VolCorrBeta [NariCapitalTrading]Indicator Overview: VolCorrBeta
The VolCorrBeta indicator is designed to analyze and interpret intermarket relationships. This indicator combines volatility, correlation, and beta calculations to provide a comprehensive view of how certain assets (BTC, DXY, CL) influence the ES futures contract (I tailored this indicator to the ES contract, but it will work for any symbol).
Functionality
Input Symbols
BTCUSD : Bitcoin to USD
DXY : US Dollar Index
CL1! : Crude Oil Futures
ES1! : S&P 500 Futures
These symbols can be customized according to user preferences. The main focus of the indicator is to analyze how the price movements of these assets correlate with and lead the price movements of the ES futures contract.
Parameters for Calculation
Correlation Length : Number of periods for calculating the correlation.
Standard Deviation Length : Number of periods for calculating the standard deviation.
Lookback Period for Beta : Number of periods for calculating beta.
Volatility Filter Length : Length of the volatility filter.
Volatility Threshold : Threshold for adjusting the lookback period based on volatility.
Key Calculations
Returns Calculation : Computes the daily returns for each input symbol.
Correlation Calculation : Computes the correlation between each input symbol's returns and the ES futures contract returns over the specified correlation length.
Standard Deviation Calculation : Computes the standard deviation for each input symbol's returns and the ES futures contract returns.
Beta Calculation : Computes the beta for each input symbol relative to the ES futures contract.
Weighted Returns Calculation : Computes the weighted returns based on the calculated betas.
Lead-Lag Indicator : Calculates a lead-lag indicator by averaging the weighted returns.
Volatility Filter : Smooths the lead-lag indicator using a simple moving average.
Price Target Estimation : Estimates the ES price target based on the lead-lag indicator (the yellow line on the chart).
Dynamic Stop Loss (SL) and Take Profit (TP) Levels : Calculates dynamic SL and TP levels using volatility bands.
Signal Generation
The indicator generates buy and sell signals based on the filtered lead-lag indicator and confirms them using higher timeframe analysis. Signals are debounced to reduce frequency, ensuring that only significant signals are considered.
Visualization
Background Coloring : The background color changes based on the buy and sell signals for easy visualization (user can toggle this on/off).
Signal Labels : Labels with arrows are plotted on the chart, showing the signal type (buy/sell), the entry price, TP, and SL levels.
Estimated ES Price Target : The estimated price target for ES futures is plotted on the chart.
Correlation and Beta Dashboard : A table displayed in the top right corner shows the current correlation and beta values for relative to the ES futures contract.
Customization
Traders can customize the following parameters to tailor the indicator to their specific needs:
Input Symbols : Change the symbols for BTC, DXY, CL, and ES.
Correlation Length : Adjust the number of periods used for calculating correlation.
Standard Deviation Length : Adjust the number of periods used for calculating standard deviation.
Lookback Period for Beta : Change the lookback period for calculating beta.
Volatility Filter Length : Modify the length of the volatility filter.
Volatility Threshold : Set a threshold for adjusting the lookback period based on volatility.
Plotting Options : Customize the colors and line widths of the plotted elements.
在腳本中搜尋"Volatility"
Volatility Adjusted Weighted DEMA [BackQuant]Volatility Adjusted Weighted DEMA
The Volatility Adjusted Weighted Double Exponential Moving Average (VAWDEMA) by BackQuant is a sophisticated technical analysis tool designed for traders seeking to integrate volatility into their moving average calculations. This innovative indicator adjusts the weighting of the Double Exponential Moving Average (DEMA) according to recent volatility levels, offering a more dynamic and responsive measure of market trends.
Primarily, the single Moving average is very noisy, but can be used in the context of strategy development, where as the crossover, is best used in the context of defining a trading zone/ macro uptrend on higher timeframes.
Why Volatility Adjustment is Beneficial
Volatility is a fundamental aspect of financial markets, reflecting the intensity of price changes. A volatility adjustment in moving averages is beneficial because it allows the indicator to adapt more quickly during periods of high volatility, providing signals that are more aligned with the current market conditions. This makes the VAWDEMA a versatile tool for identifying trend strength and potential reversal points in more volatile markets.
Understanding DEMA and Its Advantages
DEMA is an indicator that aims to reduce the lag associated with traditional moving averages by applying a double smoothing process. The primary benefit of DEMA is its sensitivity and quicker response to price changes, making it an excellent tool for trend following and momentum trading. Incorporating DEMA into your analysis can help capture trends earlier than with simple moving averages.
The Power of Combining Volatility Adjustment with DEMA
By adjusting the weight of the DEMA based on volatility, the VAWDEMA becomes a powerful hybrid indicator. This combination leverages the quick responsiveness of DEMA while dynamically adjusting its sensitivity based on current market volatility. This results in a moving average that is both swift and adaptive, capable of providing more relevant signals for entering and exiting trades.
Core Logic Behind VAWDEMA
The core logic of the VAWDEMA involves calculating the DEMA for a specified period and then adjusting its weighting based on a volatility measure, such as the average true range (ATR) or standard deviation of price changes. This results in a weighted DEMA that reflects both the direction and the volatility of the market, offering insights into potential trend continuations or reversals.
Utilizing the Crossover in a Trading System
The VAWDEMA crossover occurs when two VAWDEMAs of different lengths cross, signaling potential bullish or bearish market conditions. In a trading system, a crossover can be used as a trigger for entry or exit points:
Bullish Signal: When a shorter-period VAWDEMA crosses above a longer-period VAWDEMA, it may indicate an uptrend, suggesting a potential entry point for a long position.
Bearish Signal: Conversely, when a shorter-period VAWDEMA crosses below a longer-period VAWDEMA, it might signal a downtrend, indicating a possible exit point or a short entry.
Incorporating VAWDEMA crossovers into a trading strategy can enhance decision-making by providing timely and adaptive signals that account for both trend direction and market volatility. Traders should combine these signals with other forms of analysis and risk management techniques to develop a well-rounded trading strategy.
Alert Conditions For Trading
alertcondition(vwdema>vwdema , title="VWDEMA Long", message="VWDEMA Long - {{ticker}} - {{interval}}")
alertcondition(vwdema
Volatility Exponential Moving AverageVEMA is a custom indicator that enhances the traditional moving average by incorporating market volatility. Unlike standard moving averages that rely solely on price, VEMA integrates both the Simple Moving Average (SMA) and the Exponential Moving Average (EMA) of the closing price, alongside a measure of market volatility.
The unique aspect of VEMA is its approach. It calculates the standard deviation of the closing price and also computes the simple moving average of this volatility. This dual approach to understanding market fluctuations allows for a more nuanced understanding of market dynamics.
Key to VEMA's functionality is the dynamic weighting factor, which adjusts the influence of SMA and EMA based on current market volatility. This factor increases the weight of the EMA, which is more responsive to recent price changes, during periods of high volatility. Conversely, during periods of lower volatility, the SMA, which offers a smoother view of price trends, becomes more prominent.
The resultant is a hybrid moving average that responds adaptively to changes in market volatility. This adaptability makes VEMA particularly useful in dynamic markets, potentially offering more insightful trend analysis and reversal signals compared to traditional moving averages.
Simple RangeThe daily price range is a good proxy to judge an instrument’s volatility. I have combined multiple concepts in this indicator to display information regarding the daily price range & its volatility.
A trading period's range is simply the difference between its high and the low. This script shows the daily high-to-low range of the price as a column chart. It has 3 main components:
1. Narrow-range days (NR7) & Wide-range Days (WR20) - as plot columns
Original concept from Thomas Bulkowski
Modified from "NR4 & NR7 Indicator" script by theapextrader7
Modified from "WR - BC Identifier" script by wrpteam2020
Narrow range days mark price contractions that often precede price expansions. This script uses NR7 (narrow range 7) as a narrow-range day. This value can be changed by the user if, instead of an NR7, he or she wishes to use NR4 or NR21, or any other interval of his or her choice. NR7 is an indecisive trading day in which the range is narrower than any of the previous six days (a total of 7 days). This is a popular concept given by Thomas Bulkowski. A breakout is said to occur when price closes above the top or below the bottom of the NR7. Upside breakout of an NR 7 candle with high volumes indicates bullishness.
Similarly, highs & lows of wide-range bars (on big volumes) are also significant reference levels for price. Wide-range candle are identified by size of the body candle (open - close). The script compares the size of previous 20 candles to identify WR20 candles. This value can also be changed by the user.
The script shows NR7 & WR20 as orange & blue bars, respectively.
The user can also turn on the option to identify a big high-to-low range candle greater than a pre-defined threshold (default is 5%). These show up as green or red bars.
2. TTM Squeeze - as background
Original concept from John Carter's book "Mastering the Trade"
Based on "Squeeze Momentum Indicator" script by LazyBear
John Carter’s TTM Squeeze indicator looks at the relationship between Bollinger Bands and Keltner's Channels to help identify period of volatility contractions. Bollinger Bands being completely enclosed within the Keltner Channels is indicative of a very low volatility. This is a state of volatility contraction known as squeeze. Using different ATR lengths (1.0, 1.5 and 2.0) for Keltner Channels, we can differentiate between levels of squeeze (High, Mid & Low compression, respectively). Greater the compression, higher the potential for explosive moves.
In the script, the High, Mid & Low compression squeezes are depicted via the background color being red, orange, or yellow, respectively.
3. Average Daily Range - as table
Original idea by alpine_trader
Modified from "ADR% - Average Daily Range % by MikeC" script by TheScrutiniser
Average Day Range (ADR) tells how much the price moves between the high and low on a given day. This is the day Range, which is then averaged to create ADR. The script uses an average of the last 20 days to calculate the ADR. Unlike ATR (Average True Range), this excludes Gaps.
The script displays the ADR as a % value in a table.
If you want to find stocks that move a lot on an average on most days, then look for stocks that have ADR% of 5% or more.
If you prefer lower volatility stocks, focus on stocks with lower ADR% values, such as 2% or less.
How it comes together
For a bullish "momentum burst", or a velocity trade:
Select stocks with Average Day Range % (ADR) greater than 5
Identify significant reference price levels via highs & lows of WR20 bars (on big volumes)
Wait for a decent mid-to-high compression squeeze
Look for clusters of NR7 candles in the consolidation
Any breakout from this consolidation should be accompanied by more than average (preferably pocket pivot) volumes
trend_vol_forecastNote: The following description is copied from the script's comments. Since TradingView does not allow me to edit this description, please refer to the comments and release notes for the most up-to-date information.
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USAGE
This script compares trend trading with a volatility stop to "buy and hold".
Trades are taken with the trend, except when price exceeds a volatility
forecast. The trend is defined by a moving average crossover. The forecast
is based on projecting future volatility from historical volatility.
The trend is defined by two parameters:
- long: the length of a long ("slow") moving average.
- short: the length of a short ("fast") moving average.
The trend is up when the short moving average is above the long. Otherwise
it is down.
The volatility stop is defined by three parameters:
- volatility window: determines the number of periods in the historical
volatility calculation. More periods means a slower (smoother)
estimate of historical volatility.
- stop forecast periods: the number of periods in the volatility
forecast. For example, "7" on a daily chart means that the volatility
will be forecasted with a one week lag.
- stop forecast stdev: the number of standard deviations in the stop
forecast. For example, "2" means two standard deviations.
EXAMPLE
The default parameters are:
- long: 50
- short: 20
- volatility window: 30
- stop forecast periods: 7
- stop forecast standard deviations: 1
The trend will be up when the 20 period moving average is above the 50
period moving average. On each bar, the historical volatility will be
calculated from the previous 30 bars. If the historical volatility is 0.65
(65%), then a forecast will be drawn as a fuchsia line, subtracting
0.65 * sqrt(7 / 365) from the closing price. If price at any point falls
below the forecast, the volatility stop is in place, and the trend is
negated.
OUTPUTS
Plots:
- The trend is shown by painting the slow moving average green (up), red
(down), or black (none; volatility stop).
- The fast moving average is shown in faint blue
- The previous volatility forecasts are shown in faint fuchsia
- The current volatility forecast is shown as a fuchsia line, projecting
into the future as far as it is valid.
Tables:
- The current historical volatility is given in the top right corner, as a
whole number percentage.
- The performance table shows the mean, standard deviation, and sharpe
ratio of the volatility stop trend strategy, as well as buy and hold.
If the trend is up, each period's return is added to the sample (the
strategy is long). If the trend is down, the inverse of each period's
return is added to the sample (the strategy is short). If there is no
trend (the volatility stop is active), the period's return is excluded
from the sample. Every period is added to the buy-and-hold strategy's
sample. The total number of periods in each sample is also shown.
Circuit Breaker Table (NSE Style)🛡️ NSE Circuit Breaker Table – With Volatility-Based Band Support
This script displays a real-time circuit breaker table for any stock, showing the Upper and Lower circuit limits in a clean 2x2 grid. It’s especially useful for Indian traders monitoring NSE-listed stocks.
✅ Key Features:
📊 Upper & Lower Limits based on the previous day’s close
⚡ Optional ATR-based dynamic volatility band calculation
🎨 Customizable font sizes (Small / Medium / Large)
✅ Table neatly positioned on the top-right corner of your chart
🟢 Upper circuit shown in green, 🔴 lower circuit in red
Works on all NSE stocks and adapts automatically to charted symbols
⚙️ Customization Options:
Use static percentage bands (e.g., 10%)
Or enable ATR mode to reflect dynamic circuit potential based on recent volatility
This tool helps you stay aware of where a stock might get halted — useful for momentum traders, circuit breakout traders, and anyone monitoring volatility limits during intraday sessions.
Frahm Factor Position Size CalculatorThe Frahm Factor Position Size Calculator is a powerful evolution of the original Frahm Factor script, leveraging its volatility analysis to dynamically adjust trading risk. This Pine Script for TradingView uses the Frahm Factor’s volatility score (1-10) to set risk percentages (1.75% to 5%) for both Margin-Based and Equity-Based position sizing. A compact table on the main chart displays Risk per Trade, Frahm Factor, and Average Candle Size, making it an essential tool for traders aligning risk with market conditions.
Calculates a volatility score (1-10) using true range percentile rank over a customizable look-back window (default 24 hours).
Dynamically sets risk percentage based on volatility:
Low volatility (score ≤ 3): 5% risk for bolder trades.
High volatility (score ≥ 8): 1.75% risk for caution.
Medium volatility (score 4-7): Smoothly interpolated (e.g., 4 → 4.3%, 5 → 3.6%).
Adjustable sensitivity via Frahm Scale Multiplier (default 9) for tailored volatility response.
Position Sizing:
Margin-Based: Risk as a percentage of total margin (e.g., $175 for 1.75% of $10,000 at high volatility).
Equity-Based: Risk as a percentage of (equity - minimum balance) (e.g., $175 for 1.75% of ($15,000 - $5,000)).
Compact 1-3 row table shows:
Risk per Trade with Frahm score (e.g., “$175.00 (Frahm: 8)”).
Frahm Factor (e.g., “Frahm Factor: 8”).
Average Candle Size (e.g., “Avg Candle: 50 t”).
Toggles to show/hide Frahm Factor and Average Candle Size rows, with no empty backgrounds.
Four sizes: XL (18x7, large text), L (13x6, normal), M (9x5, small, default), S (8x4, tiny).
Repositionable (9 positions, default: top-right).
Customizable cell color, text color, and transparency.
Set Frahm Factor:
Frahm Window (hrs): Pick how far back to measure volatility (e.g., 24 hours). Shorter for fast markets, longer for chill ones.
Frahm Scale Multiplier: Set sensitivity (1-10, default 9). Higher makes the score jumpier; lower smooths it out.
Set Margin-Based:
Total Margin: Enter your account balance (e.g., $10,000). Risk auto-adjusts via Frahm Factor.
Set Equity-Based:
Total Equity: Enter your total account balance (e.g., $15,000).
Minimum Balance: Set to the lowest your account can go before liquidation (e.g., $5,000). Risk is based on the difference, auto-adjusted by Frahm Factor.
Customize Display:
Calculation Method: Pick Margin-Based or Equity-Based.
Table Position: Choose where the table sits (e.g., top_right).
Table Size: Select XL, L, M, or S (default M, small text).
Table Cell Color: Set background color (default blue).
Table Text Color: Set text color (default white).
Table Cell Transparency: Adjust transparency (0 = solid, 100 = invisible, default 80).
Show Frahm Factor & Show Avg Candle Size: Check to show these rows, uncheck to hide (default on).
OA - Sigma BandsDescription:
The OA - Sigma Bands indicator is a fully adaptive, volatility-sensitive dynamic band system designed to detect price expansion and potential breakouts. Unlike traditional fixed-width Bollinger Bands, OA - Sigma Bands adjust their boundaries based on a combination of standard deviation (σ) and Average Daily Range (ADR), making them more responsive to real market behavior and shifts in volatility.
Key Concepts & Logic
This tool constructs three distinct band regions:
Sigma Bands (±σ):
Calculated using the standard deviation of the closing price over a user-defined lookback period. This acts as the core volatility filter to identify statistically significant price deviations.
ADR Zones (±ADR):
These zones provide an additional layer based on the percentage average of daily price ranges over the last 20 bars. They help visualize intraday or short-term expected volatility.
Dynamic Adjustment Logic:
When price breaks outside the upper/lower sigma or ADR boundaries for a defined number of bars (user input), the system recalibrates. This ensures that the bands evolve with volatility and don’t remain outdated in trending markets.
Inputs & Customization
Sigma Multiplier: Set how wide the sigma bands should be (default: 1.5).
Lookback Period: Controls how many bars are used to calculate the standard deviation (default: 200).
Break Confirmation Bars: Determines how many candles must close beyond a boundary to trigger band recalibration.
ADR Period: Internally fixed at 20 bars for stable short-term volatility measurement.
Full Color Customization: Customize the band colors and fill transparency to suit your chart style.
Benefits & Use Cases
Breakout Trading: Detect when price exits statistically significant ranges, confirming trend expansion.
Mean Reversion: Use the outer bands as potential reversion zones in sideways or low-volatility markets.
Volatility Awareness: Visually identify when price is compressed or expanding.
Dynamic Structure: The auto-updating nature makes it more reliable than static historical zones.
Overlay-Ready: Designed to sit directly on price charts with minimal clutter.
Disclaimer
This script is intended for educational and informational purposes only. It does not constitute investment advice, financial guidance, or a recommendation to buy or sell any security. Always perform your own research and apply proper risk management before making trading decisions.
If you enjoy this script or find it useful, feel free to give it or leave a comment!
ConeCastConeCast is a forward-looking projection indicator that visualizes a future price range (or "cone") based on recent trend momentum and adaptive volatility. Unlike lagging bands or reactive channels, this tool plots a predictive zone 3–50 bars ahead, allowing traders to anticipate potential price behavior rather than merely react to it.
How It Works
The core of ConeCast is a dynamic trend-slope engine derived from a Linear Regression line fitted over a user-defined lookback window. The slope of this trend is projected forward, and the cone’s width adapts based on real-time market volatility. In calm markets, the cone is narrow and focused. In volatile regimes, it expands proportionally, using an ATR-based % of price to scale.
Key Features
📈 Predictive Cone Zone: Visualizes a forward range using trend slope × volatility width.
🔄 Auto-Adaptive Volatility Scaling: Expands or contracts based on market quiet/chaotic states.
📊 Regime Detection: Identifies Bull, Bear, or Neutral states using a tunable slope threshold.
🧭 Multi-Timeframe Compatible: Slope and volatility can be calculated from higher timeframes.
🔔 Smart Alerts: Detects price entering the cone, and signals trend regime changes in real time.
🖼️ Clean Visual Output: Optionally includes outer cones, trend-trail marker, and dashboard label.
How to Use It
Use on 15m–4H charts for best forward visibility.
Look for price entering the cone as a potential trend continuation setup.
Monitor regime changes and volatility expansion to filter choppy market zones.
Tune the slope sensitivity and ATR multiplier to match your symbol's behavior.
Use outer cones to anticipate aggressive swings and wick traps.
What Makes It Unique
ConeCast doesn’t follow price — it predicts a possible future price envelope using trend + volatility math, without relying on lagging indicators or repainting logic. It's a hybrid of regression-based forecasting and dynamic risk zoning, designed for swing traders, scalpers, and algo developers alike.
Limitations
ConeCast projects based on current trend and volatility — it does not "know" future price. Like all projection tools, accuracy depends on trend persistence and market conditions. Use this in combination with confirmation signals and risk management.
Quantile DEMA Trend | QuantEdgeB🚀 Introducing Quantile DEMA Trend (QDT) by QuantEdgeB
🛠️ Overview
Quantile DEMA Trend (QDT) is an advanced trend-following and momentum detection indicator designed to capture price trends with superior accuracy. Combining DEMA (Double Exponential Moving Average) with SuperTrend and Quantile Filtering, QDT identifies strong trends while maintaining the ability to adapt to various market conditions.
Unlike traditional trend indicators, QDT uses percentile filtering to adjust for volatility and provides dynamic thresholds, ensuring consistent signal performance across different assets and timeframes.
✨ Key Features
🔹 Trend Following with Adaptive Sensitivity
The DEMA component ensures quicker responses to price changes while reducing lag, offering a real-time reflection of market momentum.
🔹 Volatility-Adjusted Filtering
The SuperTrend logic incorporates quantile percentile filters and ATR (Average True Range) multipliers, allowing QDT to adapt to fluctuating market volatility.
🔹 Clear Signal Generation
QDT generates clear Long and Short signals using percentile thresholds, effectively identifying trend changes and market reversals.
🔹 Customizable Visual & Signal Settings
With multiple color modes and customizable settings, you can easily align the QDT indicator with your trading strategy, whether you're focused on trend-following or volatility adjustments.
📊 How It Works
1️⃣ DEMA Calculation
DEMA is used to reduce lag compared to traditional moving averages. It is calculated by applying a Double Exponential Moving Average to price data. This smoother trend-following mechanism ensures responsiveness to market movements without introducing excessive noise.
2️⃣ SuperTrend with Percentile Filtering
The SuperTrend component adapts the trend-following signal by incorporating quantile percentile filters. It identifies dynamic support and resistance levels based on historical price data:
• Upper Band: Calculated using the 75th percentile + ATR (adjusted with multiplier)
• Lower Band: Calculated using the 25th percentile - ATR (adjusted with multiplier)
These dynamic bands adjust to market conditions, filtering out noise while identifying the true direction.
3️⃣ Signal Generation
• Long Signal: Triggered when price crosses below the SuperTrend Lower Band
• Short Signal: Triggered when price crosses above the SuperTrend Upper Band
The indicator provides signals with corresponding trend direction based on these crossovers.
👁 Visual & Custom Features
• 🎨 Multiple Color Modes: Choose from "Strategy", "Solar", "Warm", "Cool", "Classic", and "Magic" color palettes to match your charting style.
• 🏷️ Long/Short Signal Labels: Optional labels for visual cueing when a long or short trend is triggered.
• 📉 Bar Color Customization: Bar colors dynamically adjust based on trend direction to visually distinguish the market bias.
👥 Who Should Use QDT?
✅ Trend Followers: Use QDT as a dynamic tool to confirm trends and capture profits in trending markets.
✅ Swing Traders: Use QDT to time entries based on confirmed breakouts or breakdowns.
✅ Volatility Traders: Identify market exhaustion or expansion points, especially during volatile periods.
✅ Systematic & Quant Traders: Integrate QDT into algorithmic strategies to enhance market detection with adaptive filtering.
⚙️ Customization & Default Settings
- DEMA Length(30): Controls the lookback period for DEMA calculation
- Percentile Length(10): Sets the lookback period for percentile filtering
- ATR Length(14): Defines the length for calculating ATR (used in SuperTrend)
- ATR Multiplier(1.2 ): Multiplier for ATR in SuperTrend calculation
- SuperTrend Length(30):Defines the length for SuperTrend calculations
📌 How to Use QDT in Trading
1️⃣ Trend-Following Strategy
✔ Enter Long positions when QDT signals a bullish breakout (price crosses below the SuperTrend lower band).
✔ Enter Short positions when QDT signals a bearish breakdown (price crosses above the SuperTrend upper band).
✔ Hold positions as long as QDT continues to provide the same direction.
2️⃣ Reversal Strategy
✔ Take profits when price reaches extreme levels (upper or lower percentile zones) that may indicate trend exhaustion or reversion.
3️⃣ Volatility-Driven Entries
✔ Use the percentile filtering to enter positions based on mean-reversion logic or breakout setups in volatile markets.
🧠 Why It Works
QDT combines the DEMA’s quick response to price changes with SuperTrend's volatility-adjusted thresholds, ensuring a responsive and adaptive indicator. The use of percentile filters and ATR multipliers helps adjust to varying market conditions, making QDT suitable for both trending and range-bound environments.
🔹 Conclusion
The Quantile DEMA Trend (QDT) by QuantEdgeB is a powerful, adaptive trend-following and momentum detection system. By integrating DEMA, SuperTrend, and quantile percentile filtering, it provides accurate and timely signals while adjusting to market volatility. Whether you are a trend follower or volatility trader, QDT offers a robust solution to identify high-probability entry and exit points.
🔹 Key Takeaways:
1️⃣ Trend Confirmation – Uses DEMA and SuperTrend for dynamic trend detection
2️⃣ Volatility Filtering – Adjusts to varying market conditions using percentile logic
3️⃣ Clear Signal Generation – Easy-to-read signals and visual cues for strategy implementation
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Volatility-Driven CandleThis indicator identifies and highlights "volatility-driven candles" on a price chart, based on their body size relative to market volatility. It calculates the Average True Range (ATR) over a 14-period window to measure volatility. A candle is considered "volatility-driven" if its body (the difference between the close and open prices) exceeds a user-defined threshold, which is specified as a multiple of the ATR.
The script distinguishes between bullish and bearish volatility-driven candles:
Bullish volatility-driven candles (where the close is greater than the open) are marked with a blue label.
Bearish volatility-driven candles (where the close is less than the open) are marked with an orange label.
Additionally, the background color of the chart is shaded:
Blue for bullish volatility-driven candles.
Orange for bearish volatility-driven candles.
This script helps traders easily spot significant price movements relative to volatility, highlighting potential reversal points based on candle body size.
Volatility and Tick Size DataThis indicator, titled "Tick Information & Standard Deviation Table," provides detailed insights into market microstructure, including tick size, point value, and standard deviation values calculated based on the True Range. It helps visualize essential trading parameters that influence transaction costs, risk management, and portfolio performance, including volatility measures that can guide investment strategies.
Why These Data Points Are Important for Portfolio Management
Tick Size and Point Value:
Tick size refers to the smallest possible price movement in a given asset. It defines the granularity of the price changes, affecting how precise the market price can be at any moment. Point value reflects the monetary value of a single price movement (one tick). These two data points are essential for understanding transaction costs and for evaluating how much capital is at risk per price movement. Smaller tick sizes may lead to more efficient pricing in high-frequency trading strategies (Hasbrouck, 2009).
Reference: Hasbrouck, J. (2009). Empirical Market Microstructure. Foundations and Trends® in Finance, 3(4), 169-272.
Standard Deviations and Volatility:
Standard deviation measures the variability or volatility of an asset's price over a set period. This data point is critical for portfolio management, as it helps to quantify risk and predict potential price movements. True Range and its standard deviations provide a more comprehensive measure of market volatility than just price fluctuations, as they include gaps and extreme price changes. Investors use volatility data to assess the potential risk and adjust portfolio allocations accordingly (Ang, 2006).
Reference: Ang, A. (2006). Asset Management: A Systematic Approach to Factor Investing. Oxford University Press.
Risk Management:
The ability to quantify risk through metrics like the 1st, 2nd, and 3rd standard deviations of the true range is essential for implementing risk controls within a portfolio. By incorporating volatility data, portfolio managers can adjust their strategies for different market conditions, potentially reducing exposure to high-risk environments. These volatility measures help in setting stop-loss levels, optimizing position sizes, and managing the portfolio’s overall risk-return profile (Black & Scholes, 1973).
Reference: Black, F., & Scholes, M. (1973). The Pricing of Options and Corporate Liabilities. Journal of Political Economy, 81(3), 637-654.
Portfolio Diversification and Hedging:
Understanding asset volatility and transaction costs is critical when constructing a diversified portfolio. By using the standard deviations from this indicator, investors can better identify assets that may provide diversification benefits, potentially reducing the overall portfolio risk. Moreover, the point values and tick sizes help assess the cost-effectiveness of various assets, enabling portfolio managers to implement more efficient hedging strategies (Markowitz, 1952).
Reference: Markowitz, H. (1952). Portfolio Selection. The Journal of Finance, 7(1), 77-91.
Conclusion
The Tick Information & Standard Deviation Table provides critical market data that informs the risk management, diversification, and pricing strategies used in portfolio management. By incorporating tick size, point value, and volatility metrics, investors can make more informed decisions, better manage risk, and optimize the returns on their portfolios. The data serves as an essential tool for aligning asset selection and portfolio allocations with the investor's risk tolerance and market conditions.
Custom ATR Trailing StopThis Script creates a custom ATR (Average True Range) trailing stop. It allows traders to set up automated stop-loss levels based on the ATR, which adjusts dynamically to market volatility. The script is designed to support both long and short trades, offering flexibility and precision in trade management.
When loading the indicator to your chart, simply click to set the trade begining time, confirm various settings and you are set.
Check tooltips for more details in the input settigns menu.
User Inputs
Trade Setup: Allows users to set the trade direction (Long or Short), the signal source for entries, and the specific bar time for the trade setup.
ATR Settings: Configurable ATR lookback period, ATR smoothing period, initial ATR multiplier for setting the stop-loss, breakeven ATR multiplier, and a manual breakeven level.
ATR Calculations
Computes the ATR and its moving average.
Determines initial and breakeven stop levels based on the ATR.
Signal Validation
Validates long or short trade signals based on the specified bar time and trade direction.
Triggers alerts when a valid trade signal is detected.
Trailing Stop Logic
For long trades, adjusts the stop-loss level dynamically based on the ATR.
For short trades, performs similar adjustments in the opposite direction.
Updates the trailing stop level to ensure it follows the price, moving closer as the price moves favorably.
Resets the trade state when the stop-loss is hit, triggering an alert.
Plotting
Plots the trailing stop levels on the chart.
Uses green for stop levels indicating profit and red for stop levels indicating a loss.
0_dteUSAGE
This script guages the probability of an underlying moving a certain amount on expiration day, to aid the popular "0 dte" strategy. The script counts how many next-day moves exceeded a given magnitude in the past, under similar conditions. The inputs are:
mark_mode:
- "open": measures the magnitude as "open to close"--a true 0 dte.
- "previous close": for lazy people who don't want to wake up early. measures magnitude from the previous day's close.
move_mode:
- "percent": measures moves that exceed a given percentage.
- "absolute": measures moves that exceed a point value.
move-dir: measure only up moves, down moves, or both.
vol_model: the model for realized volatility. (may add more later).
min_vol: only measure moves when realized vol is above this value.
max_vol: only measure moves when realized vol is below this value.
precision: number of digits printed in the output table.
EXAMPLE:
- mark_mode: "previous close"
- move_mode: "percent"
- move_dir: "up"
- move_mag: 0.07
- vol_model: hv30
- min_vol: 0.2
- max_vol: 0.5
These settings will count the number of trading days that closed 7% higher than the previous day's close, when the previous day's realized volatility (annualized) was between 20% and 50%. The outputs are:
- current vol: green plot. Today's realized vol. Shown for convenience.
- max and min vol: red plots. Also shown for convenience.
- count: the number of days that exceeded the chosen magnitude, when the previous day's realized volatility was within the chosen bounds.
- total: the total number of days where realized volatility was within the chosen bounds
- probability: count / total. the percentage of days that exceeded the move when volatility was within the bounds.
- move: plotted as a purple line. purple "X" labels are plotted above
- bars where the move exceeded the magnitude threshold and volatility was in-bounds. a "hit".
CONCLUSION
This script is based on the idea that realized volatility has some bearing on future volatility. By seeing what happened in the past when volatility was close to its current value, we may be able to assess the probability that our short put will be in the money, tomorrow, and our account devastated.
NOTE: Unlike many of my other scripts, all percentages--both inputs and outputs--are given in fractional form. E.g., 0.01 means 1%.
ADR(20)% - Qullamagi (corner value) v6This indicator displays the 20-bar Average Daily Range (ADR) either as a percentage of price or in raw dollar terms, shown in a clean corner box on the chart.
Switch between % ADR and $ ADR with a single checkbox.
Place the output box in any chart corner.
Useful for volatility assessment, stop-loss sizing, and stock selection.
Inspired by the trading approach of Kristjan Qullamägi (Qullamaggie), who uses ADR(20) both to filter high-momentum stocks and to size risk (stops should generally be ≤ 1×ADR).
Harmony in Havoc - The Entropy of VoVix Harmony in Havoc – The Entropy of VoVix
There are moments in the market when chaos and order are not opposites, but partners in a dance.
Harmony in Havoc is not just an indicator—it’s a window into that dance.
Most tools try to tame the market by smoothing it, boxing it in, or chasing after what’s already happened. This script does the opposite: it listens for the music beneath the noise, the rare moments when volatility and unpredictability align, and the market’s next movement is about to begin.
What is Harmony in Havoc?
VoVix Spike:
The pulse of volatility-of-volatility. Not just how much the market is moving, but how violently its own heartbeat is changing.
Entropy:
A real-time measure of surprise. When entropy is high, the market is not just moving—it’s breaking its own patterns, rewriting its own rules.
Progression Bar & Status:
The yellow bar is your visual gauge of tension. As it fills, the market is winding up.
Wait: The world is calm.
Get ready!: The storm is building.
Take Action!!: The probability of a regime eruption is at its peak.
Yellow Background:
When the background glows, the market is at its most unstable—this is not a buy or sell signal, but a quant alert.
How does it work?
Every tick, Harmony in Havoc measures the distance between the market’s current volatility and its own unpredictability. When the VoVix spike approaches or exceeds the entropy threshold, the system knows:
“This is the moment when the improbable becomes possible.”
Why is this different?
It doesn’t tell you what to do.
It doesn’t chase price.
It doesn’t care about trends, bands, or the past.
Instead, it gives you a quantitative sense of anticipation—a way to see when the market is most likely to break from its own history, and when the edge is at its sharpest.
How to use it:
Watch for the yellow background and “Take Action!!” status.
Use it as a regime filter, a volatility dashboard, or a warning system for your own strategies.
Tune the inputs for your asset and timeframe—make it your own.
Inputs—explained for you:
VoVix Fast/Slow ATR & Stdev:
Control how sensitive the system is to volatility shocks. Lower = more signals, higher = only the rarest events.
Entropy Window & Bins:
Control how “surprised” the entropy engine is by current volatility. Shorter window = more responsive, more bins = finer detail.
Show/Hide Controls:
Toggle the VoVix spike, entropy line, and their glows to customize your visual experience.
Bottom line:
This is not a buy or sell script.
This is a quant regime detector for those who want to feel the market’s tension—to sense when harmony and havoc are about to collide.
Disclaimer:
Trading is risky. This script is for research and informational purposes only, not financial advice. Backtest, paper trade, and know your risk before going live. Past performance is not a guarantee of future results.
*I've only tested this on 1 and 5 min frames.
Use with discipline. Trade your edge.
— Dskyz, for DAFE Trading Systems
3 days ago
Release Notes
* Now mobile friendly. I've added a toggle to switch the dashboard on/off, and added a mobile information line that shows the same information on the dashboard. This is to allow the script to stay visually in balance and this also has a toggle.
* Background color added that coresponds with Buy or Sell areas.
ATR Impact CandlesATR Impact Candles: Simplify Your Trading with Pure Price Action
You don’t need dozens of cluttered indicators to catch what really matters. With ATR Impact Candles, you get a powerful, single-tool solution that cuts through the noise by focusing on what truly drives the market: price action and volatility. This indicator highlights only those candlesticks that pack a punch—showing you when the market’s range is exceptionally strong relative to its recent behavior. Whether you’re a scalper or a swing trader, ATR Impact Candles empowers you to time your entries and exits with confidence, letting you trade based on real market momentum.
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Indicator Overview
The indicator is designed for TradingView and is implemented in Pine Script (version 5). Its primary purpose is to highlight specific candles that meet a defined volatility condition based on the Average True Range (ATR). Instead of modifying every candle’s appearance, the indicator only changes the color of those “signal” candles that exceed a user-defined multiple of the ATR. The rest of the candles remain in their traditional black and white appearance—preserving the classic candlestick chart look.
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Key Features
1. ATR-Based Signal Identification:
• ATR Calculation:
The indicator calculates the ATR using a configurable lookback period (default is 14 periods). The ATR is a common volatility measure that reflects the average range of price movement.
• Threshold Condition:
A candle is flagged as a signal if its range (high minus low) meets or exceeds a specified multiple (the “ATR Factor”) of the ATR. By default, this factor is set to 2, meaning any candle whose range is at least twice the ATR is considered significant.
2. Dynamic Candle Coloring:
• Signal Candles:
• When a candle meets the ATR threshold condition:
• Up Candles: are colored green.
• Down Candles: are colored red.
• Non-Signal Candles:
• Candles that do not meet the threshold condition retain their classic appearance:
• Up candles are white.
• Down candles are black.
3. User Configurability:
• ATR Period:
Traders can adjust the ATR period to tailor the volatility measure to different markets or timeframes.
• ATR Factor:
The multiple of the ATR that defines a signal candle is also configurable, giving flexibility to experiment with different thresholds for what constitutes “significant” price movement.
• Overlay Display:
The indicator runs in overlay mode on the chart, meaning it directly affects the appearance of the candlestick bars without interfering with other chart elements.
4. Additional Visual Aid:
• Threshold Line Plot:
The script optionally plots a line representing the ATR multiplied by the chosen factor. This line serves as a visual benchmark on the chart, allowing traders to see at what level the ATR threshold lies relative to the price action.
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How It Works
1. ATR Calculation:
The indicator first calculates the Average True Range (ATR) for the defined period. This value is updated for each new candle.
2. Range Comparison:
For each candle, the indicator calculates the range (high - low) and compares it to the threshold, which is the ATR multiplied by the user-defined factor.
3. Conditional Coloring:
• If the Candle’s Range ≥ (ATR * Factor):
• The candle is marked as a “signal candle.”
• Its color is set to green if it is an up candle (close is greater than or equal to open) or red if it is a down candle.
• Otherwise:
• The candle retains its classic look, with up candles in white and down candles in black.
4. Chart Display:
By applying these rules to every candle, the indicator visually emphasizes those moments when the market shows unusually large price movements relative to its recent average volatility. This helps traders quickly spot potential breakouts or reversals.
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Practical Applications
• Volatility Breakouts:
Identify candles that may signal the start of a breakout or strong reversal.
• Risk Management:
Adjust stop-loss levels or position sizes when unusually volatile candles are detected.
• Signal Confirmation:
Combine with other technical indicators or chart patterns to reinforce entry or exit decisions.
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ATR Impact Candles is your essential, no-nonsense tool for filtering out market noise and focusing solely on significant price action. Simplify your trading decisions and harness the power of volatility with one clear, effective indicator.
Connors VIX Reversal III invented by Dave LandryThis strategy is based on trading signals derived from the behavior of the Volatility Index (VIX) relative to its 10-day moving average. The rules are split into buying and selling conditions:
Buy Conditions:
The VIX low must be above its 10-day moving average.
The VIX must close at least 10% above its 10-day moving average.
If both conditions are met, a buy signal is generated at the market's close.
Sell Conditions:
The VIX high must be below its 10-day moving average.
The VIX must close at least 10% below its 10-day moving average.
If both conditions are met, a sell signal is generated at the market's close.
Exit Conditions:
For long positions, the strategy exits when the VIX trades intraday below its previous day’s 10-day moving average.
For short positions, the strategy exits when the VIX trades intraday above its previous day’s 10-day moving average.
This strategy is primarily a mean-reversion strategy, where the market is expected to revert to a more normal state after the VIX exhibits extreme behavior (i.e., large deviations from its moving average).
About Dave Landry
Dave Landry is a well-known figure in the world of trading, particularly in technical analysis. He is an author, trader, and educator, best known for his work on swing trading strategies. Landry focuses on trend-following and momentum-based techniques, teaching traders how to capitalize on shorter-term price swings in the market. He has written books like "Dave Landry on Swing Trading" and "The Layman's Guide to Trading Stocks," which emphasize practical, actionable trading strategies.
About Connors Research
Connors Research is a financial research firm known for its quantitative research in financial markets. Founded by Larry Connors, the firm specializes in developing high-probability trading systems based on historical market behavior. Connors’ work is widely respected for its data-driven approach, including systems like the RSI(2) strategy, which focuses on short-term mean reversion. The firm also provides trading education and tools for institutional and retail traders alike, emphasizing strategies that can be backtested and quantified.
Risks of the Strategy
While this strategy may appear to offer promising opportunities to exploit extreme VIX movements, it carries several risks:
Market Volatility: The VIX itself is a measure of market volatility, meaning the strategy can be exposed to sudden and unpredictable market swings. This can result in whipsaws, where positions are opened and closed in rapid succession due to sharp reversals in the VIX.
Overfitting: Strategies based on specific conditions like the VIX closing 10% above or below its moving average can be subject to overfitting, meaning they work well in historical tests but may underperform in live markets. This is a common issue in quantitative trading systems that are not adaptable to changing market conditions .
Mean-Reversion Assumption: The core assumption behind this strategy is that markets will revert to their mean after extreme movements. However, during periods of sustained trends (e.g., market crashes or rallies), this assumption may break down, leading to prolonged drawdowns.
Liquidity and Slippage: Depending on the asset being traded (e.g., S&P 500 futures, ETFs), liquidity issues or slippage could occur when executing trades at market close, particularly in volatile conditions. This could increase costs or worsen trade execution.
Scientific Explanation of the Strategy
The VIX is often referred to as the "fear gauge" because it measures the market's expectations of volatility based on options prices. Research has shown that the VIX tends to spike during periods of market stress and revert to lower levels when conditions stabilize . Mean reversion strategies like this one assume that extreme VIX levels are unsustainable in the long run, which aligns with findings from academic literature on volatility and market behavior.
Studies have found that the VIX is inversely correlated with stock market returns, meaning that higher VIX levels often correspond to lower stock prices and vice versa . By using the VIX’s relationship with its 10-day moving average, this strategy aims to capture reversals in market sentiment. The 10% threshold is designed to identify moments when the VIX is significantly deviating from its norm, signaling a potential reversal.
However, academic research also highlights the limitations of relying on the VIX alone for trading signals. The VIX does not predict market direction, only volatility, meaning that it cannot indicate the magnitude of price movements . Furthermore, extreme VIX levels can persist longer than expected, particularly during financial crises.
In conclusion, while the strategy is grounded in well-established financial principles (e.g., mean reversion and the relationship between volatility and market performance), it carries inherent risks and should be used with caution. Backtesting and careful risk management are essential before applying this strategy in live markets.
VIX-Heatmap [CrossTrade]The "VIX-Heatmap" is a sophisticated and informative indicator designed for traders who want to integrate volatility analysis into their trading strategy, especially focusing on the market's fear gauge, the VIX (Volatility Index). This tool is not just about plotting numbers; it's about visualizing market sentiment in a more intuitive and impactful way.
Key Features and Customization Options:
1. Primary Functionality:
At its core, the VIX-Heatmap tracks the daily closing price of the VIX. It provides a clear, line-based visualization, with the line color set to black for stark contrast and easy visibility.
2. Segmented Volatility Levels:
The indicator allows users to set multiple VIX levels: Danger Zone (super low VIX level), and Levels 1 through 5. These levels are represented as horizontal lines on the chart, offering a structured view of different volatility thresholds.
3. Customizable Thresholds:
Traders can input their preferred values for each level, tailoring the indicator to fit their perception of market risk and volatility. This customization makes the tool versatile for different trading styles and market conditions.
4. Heatmap Visualization:
The chart's background color changes based on the VIX level, creating a "heatmap" effect. This visual representation allows traders to quickly gauge the current market sentiment. The color intensity varies from white (for extremely low VIX values) through various shades of red, increasing in intensity with higher VIX levels. This gradient provides an immediate visual cue of rising or falling market anxiety.
5. Interactive Display:
The indicator includes an interactive table display at the bottom center of the chart that shows the current VIX level in large, bold text, ensuring that it catches the trader's eye.
6. Optional Background Coloring:
Users have the option to enable or disable the heatmap feature. When enabled, the chart's background reflects the VIX level with the corresponding color, enhancing the visual impact of the data.
Applications and Benefits:
The VIX-Heatmap is ideal for traders who base their decisions not only on price movements but also on market sentiment and volatility. Its color-coded heatmap approach simplifies the interpretation of the VIX data, making it accessible even to those who may not be deeply familiar with volatility indices. By offering a quick visual summary of current market fear levels, it aids in making informed decisions, especially in times of market uncertainty.
In summary, the VIX-Heatmap transforms the traditional VIX data into an interactive, visually engaging, and easy-to-interpret format.
Volatility Adjusted Composite RSI with SMA and EMA SignalsOverview
The script "VAC - RSI with SMA and EMA Signals" combines the traditional Relative Strength Index (RSI) with Time-based RSI (T-RSI), and adjusts it for volatility to create a Composite RSI (C-RSI). The script further uses Simple Moving Average (SMA) and Exponential Moving Average (EMA) to generate signals for potential trading opportunities. In the "VAC - RSI with SMA and EMA Signals" script, the combination of price, time, and volatility works as follows:
Price: The script calculates the traditional RSI based on price changes over a specified period.
Time: Alongside the price-based RSI, a Time-based RSI (T-RSI) is calculated, which considers the number of upward and downward closes over the same period.
Volatility: Volatility is integrated into the Composite RSI (C-RSI) by adjusting it with a Z-score based on a standard deviation of closing prices.
These three factors work together to create a more holistic and robust indicator.
How can it be used?
This script is used to identify potential overbought and oversold conditions in the market. It plots the VAC-RSI, SMA, and EMA on a chart, along with overbought and oversold levels, providing visual signals to the trader. When the EMA is below the SMA, it is a bullish signal, and vice versa for a bearish signal.
Default Values for Different Inputs:
Price RSI Weightage (%): 65
Unified Period for RSI & T-RSI: 14
C-RSI SMA Period: 13
C-RSI EMA Period: 33
C-RSI Bull Trend Support: 35
C-RSI Bear Trend Resistance: 65
Use Volatility Adjusted C-RSI (VAC-RSI): true
Standard Deviation Period: 14
Volatility Scaling Factor (α): 5
These values can be adjusted according to the trading strategy to optimize the signals for different assets or timeframes.
Strategies this Can be Used for:
The script can be used in various trading strategies including:
Trend Following: By observing the crosses of EMA and SMA, traders can follow the trend.
Reversion to the Mean: Using the overbought and oversold levels to identify potential reversal points.
Breakout: Identifying breakout points using the Bull and Bear Market Support and Resistance levels.
Comparison with the Standard Indicator:
Enhanced Sensitivity to Market Conditions
Improved Signal Quality
Versatility
Volatility Adjustment
Interpretation of Output Values:
VAC-RSI Value:
The script provides additional overbought (80) and oversold (20) lines to help identify extreme conditions.
SMA and EMA Values:
When the EMA is below the SMA, it is generally considered a bullish signal.
When the EMA is above the SMA, it is generally considered a bearish signal.
The cross of EMA and SMA can be used as a trigger for entry or exit points.
Bull and Bear Market Support and Resistance Lines:
The Bull Market VAC-RSI Support (default at 35) and Bear Market VAC-RSI Resistance (default at 65) lines can be used to identify potential breakout or breakdown points.
In a bull market, if the VAC-RSI stays above the support line, it indicates a strong uptrend.
In a bear market, if the VAC-RSI stays below the resistance line, it indicates a strong downtrend.
Loro Vola StopThis indicator is a variation of a chandelier volatility stop using an average true range. The indicator draws a green support line in an uptrend and a red resistance line in a downtrend. The signals normally should be used as exit triggers.
Lancelot vstop intraday trending strategyDear all,
Free strategy again.
I found using 3 volatility stop with different settings could be very helpful when trading an intraday trending market.
With the ATR setting or 5, 10, 15, we can weed out many false break.
Vstop setting is OHLC4.
On the other hand, this strategy also utilize Renko as part of the strategy, so you could say this strategy is mainly an intraday break out trend following strategy.
Works well on BTCUSD XBTUSD, as well as other major liquid alt Pairs.
And lastly,
Save Hong Kong, the revolution of our times.
CloudRest ATR based cloudThis is an indicator I have been working on for the past 2 years, developed specifically for cryptocurrency.
It is primarily a trend following indicator with great success and it performs the best in 4hrs to the weekly chart.
There are two components of this indicator.
The baseline from Ichimoku cloud and volatility stop .
baseline period = 26
volatility stop = 1.5ATR, 3
You can view this as the main component of a trend following system but you will need other confirmation indicators to confirm your entry.
Feel free to modify the script for your own system.
Feel free to follow me on twitter @Lancelot_Auger
I will be posting more content in the future, stay tuned.
And lastly,
Free hong kong, the revolution of our time!
