ZenLab ATR FNSThis indicator was created specifically for Zen Labs which includes a custom ATR (Average True Range) table that displays the ATR value for a selected period of candles.
ATR is a volatility indicator that measures the average range between high and low prices over a given number of periods. It helps traders assess how much an asset typically moves, providing valuable information for setting stop losses, take profits, or identifying market conditions. It adapts to changing market conditions, making it useful across different timeframes and asset classes.
How the ATR Indicator Works:
The ATR is based on the concept of True Range (TR), which is the greatest of the following three values:
- Current High minus Current Low
- Absolute value of Current High minus Previous Close
- Absolute value of Current Low minus Previous Close
Averaging the True Range:
Once the True Range is calculated for each period, the ATR is computed by averaging these True Ranges over a set number of periods and is displayed in the table.
Interpreting the ATR:
- A higher ATR value indicates higher volatility—prices are moving more significantly.
- A lower ATR value indicates lower volatility—prices are more stable and less active.
Enjoy!
- Rebel Empire
Cari skrip untuk "ATR"
Dynamic Volatility Heatmap (ATR)How the Script Works
Dynamic Thresholds:
atrLow and atrHigh are calculated as percentiles (20% and 80% by default) of ATR values over the last double the ATR period (28 days if ATR is 14).
This creates thresholds that adapt to recent market conditions.
Background Heatmap:
Green: ATR is below the low threshold, indicating calm markets (options are cheap).
Red: ATR is above the high threshold, signaling elevated volatility (options are expensive).
Yellow: ATR is within the normal range, showing neutral market conditions.
Overlay Lines:
]Dynamic lines for atrLow and atrHigh help visualize thresholds on the chart.
Interpretation for Trading
Green Zone (Low ATR):
Interpretation: The market is calm, and options are likely underpriced.
Trade Setup: Favor buying options (e.g., long straddles or long calls/puts) to profit from potential volatility increases.
Red Zone (High ATR):
Interpretation: The market is volatile, and options are likely overpriced.
Trade Setup: Favor selling options (e.g., credit spreads or iron condors) to benefit from volatility decay.
Yellow Zone (Neutral ATR):
Interpretation: Volatility is within typical levels, offering no strong signal.
Trade Setup: Combine with other indicators, such as gamma levels or Bollinger Bands, for confirmation.
5. Enhancing with Other Indicators
Combine with Bollinger Bands:
Overlay Bollinger Bands to identify price extremes and align them with volatility heatmap signals.
Custom ATR with Paranormal Bar FilterCustom ATR with Paranormal Bar Filter
Description:
This indicator calculates a custom ATR (Average True Range) by filtering out bars with unusually large or small price ranges. It helps provide a more accurate measure of market volatility by ignoring outliers.
How it works:
True Range Calculation:
The price range for each bar is calculated.
Bars with ranges much larger or smaller than typical are excluded.
Filtered ATR:
The ATR is calculated using only the bars that pass the filter.
Current Bar Progress:
Measures how much the current bar has moved compared to the filtered ATR, based on the difference between its opening and closing prices.
Display:
A line represents the filtered ATR.
A table shows the filtered ATR, the current bar's range, and its progress relative to the ATR.
Input Settings:
ATR Period: Number of bars used to calculate the ATR.
Filter Window: Number of recent bars used to determine the typical range.
Filter Threshold: Sensitivity of the filter. A higher value allows more bars to pass.
How to Use:
Monitor Volatility:
Use the filtered ATR to understand market volatility while ignoring unusual price movements.
Track Current Bar Progress:
See how much of the ATR the current bar has completed.
Adjust Filter Settings:
Fine-tune the filter to match your trading timeframe and strategy.
This indicator is designed for traders who want to track market volatility without being misled by extreme outlier bars.
Delta Volume-ATR ChangeDelta Volume-ATR Change Indicator
The Delta Volume-ATR Change Indicator is designed to analyze the effectiveness of volume in relation to price volatility by comparing the percentage change in volume with the percentage change in ATR over the last two bars. This indicator provides insights into how volume changes impact price movement, allowing traders to gauge the strength or weakness of market momentum based on volume efficiency.
Formula:
% Volume Change = (Volume - Volume ) / Volume * 100
% ATR Change = (ATR - ATR ) / ATR * 100
Delta = % Volume Change - % ATR Change
The result, Delta, shows the difference between the volume change and ATR change, with positive delta indicating a stronger volume impact and negative delta suggesting weaker volume support relative to price movement.
Features:
Multiple Display Styles: Choose from three visualization styles — Histogram, Line, or Columns — to display delta values in a way that best fits your analysis style.
Delta Smoothing: The smoothed Delta line (using an SMA with customizable length) provides a clearer trend of volume efficiency over time.
Color Coding: Delta bars change color based on direction — green for positive values and red for negative, allowing for quick visual assessment of volume effectiveness.
Applications:
Identify market conditions where high volume is driving price effectively (positive Delta).
Detect instances of low volume efficiency, where price changes may not be fully supported by volume (negative Delta).
Useful for short-term and swing traders looking to understand volume patterns in relation to volatility.
This indicator is a valuable tool for traders seeking to gain insights into volume and volatility interplay, helping improve timing and reliability in market entries and exits.
Trend Magic Enhanced [AlgoAlpha]🔥✨ Trend Magic Enhanced - Boost Your Trend Analysis! 🚀📈
Introducing the Trend Magic Enhanced indicator by AlgoAlpha, a powerful tool designed to help you identify market trends with greater accuracy. This advanced indicator combines the Commodity Channel Index (CCI) and Average True Range (ATR) to calculate dynamic support and resistance levels, known as the Trend Magic. By smoothing the Trend Magic with various moving average types, this indicator provides clearer trend signals and helps you make more informed trading decisions.
Key Features :
🎯 Unique Trend Identification : Combines CCI and ATR to detect market trends and potential reversals.
🔄 Customizable Smoothing : Choose from SMA, EMA, SMMA, WMA, or VWMA to smooth the Magic Trend for clearer signals.
🎨 Flexible Appearance Settings : Customize colors for bullish and bearish trends to suit your charting preferences.
⚙️ Adjustable Parameters : Modify CCI period, ATR period, ATR multiplier, and smoothing length to align with your trading strategy.
🔔 Alert Notifications : Set alerts for trend shifts to stay ahead of market movements.
📈 Visual Signals : Displays trend direction changes directly on the chart with up and down arrows.
Quick Guide to Using the Trend Magic Enhanced Indicator
🛠 Add the Indicator : Add the indicator to your chart by pressing the star icon to add it to favorites. Customize settings such as CCI period, ATR multiplier, ATR period, smoothing options, and colors to match your trading style.
📊 Analyze the Chart : Observe the Trend Magic line and the color-coded trend signals. When the Trend Magic line turns bullish (e.g., green), it indicates an upward trend, and when it turns bearish (e.g., red), it indicates a downward trend. Use the visual arrows to spot trend direction changes.
🔔 Set Alerts : Enable alerts to receive notifications when a trend shift is detected, so you can act promptly on trading opportunities without constantly monitoring the chart.
How It Works:
The Trend Magic Enhanced indicator integrates the Commodity Channel Index (CCI) and Average True Range (ATR) to calculate a dynamic Trend Magic line. By adjusting price levels based on CCI values—upward when CCI is positive and downward when negative—and factoring in ATR for market volatility, it creates adaptive support and resistance levels. Optionally smoothed with various moving averages to reduce noise, the indicator changes line color based on trend direction, highlights trend changes with arrows, and provides alerts for significant shifts, aiding traders in identifying potential entry and exit points.
Enhancements Over the Original Trend Magic Indicator
The Trend Magic Enhanced indicator significantly refines the trend identification method of the original Trend Magic script by introducing customizable smoothing options and additional analytical features. While the original indicator determines trend direction solely based on the Commodity Channel Index (CCI) crossing above or below zero and adjusts the Magic Trend line using the Average True Range (ATR), the enhanced version allows users to smooth the Magic Trend line with various moving average types (SMA, EMA, SMMA, WMA, VWMA). This smoothing reduces market noise and provides clearer trend signals. Additionally, the enhanced indicator incorporates price action analysis by detecting crossovers and crossunders of price with the Magic Trend line, and it visually marks trend changes with up and down arrows on the chart. These improvements offer a more responsive and accurate trend detection compared to the original method, enabling traders to identify potential entry and exit points more effectively.
Enhance your trading strategy with the Trend Magic Enhanced indicator by AlgoAlpha and gain a clearer perspective on market trends! 🌟📈
Fair Value Gap (FVG) Oscillator [UAlgo]The "Fair Value Gap (FVG) Oscillator " is designed to identify and visualize Fair Value Gaps (FVG) within a given lookback period on a trading chart. This indicator helps traders by highlighting areas where price gaps may signify potential trading opportunities, specifically bullish and bearish patterns. By leveraging volume and Average True Range (ATR) data, the FVG Oscillator aims to enhance the accuracy of pattern recognition and provide more reliable signals for trading decisions.
🔶 Identification of Fair Value Gap (FVG)
Fair Value Gaps (FVG) are specific price areas where gaps occur, and they are often considered significant in technical analysis. These gaps can indicate potential future price movements as the market may return to fill these gaps. This indicator identifies two types of FVGs:
Bullish FVG: Occurs when the current low price is higher than the high price two periods ago. This condition suggests a potential upward price movement.
Obtains with:
low > high
Bearish FVG: Occurs when the current high price is lower than the low price two periods ago. This condition suggests a potential downward price movement.
Obtains with:
high < low
The FVG Oscillator not only identifies these gaps but also verifies them using volume and ATR conditions to ensure more reliable trading signals.
🔶 Key Features
Lookback Period: Users can set the lookback period to determine how far back the indicator should search for FVG patterns.
ATR Multiplier: The ATR Multiplier is used to adjust the sensitivity of the ATR-based conditions for verifying FVG patterns.
Volume SMA Period: This setting determines the period for the Simple Moving Average (SMA) of the volume, which helps in identifying high volume conditions.
Why ATR and Volume are Used?
ATR (Average True Range) and volume are integrated into the Fair Value Gap (FVG) Oscillator to enhance the accuracy and reliability of the identified patterns. ATR measures market volatility, helping to filter out insignificant price gaps and focus on impactful ones, ensuring that the signals are relevant and strong. Volume, on the other hand, confirms the strength of price movements. High volume often indicates the sustainability of these movements, reducing the likelihood of false signals. Together, ATR and volume ensure that the detected FVGs are both significant and supported by market activity, providing more trustworthy trading signals.
Normalized Values: The FVG counts are normalized to enhance the visual representation and interpretation of the patterns on the chart.
Visual Customization and Plotting: Users can customize the colors for positive (bullish) and negative (bearish) areas, and choose whether to display these areas on the chart, also plots the bullish and bearish FVG counts, a zero line, and the net value of FVG counts. Additionally, it uses histograms to display the width of verified bullish and bearish patterns.
🔶 Disclaimer:
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Lines of Chaos (ATR/ADR Levels)Lines of Chaos Indicator
This script is designed to provide traders with ATR (Average True Range) and ADR (Average Daily Range) support and resistance levels.
How it Works:
Support and Resistance Lines: The script plots ATR/ADR-based support and resistance lines based on a moving average of the last ATR/ADR Length days, the previous day's close, and the current day's open. Changing the ATR/ADR Length value changes the number of days of data to average.
EMA: The EMA is colored red when the ticker is potentially bearish. The EMA is colored green when the ticker is potentially bullish. Changing the EMA Length changes the number of data bars to average.
Default Settings: The default settings are optimized for most trading environments.
Key Features:
ATR & ADR Calculation: You can use ATR, ADR, or both. ATR is recommended for most scenarios.
Customizable Lengths: Adjust the ATR/ADR Length to refine the average calculation to your preference, with 14 being the standard value.
EMA for Market Bias: The EMA helps determine the ticker bias. It is colored green when the market is above the average price and red when below. This allows you to more easily determine whether or not the ADR/ATR levels are valid.
Versatile Usage: Suitable for various trading types, ensuring broad applicability across different market conditions.
How to Use:
Bounces off Levels: When the price bounces off a support/resistance level, the price will likely respect this level. This indicates that the price is unlikely to exceed the ticker's average volatility.
Breakthroughs of Levels: When the price breaks through a support/resistance level, the price will likely continue beyond this level. This indicates that the price has moved beyond that ticker's average volatility.
[EKIN] ATR Exit StrategyMy exit strategy to reduce risk via tracking price and ATR. Sets new STOP price based on how many ATR is current price above from the entry price.
I only check 5 and 20 EMAs for entry strategy. I intentionally used a simple entry strategy to further test the impact of this exit strategy.
First sets STOP at 1.5 ATR below the entry price.
If there is a 2 ATR increase, pulls STOP to the entry point to eliminate the possibility of loss.
If there is a 3 ATR increase, takes a 50% profit and moves STOP to 1 ATR above the entry price.
If there is a 4 ATR increase, moves STOP to 2 ATR above the entry price.
If there is a 5 ATR increase, moves STOP to 3 ATR above the entry price.
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This is my first strategy attempt so I am open to any recommendations. I am planning to update this strategy overtime when I get better at pinescript and trading in general
RAHUL ATR + Volume SpikesNew Volume Spikes Strategy.
The Average True Range (ATR) indicator is a technical analysis tool that measures the volatility of an asset. It can be used to create a trading strategy by identifying periods of high volatility and making trades based on those conditions.
Here is an example of a simple ATR trading strategy:
Calculate the ATR for the asset you are trading. This can typically be done using a charting platform or software.
Identify the average ATR over a period of time (such as 14 days). This will be your "threshold" for determining high volatility.
When the current ATR is above the threshold, enter a long position (buy) in the asset.
When the current ATR is below the threshold, exit the long position (sell) and wait for the next period of high volatility.
Repeat the process for the next period of time.
This is a basic example of an ATR strategy and can be adjusted as per one's preference, you can add other indicators or market conditions to filter out trades and also use different time frame to check the ATR values. ATR can also be used in combination with other indicators and strategies to improve the accuracy of your trades.
It's always important to backtest any strategy before actually trading with real money, and also to consider the risk management, stop loss and profit taking levels, and adjust the strategy accordingly
Higher Time Frame Average True RangesPurpose: This script will help an options trader asses risk and determine good entry and exit strategies
Background Information: The true range is the greatest of: current high minus the current low; the absolute value of the current high minus the previous close; and the absolute value of the current low minus the previous close. The Average True Range (ATR) is a 14-day moving average of the true range. Traders use the ATR indicator to assess volatility in stocks and decide when to enter and exit trades. It is important to note the limitations of using True Range and ATR: These indications cannot tell you the direction of your options trade (call vs. put) and they cannot tell you whether a particular trend is about to reverse. However, it can be used to assess if volatility has peaked for a particular direction and time period.
How this script works: This indicator calculates true range for the daily (DTR), weekly (WTR), and monthly (MTR) time frames and compares it to the Average True Range (ATR) for each of those time frames (DATR, WATR, and MATR). The comparison is displayed into a colored table in the upper right-hand corner of the screen. When a daily, weekly, or monthly true range reaches 80% of its respective ATR, the row for that time frame will turn Orange indicating medium risk for staying in the trade. If the true range goes above 100% of the respective ATR, then the row will turn Red indicating high risk for staying in the trade. When the row for a time period turns red, volatility for the time period has likely peaked and traders should heavily consider taking profits. It is important to note these calculations start at different times for each time frame: Daily (Today’s Open), Weekly (Monday’s Open), Monthly (First of the Month’s Open). This means if it’s the 15th of the month then the Monthly True Range is being calculated for the trading days in the first half of the month (approximately 10 trade days).
The script also plots three sets of horizontal dotted lines to visually represent the ATR for each time period. Each set is generated by adding and subtracting the daily, weekly, and monthly ATRs from that time periods open price. For example, the weekly ATR is added and subtracted from Mondays open price to visually represent the true range for that week. The DATR is represented by red lines, the WATR is represented by the green lines, and the MATR is represented by the blue lines. These plots could also be used to assess risk as well.
How to use this script: Use the table to assess risk and determine potential exit strategies (Green=Low Risk, Orange=Medium Risk, Red=High Risk. Use the dotted lines to speculate what a stock’s price could be in a given time period (Daily=Red, Weekly=Green, and Monthly=Blue). And don’t forget the true range’s calculation and plots starts at the beginning of each time period!
ER-Adaptive ATR, STD-Adaptive Damiani Volatmeter [Loxx]ER-Adaptive ATR, STD-Adaptive Damiani Volatmeter is a Damiani Volatmeter with both Efficiency-Ratio Adaptive ATR, used in place of ATR, and Adaptive Deviation, used in place of Standard Deviation.
What is Adaptive Deviation?
By definition, the Standard Deviation (STD, also represented by the Greek letter sigma σ or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. In technical analysis we usually use it to measure the level of current volatility .
Standard Deviation is based on Simple Moving Average calculation for mean value. This version of standard deviation uses the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA , we can call it EMA deviation. And added to that, Perry Kaufman's efficiency ratio is used to make it adaptive (since all EMA type calculations are nearly perfect for adapting).
The difference when compared to standard is significant--not just because of EMA usage, but the efficiency ratio makes it a "bit more logical" in very volatile market conditions.
The green line is the Adaptive Deviation, the white line is regular Standard Deviation. This concept will be used in future indicators to further reduce noise and adapt to price volatility .
See here for a comparison between Adaptive Deviation and Standard Deviation
What is Efficiency Ratio Adaptive ATR?
Average True Range (ATR) is widely used indicator in many occasions for technical analysis . It is calculated as the RMA of true range. This version adds a "twist": it uses Perry Kaufman's Efficiency Ratio to calculate adaptive true range
See here for a comparison between Efficiency-Ratio Adaptive ATR, and ATR.
What is the Damiani Volatmeter?
Damiani Volatmeter uses ATR and Standard deviation to tease out ticker volatility so you can better understand when it's the ideal time to trade. The idea here is that you only take trades when volatility is high so this indicator is to be coupled with various other indicators to validate the other indicator's signals. This is also useful for detecting crabbing and chopping markets.
Shoutout to user @xinolia for the DV function used here.
Anything red means that volatility is low. Remember volatility doesn't have a direction. Anything green means volatility high despite the direction of price. The core signal line here is the green and red line that dips below two while threshold lines to "recharge". Maximum recharge happen when the core signal line shows a yellow ping. Soon after one or many yellow pings you should expect a massive upthrust of volatility . The idea here is you don't trade unless volatility is rising or green. This means that the Volatmeter has to dip into the recharge zone, recharge and then spike upward. You can also attempt to buy or sell reversals with confluence indicators when volatility is in the recharge zone, but I wouldn't recommend this. However, if you so choose to do this, then use the following indicator for confluence.
And last reminder, volatility doesn't have a direction! Red doesn't mean short, and green doesn't mean long, Red means don't trade period regardless of direction long/short, and green means trade no matter the direction long/short. This means you'll have to add an indicator that does show direction such as a mean reversion indicator like Fisher Transform or a Gaussian Filter. You can search my public scripts for various Fisher Transform and Gaussian Filter indicators.
Price-Filtered Spearman Rank Correl. w/ Floating Levels is considered the Mercedes Benz of reversal indicators
Comparison between this indicator, ER-Adaptive ATR, STD-Adaptive Damiani Volatmeter , and the regular Damiani Volatmeter . Notice that the adaptive version catches more volatility than the regular version.
How signals work
RV = Rising Volatility
VD = Volatility Dump
Plots
White line is signal
Thick red/green line is the Volatmeter line
The dotted lower lines are the zero line and minimum recharging line
Included
Bar coloring
Alerts
Signals
Related indicators
Variety Moving Average Waddah Attar Explosion (WAE)
Damiani Volatmeter
TAExtLibrary "TAExt"
Indicator functions can be used in other indicators and strategies. This will be extended by time with indicators I use in my strategies and studies.
atrwo(length, stdev_length, stdev_mult) ATR without outliers
Parameters:
length : The length of the ATR
stdev_length : The length of the standard deviation, used for detecting outliers
stdev_mult : The multiplier of the standard deviation, used for detecting outliers
Returns: The ATR value
atrwma(src, period, type, atr_length, stdev_length, stdev_mult) ATR without outlier weighted moving average
Parameters:
src : The source of the moving average
period : The period of the moving average
type : The type of the moving average, possible values: SMA, EMA, RMA
atr_length : The length of the ATR
stdev_length : The length of the standard deviation, used for detecting outliers
stdev_mult : The multiplier of the standard deviation, used for detecting outliers
Returns: The moving average value
jma(src, period, phase, power) Jurik Moving Average
Parameters:
src : The source of the moving average
period : The period of the moving average calculation
phase : The phase of jurik MA calculation (-100..100)
power : The power of jurik MA calculation
Returns: The Jurik MA series
anyma(src, period, type, offset, sigma, phase, power) Moving Average by type
Parameters:
src : The source of the moving average
period : The period of the moving average calculation
type : The type of the moving average
offset : Used only by ALMA, it is the ALMA offset
sigma : Used only by ALMA, it is the ALMA sigma
phase : The phase of jurik MA calculation (-100..100)
power : The power of jurik MA calculation
Returns: The moving average series
wae(macd_src, macd_fast_length, macd_slow_length, macd_sensitivity, bb_base_src, bb_upper_src, bb_lower_src, bb_length, bb_mult, dead_zone_length, dead_zone_mult) Waddah Attar Explosion (WAE)
Parameters:
macd_src : The source series used by MACD
macd_fast_length : The fast MA length of the MACD
macd_slow_length : The slow MA length of the MACD
macd_sensitivity : The MACD diff multiplier
bb_base_src : The source used by stdev
bb_upper_src : The source used by the upper Bollinger Band
bb_lower_src : The source used by the lower Bollinger Band
bb_length : The lenth for Bollinger Bands
bb_mult : The multiplier for Bollinger Bands
dead_zone_length : The ATR length for dead zone calculation
dead_zone_mult : The ATR multiplier for dead zone
Returns:
ssl(length, high_src, low_src) Semaphore Signal Level channel (SSL)
Parameters:
length : The length of the moving average
high_src : Source of the high moving average
low_src : Source of the low moving average
Returns:
adx(atr_length, di_length, adx_length, high_src, low_src, atr_ma_type, di_ma_type, adx_ma_type) Average Directional Index + Direction Movement Index (ADX + DMI)
Parameters:
atr_length : The length of ATR
di_length : DI plus and minus smoothing length
adx_length : ADX smoothing length
high_src : Source of the high moving average
low_src : Source of the low moving average
atr_ma_type : MA type of the ATR calculation
di_ma_type : MA type of the DI calculation
adx_ma_type : MA type of the ADX calculation
Returns:
Mean Reversion Strategy v2 [KL]Description :
This strategy will enter a position when the following conditions are met:
a) Main signal: When source data (ATR) diverts from its moving average value, and
b) Confirmation: If predicted direction of trend is favorable.
Assumptions :
During periods of high price volatility, ATR diverts from its moving average value. Eventually, ATR should revert. But since just knowing the magnitude of increase/decrease of ATR does not indicate a trend signal, we need to introduce a model to predict the current trend.
In short:
• Trend Prediction : This strategy calculates the expected logarithmic return of the security (the "Drift") and considers prices to be moving in uptrend if the drift curve is upward sloping.
• Assessment of ATR diversion : To determine "yes/no" regarding whether ATR at a given point in time has diverted, this script conducts a two-tailed hypothesis test at each candlestick period. The null hypothesis (H0) is that the fast moving average value should equal the slow moving average value (say, denoted as H0: atr14 == atr28; it is assumed that atr28 is more meaningful for the purpose of describing the current trend because it has a larger sample size). Investopedia has an article summarizing this topic .
Exit Condition :
When trailing stop loss hits.
Previous version :
This strategy is based on Version 1 published back in September . This older version considers +/- one standard deviation to be the critical values relative to average ATR when testing whether ATR has diverted from the mean. This does not take Standard Error ("SE") into account. As a result, the threshold is often too wide and it generates too many entry signals.
Adaptive Pivot (HLC3)SUMMARY:
Standard Pivot (HLC3) with ATR leeway added to make it adaptive to market volatility.
DESCRIPTION:
Adaptive Pivot is an indicator utilizing the simplicity of HLC3 Pivots as a turning point (and sometimes a trend indicator) while addressing it's fixed and inflexible nature.
Because the indicator is just a single line in the chart, the price may go near it but never touch it. Or it can go pass through it and never retest it again. In an attempt to lessen these from occurring, we can combine pivots with average true range (ATR). This is the specific formula I applied in this indicator:
>Upper Pivot = HLC3 + ATR
>Lower Pivot = HLC3 - ATR
This creates a kind of a range or cloud around the Pivot, making it possibly a more accurate indicator for market turning points.
ADJUSTABLE PARAMETERS:
The usual ATR parameters are included in this indicator:
>ATR_Length = input(14, title="ATR Length", minval=1)
>ATR_Smoothing = input(title="ATR Smoothing", defval="RMA", options="RMA", "SMA", "EMA", "WMA")
Added to the usual ones is this:
>ATR_Multiplier = input(1, title="ATR Multiplier", minval=0.1)
which modifies the extent of the ATR (similar to Chandelier Exit) as it is added/subtracted from the pivot values.
Pivot’s timeframe is also adjustable:
>Pivot_Timeframe = input("3M", title='Pivot Resolution')
Note: I did not lock the type to input.resolution to allow for more possible timeframes.
OTHER PARAMETERS
Indicator color will change to green when the open is above the HLC3 Pivot and change to red when the reverse is true.
Liquidity Trap Strategy - ATR OptimizedLiquidity Trap Strategy – Optimized Version
1. Overview
The Liquidity Trap Strategy is a high-probability price action trading system designed to exploit “trapped buyers or sellers” around key levels from the previous trading day.
Markets: Works on any market (Forex, Crypto, Futures, Indices, Stocks)
Timeframes: Designed for 15-minute (15m) and 1-hour (1H) charts
Trading Style: “Hunter” style — trades may not happen every day, but setups are high-probability
Trade Frequency: Only first trade per day is taken for simplicity and high quality
2. Key Components
a) Daily Levels
Previous Day High (PDH) and Previous Day Low (PDL) are automatically calculated using the prior day’s bar.
These are drawn as anchored horizontal lines, extending to the current day.
PDH/PDL act as key support/resistance zones — areas where liquidity is often trapped.
b) Trap Concept
The strategy is based on the “liquidity trap” principle:
Buyer Trap (Short Entry):
Price breaks above the previous day high (PDH) → buyers think price will continue higher.
Price reverses immediately below PDH, trapping aggressive buyers above the key level.
This creates selling pressure, giving an opportunity to enter short.
Seller Trap (Long Entry):
Price breaks below the previous day low (PDL) → sellers think price will continue lower.
Price reverses immediately above PDL, trapping aggressive sellers below the key level.
This creates buying pressure, giving an opportunity to enter long.
The key idea: trapped traders cause the market to move in the opposite direction of the breakout, creating high-probability moves.
c) Trade Execution Logic
Buyer Trap / Short Entry:
Condition: high > PDH AND close < PDH AND no trade taken yet today
Entry: Short at the close of the trap candle
Stop Loss: ATR-based above the trap candle high to avoid minor wick stops
Take Profit: 2:1 Risk-to-Reward ratio
Seller Trap / Long Entry:
Condition: low < PDL AND close > PDL AND no trade taken yet today
Entry: Long at the close of the trap candle
Stop Loss: ATR-based below the trap candle low
Take Profit: 2:1 Risk-to-Reward ratio
Only the first trap trade of the day is allowed to avoid overtrading.
d) Risk Management
Stop-Loss (SL):
ATR-based to account for market volatility
Ensures the trade survives minor wick sweeps without being stopped out prematurely
Take-Profit (TP):
Fixed 2:1 R:R relative to SL
Ensures each winning trade outweighs potential losses
Trade Frequency:
Only first trade per day is allowed, making it highly selective and reducing noise
3. Visual Features
PDH/PDL Lines: Anchored to previous day, extend into current day, color-coded:
PDH → Green
PDL → Red
Trade Labels: Placed on the trap candle:
Short → Red label “Short”
Long → Green label “Long”
The visual markers make it easy to identify exactly where the trap occurred and the trade was triggered.
4. How the Strategy Works – Step by Step
Example for Short (Buyer Trap):
Market opens, PDH/PDL from yesterday are drawn.
Price spikes above PDH → some buyers enter expecting breakout continuation.
Price immediately closes back below PDH, trapping buyers.
The strategy enters short at the close of the reversal candle.
SL: placed above the trap candle using ATR to give room
TP: calculated as 2x the risk (distance from entry to SL)
Trade executes — first trade of the day. Any further trap signals today are ignored.
Example for Long (Seller Trap):
Price drops below PDL → some sellers enter.
Price immediately closes back above PDL, trapping sellers.
Strategy enters long at the close of the reversal candle.
SL: below trap candle using ATR
TP: 2:1 R:R
Trade executes — only first trade of the day.
5. Why This Strategy Works
Exploits liquidity zones: Markets often hunt stops above PDH or below PDL.
High-probability reversals: Trapped traders create strong counter moves.
ATR SL: avoids being stopped by minor market noise or wick spikes.
Selective trading: Only first trade per day → reduces overtrading and noise.
Clear visual markers: Makes manual observation and confirmation easy.
6. Key Tips for Traders
Best on high-volume instruments like Forex majors, indices, or crypto pairs with decent liquidity.
Works well on 15m and 1H charts — 15m allows quicker signals, 1H filters noise.
Avoid trading around major news releases — traps can behave differently during high volatility events.
Always backtest and use the ATR SL — never reduce SL too much, otherwise stops will trigger before the real move.
✅ Summary:
The Liquidity Trap Strategy identifies trapped buyers/sellers using previous day highs/lows.
It uses ATR-adapted stops and 2:1 R:R TP.
Only first trade per day is executed, reducing false signals.
Anchored PDH/PDL lines and labels make trade opportunities clear.
This system is low-frequency, high-probability, focusing on trading smart rather than frequently.
ORB + INMERELO ADR + ATRThis indicator provides **two completely different but complementary lines of information** for intraday traders:
# **1. The ORB Line (ADR-Based Context Line)**
The ORB portion of the script focuses on **range expansion** relative to typical daily behavior.
### **What it measures**
* **20-day ADR (Average Daily Range)**
* **Today’s range as a % of ADR**
* **How much of the average range has been “used”** by the time you’re considering an Opening Range Breakout
### **Why it matters for ORB trading**
Successful ORBs thrive when:
* **ADR used% is low** (green) → plenty of fuel left for expansion
* **ADR used% is moderate** (orange) → breakout still possible but less explosive
* **ADR used% is high** (red) → breakout attempts often fail or reverse
### **What the indicator gives you**
A clean, color-coded readout of:
* ADR
* Today’s range
* Used%
* A simple green/orange/red evaluation of ORB quality
This allows a trader to quickly judge whether **conditions favor ORB continuation or mean-reversion reversal**—without manually calculating ranges or switching charts.
---
# **2. The INMERELO Line (ATR Stretch + MA Interaction)**
The INMERELO portion of the script is built around **mean-reversion mechanics**:
the market tends to revert back toward the **first daily MA it crosses under**.
### **How it determines the active MA**
At the start of each session, the script waits for price to cross under:
* **EMA10**
* **EMA21**
* **SMA50**
Whichever MA is crossed first becomes the **active MA** for the day.
If no cross has occurred yet, the indicator shows the **nearest MA**, so traders know exactly what the likely “INMERELO magnet” will be.
### **What it measures**
* **Stretch from the active MA (in ATR units)**
* **20-day ATR regime direction (expanding or contracting)**
* **Daily MA context: E10, E21, or S50**
### **Why it matters for INMERELOs**
This provides:
* The **target MA**
* The **distance to that MA in ATRs**
* A color-coded stretch score:
* **0.6–1.2 ATR** → prime INMERELO zone (Green)
* Moderately stretched → Orange
* Overstretched or dead zone → Red
An up/down arrow shows whether **volatility is expanding or compressing**, which affects expected retrace behavior.
### **What the indicator gives you**
All INMERELO data is displayed in a second compact line:
* Stretch to MA
* Active MA label (E10/E21/S50)
* ATR regime arrow
This allows fast identification of high-probability **mean-reversion trades back to the MA**.
---
# **Summary**
This indicator shows:
### **Line 1 → ORB Context (ADR)**
* Is the stock setup for a powerful breakout?
* How much ADR is left?
* Are you early (good) or late (risky)?
### **Line 2 → INMERELO Context (ATR + MA Stretch)**
* Which MA is in control today (EMA10, EMA21, or SMA50)?
* How many ATRs away from that MA are we?
* Is volatility expanding or contracting?
* Is this a clean INMERELO setup or not?
Together, these two lines give traders the **two most important intraday lenses**:
**range expansion (ORB)** and **mean reversion (INMERELO)**—updated every bar, without clutter.
Volume Order Block Scanner [BOSWaves]Volume Order Block Scanner - Dynamic Detection of High-Volume Supply and Demand Zones
Overview
The Volume Order Block Scanner introduces a refined approach to institutional zone mapping, combining volume-weighted order flow, structural displacement, and ATR-based proportionality to identify regions of aggressive participation from large entities.
Unlike static zone mapping or simplistic body-size filters, this framework dynamically evaluates each candle through a multi-layer model of relative volume, candle structure, and volatility context to isolate genuine order block formations while filtering out market noise.
Each identified zone represents a potential institutional footprint, defined by significant volume surges and efficient body-to-ATR relationships that indicate purposeful positioning. Once mapped, each order block is dynamically adjusted for volatility and tracked throughout its lifecycle - from creation to mitigation to potential invalidation - producing an evolving liquidity map that adapts with price.
This adaptive behavior allows traders to visualize where liquidity was absorbed and where it remains unfilled, revealing the structural foundation of institutional intent across timeframes.
Theoretical Foundation
At its core, the Volume Order Block Scanner is built on the interaction between volume displacement and structural imbalance. Traditional order block systems often rely on fixed candle formations or simple engulfing logic, neglecting the fundamental driver of institutional activity: volume concentration relative to volatility.
This framework redefines that approach. Each candle is filtered through two comparative ratios:
Relative Volume Ratio (RVR) - the candle’s volume compared to its rolling average, confirming genuine transactional surges.
Body-ATR Ratio (BAR) - a measure of displacement efficiency relative to recent volatility, ensuring structural strength.
Only when both conditions align is an order block validated, marking a displacement event significant enough to create a lasting imbalance.
By embedding this logic within a volatility-adjusted environment, the system maintains scalability across asset classes and volatility regimes - equally effective in crypto, forex, or index markets.
How It Works
The Volume Order Block Scanner operates through a structured multi-stage process:
Displacement Detection - Identifies candles whose body and volume exceed dynamic thresholds derived from ATR and rolling volume averages. These represent the origin points of institutional aggression.
Zone Construction - Each qualified candle generates an order block with ATR-proportional dimensions to ensure consistency across instruments and timeframes. The zone includes two regions: Body Zone (the precise initiation point of displacement) and Wick Imbalance (the residual inefficiency representing unfilled liquidity).
Lifecycle Tracking - Each zone is continuously monitored for market interaction. Reactions within a defined window are classified as respected, mitigated, or invalidated, giving traders a data-driven sense of ongoing institutional relevance.
Volume Confirmation Layer - Reinforces signal integrity by ensuring that all detected blocks correspond with meaningful increases in transactional activity.
Temporal Decay Control - Zones that remain untested beyond a set period gradually lose visual and analytical weight, maintaining chart clarity and contextual precision.
Interpretation
The Volume Order Block Scanner visualizes how institutional participants interact with the market through zones of accumulation and distribution.
Bullish order blocks denote demand imbalances where price displaced upward under high volume; bearish order blocks signify supply regions formed by concentrated selling pressure.
Price revisiting these areas often reflects institutional re-entry or liquidity rebalancing, offering actionable insights for both continuation and reversal scenarios.
By continuously monitoring interaction and expiry, the framework enables traders to distinguish between active institutional footprints and historical liquidity artifacts.
Strategy Integration
The Volume Order Block Scanner integrates naturally into advanced structural and order-flow methodologies:
Liquidity Mapping : Identify high-volume regions that are likely to influence future price reactions.
Break-of-Structure Confirmation : Validate BOS and CHOCH signals through aligned order block behavior.
Volume Confluence : Combine with BOSWaves volume or momentum indicators to confirm real institutional intent.
Smart-Money Frameworks : Utilize order block retests as precision entry zones within SMC-based setups.
Trend Continuation : Filter zones in line with higher-timeframe bias to maintain directional integrity.
Technical Implementation Details
Core Engine : Dual-filter mechanism using Relative Volume Ratio (RVR) and Body-ATR Ratio (BAR).
Volatility Framework : ATR-based scaling for cross-asset proportionality.
Zone Composition : Body and wick regions plotted independently for visual clarity of imbalance.
Lifecycle Logic : Real-time monitoring of reaction, mitigation, and invalidation states.
Directional Coloring : Distinct bullish and bearish shading with adjustable transparency.
Computation Efficiency : Lightweight structure suitable for multi-timeframe or multi-asset environments.
Optimal Application Parameters
Timeframe Guidance:
5m - 15m : Reactive intraday zones for short-term liquidity engagement.
1H - 4H : Medium-term structures for swing or intraday trend mapping.
Daily - Weekly : Macro accumulation and distribution footprints.
Suggested Configuration:
Relative Volume Threshold : 1.5× - 2.0× average volume.
Body-ATR Threshold : 0.8× - 1.2× for valid displacement.
Zone Expiry : 5 - 10 bars for intraday use, 15 - 30 for swing/macro contexts.
Parameter optimization should be asset-specific, tuned to volatility conditions and liquidity depth.
Performance Characteristics
High Effectiveness:
Markets exhibiting clear displacement and directional flow.
Environments with consistent volume expansion and liquidity inefficiencies.
Reduced Effectiveness:
Range-bound markets with frequent false impulses.
Low-volume sessions lacking institutional participation.
Integration Guidelines
Confluence Framework : Pair with structure-based BOS or liquidity tools for validation.
Risk Management : Treat active order blocks as contextual areas of interest, not guaranteed reversal points.
Multi-Timeframe Logic : Derive bias from higher-timeframe blocks and execute from refined lower-timeframe structures.
Volume Verification : Confirm each reaction with concurrent volume acceleration to avoid false liquidity cues.
Disclaimer
The Volume Order Block Scanner is a quantitative mapping framework designed for professional traders and analysts. It is not a predictive or guaranteed system of profit.
Performance depends on correct configuration, market conditions, and disciplined risk management. BOSWaves recommends using this indicator as part of a comprehensive analytical process - integrating structural, volume, and liquidity context for accurate interpretation.
MTRADE ATR SL FINDERAverage True Range Stop Loss Finder (ATR)
This indicator automatically calculates dynamic stop-loss levels based on market volatility using the Average True Range (ATR) formula.
It provides both Long and Short stop levels derived from ATR values and adapts them in real time as volatility changes.
🔍 Features
Adjustable ATR Length (default: 20)
Four smoothing methods: RMA, SMA, EMA, WMA
Configurable Multiplier (default: 1.5× ATR)
Real-time High (Short Stop) and Low (Long Stop) lines on the chart
A clean on-chart table displaying:
ATR value
High stop level (H)
Low stop level (L)
— all shown with 7-decimal precision for accurate readings
⚙️ Use Cases
Volatility-based stop-loss and take-profit placement
Risk management and trailing-stop automation
Intraday and swing trading systems using ATR-driven exits
🧠 Technical Details
Built in Pine Script v5
Supports up to 7 decimal precision (precision=7)
Works as an overlay, displaying ATR bands directly on price action
Fully customizable colors and smoothing logic
by fiyatherseydir
Market Pressure Differential (MPD) [SharpStrat]Market Pressure Differential (MPD)
Concept & Purpose
The Market Pressure Differential (MPD) is a proprietary indicator designed to measure the internal balance of buying and selling pressure directly on the price chart.
Unlike standard momentum or trend indicators, MPD analyzes the structural behavior of each candle—its body, wicks, and overall range—to determine whether the market is dominated by expansion (buying aggression) or contraction (selling absorption).
This indicator provides a visual overlay of market pressure that adapts dynamically to volatility, helping traders see real-time shifts in participation intensity without using oscillators.
In simple terms:
When MPD expands upward → buyer pressure dominates.
When MPD contracts downward → seller pressure dominates.
Calculation Overview
MPD uses a structural candle formula to compute directional pressure:
Body Ratio = (Close − Open) / (High − Low)
Wick Differential = (Lower Wick − Upper Wick) / (High − Low)
Raw Pressure = (Body Ratio × Body Weight) + (Wick Differential × Wick Weight)
Then it applies:
EMA smoothing (to stabilize short-term noise)
Standard deviation normalization (to maintain consistent scaling)
ATR projection (to adapt the signal visually to volatility)
This produces the MPD projection line and the pressure ribbon, drawn directly on the main chart.
Customizable Inputs
Users can adjust color schemes, EMA smoothing length, ATR parameters, normalization length, and body/wick weighting to adapt the indicator’s sensitivity and aesthetic to different markets or chart themes.
How to Use
The Market Pressure Differential (MPD) visualizes the real-time balance between buying and selling pressure. It should be used as a contextual bias tool, not a standalone signal generator.
The white line represents the MPD projection, showing how market pressure evolves in real time based on candle structure and volatility.
The red line represents the ATR envelope, which defines the market’s expected volatility range.
MPD reacts quickly to candle structure, so trend bias is based on how its projection behaves relative to the ATR envelope:
Above the ATR band → positive pressure and bullish bias.
Below the ATR band → negative pressure and bearish bias.
Hovering near the ATR band → neutral or indecisive conditions.
The MPD percentage in the label represents the normalized strength of pressure relative to recent volatility.
Positive % = buying dominance.
Negative % = selling dominance.
Higher absolute values = stronger momentum compared to volatility.
To trade with MPD:
Watch candle colors and the projection line — green or positive % shows buyer control, red or negative % shows seller control.
Note transitions above or below the ATR level for early signs of momentum shifts.
Combine MPD signals with price structure, key levels, or volume for confirmation.
This helps reveal which side controls the market and whether that pressure is strong enough to overcome typical volatility.
Disclaimer
It introduces a novel structural–pressure approach to visualizing market dynamics.
For educational and analytical purposes only; this does not constitute financial advice.
Grand Master's Candlestick Dominance (ATR Enhanced)### Grand Master's Candlestick Dominance (ATR Enhanced)
**Overview**
Unleash the ancient wisdom of Japanese candlestick charting with a modern twist! This comprehensive Pine Script v5 strategy and indicator scans for over 75 classic and advanced candlestick patterns (bullish, bearish, and neutral), assigning dynamic strength scores (1-10) to each for precise signal filtering. Enhanced with Average True Range (ATR) for volatility-aware body size validation, it dominates the markets by combining timeless pattern recognition with robust confirmation layers. Whether used as a backtestable strategy or visual indicator, it empowers traders to spot high-probability reversals, continuations, and indecision setups with surgical accuracy.
Inspired by Steve Nison's *Japanese Candlestick Charting Techniques*, this tool elevates pattern analysis beyond basics—think Hammers, Engulfing patterns, Morning Stars, and rare gems like Abandoned Baby or Concealing Baby Swallow—all consolidated into intelligent arrays for real-time averaging and prioritization.
**Key Features**
- **Extensive Pattern Library**:
- **Bullish (25+ patterns)**: Hammer (8.0), Bullish Engulfing (10.0), Morning Star (7.0), Three White Soldiers (9.0), Dragonfly Doji (8.0), and more (e.g., Rising Three, Unique Three River Bottom).
- **Bearish (25+ patterns)**: Hanging Man (8.0), Bearish Engulfing (10.0), Evening Star (7.0), Three Black Crows (9.0), Gravestone Doji (8.0), and exotics like Upside Gap Two Crows or Stalled Pattern.
- **Neutral/Indecision (34+ patterns)**: Doji variants (Long-Legged, Four Price), Spinning Tops, Harami Crosses, and multi-bar setups like Upside Tasuki Gap or Advancing Block.
Each pattern includes duration tracking (1-5 bars) and ATR-adjusted body/shadow criteria for relevance in volatile conditions.
- **Smart Confirmation Filters** (All Toggleable):
- **Trend Alignment**: 20-period SMA (customizable) ensures entries align with the prevailing trend; optional higher timeframe (e.g., Daily) MA crossover for multi-timeframe confluence.
- **Support/Resistance (S/R)**: Pivot-based levels with 0.01% tolerance to confirm bounces or breaks.
- **Volume Surge**: 20-period volume MA with 1.5x spike multiplier to validate momentum.
- **ATR Body Sizing**: Filters small bodies (<0.3x ATR) and long bodies (>0.8x ATR) for context-aware pattern reliability.
- **Follow-Through**: Ensures post-pattern confirmation via bullish/bearish closes or closes beyond prior bars.
Minimum average strength (default 7.0) and individual pattern thresholds (5.0) prevent weak signals.
- **Entry & Exit Logic**:
- **Long Entry**: Bullish average strength ≥7.0 (outweighing bearish), uptrend, volume spike, near support, follow-through, and HTF alignment.
- **Short Entry**: Mirror for bearish dominance in downtrends near resistance.
- **Exits**: Bearish/neutral shift, or fixed TP (5%) / SL (2%)—pyramiding disabled, 10% equity sizing.
- Backtest range: Jan 1, 2020 – Dec 31, 2025 (editable). Initial capital: $10,000.
- **Interactive Dashboard** (Top-Right Panel):
Real-time insights including:
- Market phase (e.g., "Bullish Phase (Avg Str: 8.2)"), active pattern (e.g., "BULLISH: Bullish Engulfing (Str: 10.0, Bars: 2)"), and trend status.
- Strength breakdowns (Bull/Bear/Neutral counts & averages).
- Filter status (e.g., "Volume: ✔ Spike", "ATR: Enabled (L:0.8, S:0.3)").
- Backtest stats: Total trades, win rate, streak, and last entry/exit details (price & timestamp).
Toggle mode: Strategy (live trades) or Indicator (signals only).
- **Advanced Alerts** (15+ Toggleable Types):
Set up via TradingView's "Any alert() function call" for bar-close triggers:
- Entry/Exit signals with strength & pattern details.
- Strong patterns (≥2 bullish/bearish), neutral indecision, volume spikes.
- S/R breakouts, HTF reversals, high-confidence singles (≥8.0 strength).
- Conflicting signals, MA crossovers, ATR volatility bursts, multi-bar completions.
Example: "STRONG BULLISH PATTERN detected! Strength: 9.5 | Top Pattern: Three White Soldiers | Trend: Up".
**Customization & Usage Tips**
- **Inputs Groups**: Strategy toggles, confirmations, exits, backtest dates, and 15+ alert switches—all intuitively grouped.
- **Optimization**: Tune min strengths for aggressive (lower) or conservative (higher) trading; enable/disable filters to suit your style (e.g., disable S/R for scalping).
- **Best For**: Forex, stocks, crypto on 1H–Daily charts. Test on historical data to refine TP/SL.
- **Limitations**: No external data installs; relies on built-in TA functions. Patterns are probabilistic—combine with your risk management.
Master the candles like a grandmaster. Deploy on TradingView, backtest relentlessly, and let dominance begin! Questions? Drop a comment.
*Version: 1.0 | Updated: September 2025 | Credits: Built on Pine Script v5 with nods to Nison's timeless techniques.*
Daily Buy/Sell Triggers + ATR TargetsThis tool gives you a once-per-day, objective ATR map: Buy Trigger above the open, Sell Trigger below the open, clean ATR targets, and FULL ATR extremes. It’s designed for clarity, precision, and zero intraday repainting so you can plan the session and execute with confidence.
This indicator prints a new, static grid of intraday levels every New York 18:00 (end of the NY trading day). The grid is anchored at the day’s open and spaced by the Daily ATR so you get tick-precise Buy Trigger, Sell Trigger, intermediate ATR targets, and the FULL ATR bounds for the session.
The levels act as objective support/resistance and intraday measuring sticks for continuation, mean-reversion, and range expansion trades.
What you see on the chart
A thin midline at the Daily Open (anchor).
Green lines above, red lines below, spaced at your chosen ATR multiples.
Text at the far right for:
Buy trigger
Sell trigger
FULL ATR (both sides)
Intermediate targets are unlabeled to keep the chart clean (they’re still tradable S/R).
HMA Crossover + ATR + Curvature (Long & Short)📏 Hull Moving Averages (Trend Filters)
- fastHMA = ta.hma(close, fastLength)
- slowHMA = ta.hma(close, slowLength)
These two HMAs act as dynamic trend indicators:
- A bullish crossover of fast over slow HMA signals a potential long setup.
- A bearish crossunder triggers short interest.
⚡️ Curvature (Acceleration Filter)
- curv = ta.change(ta.change(fastHMA))
This calculates the second-order change (akin to the second derivative) of the fast HMA — effectively the acceleration of the trend. It serves as a filter:
- For long entries: curv > curvThresh (positive acceleration)
- For short entries: curv < -curvThresh (negative acceleration)
It helps eliminate weak or stagnating moves by requiring momentum behind the crossover.
📈 Volatility-Based Risk Management (ATR)
- atr = ta.atr(atrLength)
- stopLoss = atr * atrMult
- trailStop = atr * trailMult
These define your:
- Initial stop loss: scaled to recent volatility using ATR and atrMult.
- Trailing stop: also ATR-scaled, to lock in gains dynamically as price moves favorably.
💰 Position Sizing via Risk Percent
- capital = strategy.equity
- riskCapital = capital * (riskPercent / 100)
- qty = riskCapital / stopLoss
This dynamically calculates the position size (qty) such that if the stop loss is hit, the loss does not exceed the predefined percentage of account equity. It’s a volatility-adjusted position sizing method, keeping your risk consistent regardless of market conditions.
📌 Execution Logic
- Long Entry: on bullish HMA crossover with rising curvature.
- Short Entry: on bearish crossover with falling curvature.
- Exits: use ATR-based trailing stops.
- Position is closed when trend conditions reverse (e.g., bearish crossover exits the long).
This framework gives you:
- Trend-following logic (via HMAs)
- Momentum confirmation (via curvature)
- Volatility-aware execution and exits (via ATR)
- Risk-controlled dynamic sizing
Want to get surgical and test what happens if we use curvature on the difference between HMAs instead? That might give some cool insights into trend strength transitions.
[blackcat] L3 Mean Reversion ATR Stop Loss OVERVIEW
The L3 Mean Reversion ATR Stop Loss indicator is meticulously crafted to empower traders by offering statistically-driven stop-loss levels that adapt seamlessly to evolving market dynamics. By harmoniously blending mean reversion concepts with Advanced True Range (ATR) metrics, it delivers a robust framework for managing risks more effectively. 🌐 The primary objective is to furnish traders with intelligent exit points grounded in both short-term volatility assessments and long-term trend evaluations.
Key highlights encompass:
• Dynamic calculation of Z-scores to evaluate deviations from established means
• Adaptive stop-loss pricing leveraging real-time ATR measurements
• Clear visual cues enabling swift decision-making processes
TECHNICAL ANALYSIS COMPONENTS
📉 Z-SCORE CALCULATION
Measures how many standard deviations an asset's current price lies away from its average
Facilitates identification of extreme conditions indicative of impending reversals
Utilizes simple moving averages and standard deviation computations
📊 STANDARD DEVIATION MEASUREMENT
Quantifies dispersion of closing prices around the mean
Provides insights into underlying price distribution characteristics
Crucial for assessing potential volatility levels accurately
🕵️♂️ ADAPTIVE STOP-LOSS DETECTION
Employs ATR as a proxy for prevailing market volatility
Modulates stop-loss placements dynamically responding to shifting trends
Ensures consistent adherence to predetermined risk management protocols
INDICATOR FUNCTIONALITY
🔢 Core Algorithms
Integrate Smooth Moving Averages (SMAs) alongside standardized deviation formulas
Generate precise Z-scores reflecting true price deviations
Leverage ATR-derived multipliers for fine-grained stop-loss adjustments
🖱️ User Interface Elements
Interactive plots displaying real-time stop-loss markers
Context-sensitive color coding enhancing readability
Background shading indicating proximity to stop-level activations
STRATEGY IMPLEMENTATION
✅ Entry Conditions
Confirm bullish/bearish setups validated through multiple confirmatory signals
Ensure alignment between Z-score readings and broader trend directions
Validate entry decisions considering concurrent market sentiment factors
🚫 Exit Mechanisms
Trigger exits upon hitting predefined ATR-based stop-loss thresholds
Monitor continuous breaches signifying potential trend reversals
Execute partial/total closes contingent upon cumulative loss limits
PARAMETER CONFIGURATIONS
🎯 Optimization Guidelines
Period Length: Governs responsiveness versus smoothing trade-offs
ATR Length: Dictates the temporal scope for volatility analysis
Stop Loss ATR Multiplier: Tunes sensitivity towards stop-trigger activations
💬 Customization Recommendations
Commence with baseline defaults; iteratively refine parameters
Evaluate impacts independently prior to combined adjustments
Prioritize minimizing erroneous trigger occurrences first
Sustain balanced risk-reward profiles irrespective of chosen settings
ADVANCED RISK MANAGEMENT
🛡️ Proactive Risk Mitigation Techniques
Enforce strict compliance with pre-defined maximum leverage constraints
Mandatorily apply trailing stop-loss orders conforming to script outputs
Allocate positions proportionately relative to available capital reserves
Conduct periodic reviews gauging strategy effectiveness rigorously
⚠️ Potential Pitfalls & Solutions
Address frequent violations arising during heightened volatility phases
Manage false alerts warranting manual interventions judiciously
Prepare contingency plans mitigating margin call possibilities
Continuously assess automated system reliability amidst fluctuating conditions
PERFORMANCE AUDITS & REFINEMENTS
🔍 Critical Evaluation Metrics
Assess win percentages consistently across diverse trading instruments
Calculate average profit ratios per successful execution
Measure peak drawdown durations alongside associated magnitudes
Analyze signal generation frequencies revealing hidden patterns
📈 Historical Data Analysis Tools
Maintain comprehensive records capturing every triggered event
Compare realized profits/losses against backtested simulations
Identify recurrent systematic errors demanding corrective actions
Implement iterative refinements bolstering overall efficacy steadily
PROBLEM SOLVING ADVICE
🔧 Frequent Encountered Challenges
Unpredictable behaviors emerging within thinly traded markets
Latency issues manifesting during abrupt price fluctuations
Overfitted models yielding suboptimal results post-extensive tuning
Inaccuracies stemming from incomplete or delayed data inputs
💡 Effective Resolution Pathways
Exclude low-liquidity assets prone to erratic movements
Introduce buffer intervals safeguarding major news/event impacts
Limit ongoing optimization attempts preventing model degradation
Verify seamless connectivity ensuring uninterrupted data flows
USER ENGAGEMENT SEGMENT
🤝 Community Contributions Welcome
Highly encourage active participation sharing experiences & recommendations!
THANKS
A heartfelt acknowledgment extends to all developers contributing invaluable insights about adaptive stop-loss strategies using statistical measures! ✨
