threshold + 3.3) and (lower ATR threshold + 2) are tested... which in this example is... a Factor of 6.4 and an ATR period of 12.
The tested Factor range and ATR range are displayed in a bottom right table alongside the top performing parameter combinations.
Of course, you can change the the lower thresholds, which means you can test numerous Supertrend parameter combinations! However, no greater than 102 parameter combinations will be tested simultaneously; the best performing Supertrend parameters are plotted on the chart automatically.
I will be working on this indicator more tomorrow! Let me know if you have questions or anything you would like included!
(I of course added something fun in the script. Be sure to try it with bar replay!)
Risk Recommender — (Heatmap)📊 Risk Recommender — Per-Trade & Annualized (Heatmap Columns)
Estimate the optimal risk percentage for any market regime.
This tool dynamically recommends how much of your account equity to risk — either per trade or at a portfolio (annualized) level — using volatility as the guide.
⚙️ How it works
Two distinct modes give you flexibility:
1️⃣ Per-Trade (ATR-based)
• Calculates the current Average True Range (ATR) compared to its long-term baseline.
• When volatility is high (ATR ↑), risk per trade decreases to maintain constant dollar risk.
• When volatility is low (ATR ↓), risk per trade increases within your defined floor and ceiling.
• The display is normalized by stop distance (× ATR) and smoothed to avoid noise.
2️⃣ Annualized (Volatility Targeting)
• Computes realized volatility (standard deviation of log returns) and an EWMA forecast of future volatility.
• Blends current and forecast volatilities to estimate “effective” volatility.
• Scales your base risk so that portfolio volatility converges toward your chosen annual target (e.g., 20%).
• Useful for portfolio-level or systematic strategies that maintain constant volatility exposure.
🎨 Heatmap Visualization
The vertical column graph acts like a thermometer:
• 🟥 Red → “Reduce risk” (volatility high).
• 🟩 Green → “Increase risk” (volatility low).
• Smoothed and bounded between your Floor and Ceiling risk levels.
• Optional dotted guides mark those bounds.
• Label shows the current mode, recommended risk %, and key metrics (ATR ratio or effective volatility).
🔧 Key Inputs
• Base max risk per trade (%) — your normal per-trade risk budget.
• ATR length / Baseline ATR length — control sensitivity to short- vs. long-term volatility.
• Target annualized volatility (%) — portfolio volatility target for quant mode.
• λ (lambda) — smoothing factor for the EWMA volatility forecast (0.90–0.99 typical).
• Floor & Ceiling — clamps the output to avoid extreme sizing.
• Smoothing & Hysteresis — prevent rapid changes in risk recommendations.
🧮 Interpreting the Output
• “Recommended Risk (%)” = suggested portion of equity to risk on the next trade (or current exposure).
• In Per-Trade mode: reflects current ATR ÷ baseline ATR .
• In Annualized mode: reflects target volatility ÷ effective volatility .
• Use the color and height of the column as a quick visual cue for aggressiveness.
💡 Typical Use Cases
• Position-sizing overlay for discretionary traders.
• Volatility-targeting component for algorithmic or multi-asset systems.
• Educational tool to understand how volatility governs prudent risk management.
📘 Notes
• This indicator provides risk suggestions only ; it does not place trades.
• Works on any symbol or timeframe.
• Combine with your own strategy or alerts for full automation.
• All calculations use built-in Pine functions; no proprietary logic.
Tags:
#RiskManagement #ATR #Volatility #Quant #PositionSizing #SystematicTrading #AlgorithmicTrading #Portfolio #TradingStrategy #Heatmap #EWMA #Risk
