Volatility Prism [Nic]What is this
The volatility rainbow tracks divergences in a security and its volatility index. This can be used to identify periods of heightened implied (future) risk.
About Volatility
The volatility is calculated by looking at put / call ratios. When VIX goes up it means that puts are outpacing calls. This is a bearish signal.
About Correlation
When the security goes up while the VIX goes up, the divergence on the plot will increase and turn a color. This should be a warning.
Volatility Rainbow
This is a similar indicator, but this one merges all signals into a single line.
在腳本中搜尋"Volatility"
Turtle N NormalizedSimple script that calculates the normalized value of N. Rules taken from an online PDF containing the original Turtle system:
"The Turtles used a volatility-based constant percentage risk position sizing algorithm. The Turtles used a concept that Richard Dennis and Bill Eckhardt called N to represent the underlying volatility of a particular market.
N is simply the 20-day exponential moving average of the True Range, which is now more commonly known as the ATR. Conceptually, N represents the average range in price movement that a particular market makes in a single day, accounting for opening gaps. N was measured in the same points as the underlying contract.
The Turtles built positions in pieces which we called Units. Units were sized so that 1 N represented 1% of the account equity. Thus, a unit for a given market or commodity can be calculated using the following formula:
Unit = 1% of Account/(N x Dollars per Point)"
To normalize the Unit formula, this script instead takes the value of (close/N). Dollars per point = 1 for stocks and crypto, but will change depending on the contract specifications for individual futures.
"Since the Turtles used the Unit as the base measure for position size, and since those units were volatility risk adjusted, the Unit was a measure of both the risk of a position, and of the entire portfolio of positions."
When the value of N is high, volatility is low and you should be more risk-on.
When the value of N is low, volatility is high and you should be more risk-off.
Bermaui Deviation PercentHow it works
Red & Under 90 = Bearish Volatility
Blue & Under 90 = Bullish Volatility
Red & Under 10 = Strong Bearish Volatility
Blue & Under 10 = Strong Bullish Volatility
White & Over 90 = No Volatility (Indicating trendless chop)
I tried uploading this months ago but was banned or something from doing so.
originally created by Muhammad Elbermawi
www.mql5.com
Efficient Trend Step - Spotting Trends EfficientlyIntroduction
The trend-step indicator (or auto-line) was based on volatility and aimed to spot trends in an adaptive way, however the indicator was only based on volatility and didn't gave much attention to the trend, later on i would publish an efficient version of it (efficient auto-line) based on the efficiency ratio who could adapt to the trend and eliminate potential whipsaws trades, however this approach included many settings that would require changes if the user switched markets, which reduce the utility of the indicator and make it actually super inefficient.
This is why i had to propose this indicator who remove all the flaws the efficient auto-line had without removing the core idea of it.
The Indicator
The indicator is based on recursion, when the price is superior/inferior to the indicator precedent value +/- volatility metric, then the indicator is equal to the closing price, this allow the indicator to fit the price relatively well. The volatility metric used is based on 2 standard deviations, one fast and one slow and the efficiency ratio, basically when price is trending the volatility metric will be closer to the value of the fast standard deviations, which would allow the indicator to be closer to the price, else the metric will be closer to the slow standard deviation which restrain the indicator from changing, therefore the volatility metric act as a threshold.
length control the period of the efficiency ratio, lower values of length will result in a volatility metric way closer to the fast standard deviation thus making the indicator more inclined toward making false signals.
Lower values for slow will make the indicator more reactive.
The indicator can be reactive but can also be really conservative, thus even remaining unchanged in some contrary movements of the main trend, this is called robustness and has its pro's and con's.
Conclusion
The trend-step indicators family might get to an end, or not, nonetheless they can provide precise entries and be extremely robust, which is great. Using low settings might prove to be useful to remove some noise. I hope this version find its use amongst the community. Thanks for reading !
Squeeze PRO Arrows [Makit0]SQUEEZE PRO INDICATOR v0.5Beta
Script based in:
original John Carter's ideas (SQUEEZE & SQUEEZE PRO)
LazyBear's script (Squeeze Momentum Indicator)
USE IT IN CONJUNCTION WITH THE SQUEEZE PRO INDICATOR
This system is based in the volatility reversion to the mean: volatility contraction leads to volatility expansion and the other way on
The arrows signal is a warning of volatility compression, more often than not this leads to a expansion of volatility and a move in the action price usually bigger than the expected move
Be aware of the trend direction don't take the arrows direction as certanty, use instead the momentum histogram in the Squeeze PRO Indicator to see the slope direction
By default the arrows are setted at 5 dots, they fire in the sixth dot after 5 dots of the same color. Try differents values to get more or less signals
here are 3 levels of compression:
Level 1: ORANGE, the lesser compresion level
Level 2: RED, the normal level marked by the original squeeze indicator
Level 3: YELLOW, the max compression level
The more the compression the bigger the after move
Simple and Exponential Moving Averages
There are 2 groups of Moving Averages within the indicator, the 8 & 21 EMAs and the 50, 100 & 200 SMAs
They are disabled by default, turn it on at your peace
Please check the John Carter's book (Mastering the Trade) and attend his webinars for more insight about the squeeze & squeeze pro systems
I'm starting at trading and learning every day, I attended one of his webinars about the Squeeze Pro, and with help of the LazyBear's Squeeze Momentum Indicator code up the Squeeze PRO.
Please be aware, I'm not an expert trader, only a developer with an idea: learn to pull out money from the market in a consistent way.
This is a Beta version, please feel free to comment and give feedback, anything you consider iteresting, the more you elaborate the better :D
Thanks you all!!!
Navier-Cauchy Market Elasticity [PhenLabs]📊 Navier-Cauchy Market Elasticity
Version: PineScript™ v6
📌 Description
The Navier-Cauchy Market Elasticity (NCME) indicator takes a new step into technical analysis by applying materials science principles to financial markets. Similar to last weeks release utilizing Navier-Stokes dynamics equation this indicator focuses on the elastic interaction of virtual “solids”. Based on elasticity theory used in engineering, NCME treats price movements as material deformations, calculating market stress and strain using proven physics formulas. This unique approach reveals hidden market dynamics invisible to traditional indicators.
By implementing Lamé parameters and Young’s modulus calculations, NCME identifies critical stress points where markets exhibit extreme tension or compression. These zones often precede significant price movements, providing traders with advanced warning of potential reversals or breakouts.
🚀 Points of Innovation
• First indicator to apply Navier-Cauchy elasticity equations to market analysis
• Dynamic stress tensor calculations adapted for one-dimensional price movements
• Real-time Poisson ratio adjustments for market-specific elasticity modeling
• Gradient-based coloring system that visualizes stress intensity variations
• Advanced display modes with customizable visual layers for professional analysis
• Physics-based volatility normalization using Young’s modulus principles
🔧 Core Components
• Elasticity Engine: Calculates market elasticity using volatility-adjusted Young’s modulus
• Stress Tensor System: Computes normal stress values using Lamé parameters (λ and μ)
• Strain Measurement: Tracks price displacement relative to historical movement patterns
• Dynamic Bands: Statistical deviation bands that adapt to market elasticity changes
🔥 Key Features
• Four Display Modes: Choose between Histogram, Line, Both, or Advanced visualization
• Five Color Schemes: Modern, Classic, Neon, Ocean, and Fire themes with gradient support
• Background Stress Zones: Five distinct zones showing market stress levels visually
• Customizable Smoothing: Adjustable period for noise reduction without signal lag
• Extreme Value Detection: Automatic marking of critical stress points with visual alerts
• Advanced Mode Options: Glow effects, momentum ribbon, and extreme dots toggles
🎨 Visualization
• Stress Line: Primary indicator showing real-time market stress with gradient coloring
• Histogram Bars: Normalized stress values with dynamic opacity based on magnitude
• Reference Bands: Primary and secondary deviation bands for context
• Background Zones: Color-coded regions indicating stress intensity levels
• Signal Dots: Markers appearing at extreme stress points for easy identification
📖 Usage Guidelines
Display Settings
• Display Style
○ Default: Advanced
○ Options: Histogram, Line, Both, Advanced
○ Description: Controls visual presentation mode. Advanced offers the most comprehensive view with multiple layers
• Smoothing Period
○ Default: 3
○ Range: 1-50
○ Description: Moving average periods for noise reduction. Higher values create smoother signals but may introduce lag
Elasticity Parameters
• Displacement Length
○ Default: 14
○ Range: 1-100
○ Description: Lookback period for strain calculation. Shorter periods detect rapid stress changes
• Elasticity Length
○ Default: 30
○ Range: 1-200
○ Description: Period for volatility-based elasticity calculation. Longer periods provide more stable readings
• Poisson Ratio
○ Default: 0.3
○ Range: 0-0.5
○ Description: Theoretical elasticity ratio. 0.3 works well for most markets; adjust for specific asset classes
✅ Best Use Cases
• Identifying market tension before major breakouts
• Detecting compression zones during accumulation phases
• Confirming trend strength through stress persistence
• Timing reversals at extreme stress levels
• Multi-timeframe stress analysis for comprehensive market view
⚠️ Limitations
• Requires sufficient price history for accurate elasticity calculations
• May produce false signals during unprecedented market events
• Works best in liquid markets with consistent volume
• Not suitable as a standalone trading system
💡 What Makes This Unique
• Physics-Based Foundation: First indicator to properly implement elasticity theory
• Academic Rigor: Based on proven Navier-Cauchy equations from materials science
• Visual Innovation: Multiple display modes with professional-grade aesthetics
• Adaptive Technology: Self-adjusting parameters based on market conditions
🔬 How It Works
1. Strain Calculation:
• Measures price displacement over specified period
• Normalizes displacement relative to price level
2. Elasticity Determination:
• Calculates Young’s modulus using inverse volatility
• Updates Lamé parameters based on Poisson ratio
3. Stress Computation:
• Applies elasticity theory formula: σ = (λ + 2μ) × ε
• Scales result for visual clarity
• Applies smoothing to reduce noise
💡 Note: NCME represents a breakthrough in applying physics principles to market analysis. While based on proven scientific formulas, remember that markets are complex systems influenced by human psychology and external factors. Use NCME as part of a comprehensive trading strategy with proper risk management.
Volatility Layered Supertrend [NLR]We’ve all used Supertrend, but do you know where to actually enter a trade? Volatility Layered Supertrend (VLS) is here to solve that! This advanced trend-following indicator builds on the classic Supertrend by not only identifying trends and their strength but also guiding you to the best trade entry points. VLS divides the main long-term trend into “Strong” and “Weak” Zones, with a clear “Trade Entry Zone” to help you time your trades with precision. With layered trends, dynamic profit targets, and volatility-adaptive bands, VLS delivers actionable signals for any market.
Why I Created VLS Over a Plain Supertrend
I built VLS to address the gaps in traditional Supertrend usage and make trade entries clearer:
Single-Line Supertrend Issues: The default Supertrend sets stop-loss levels that are too wide, making it impractical for most traders to use effectively.
Unclear Entry Points: Standard Supertrend doesn’t tell you where to enter a trade, often leaving you guessing or entering too early or late.
Multi-Line Supertrend Enhancement: Many traders use short, medium, and long Supertrends, which is helpful but can lack focus. In VLS, I include Short, Medium, and Long trends (using multipliers 1 to 3), and add multipliers 4 and 5 to track extra long-term trends—helping to avoid fakeouts that sometimes occur with multiplier 3.
My Solution: I focused on the main long-term Supertrend and split it into “Weak Zone” and “Strength Zone” to show the trend’s reliability. I also defined a “Trade Entry Zone” (starting from the Mid Point, with the first layer’s background hidden for clarity) to guide you on where to enter trades. The zones include Short, Medium, and Long Trend layers for precise entries, exits, and stop-losses.
Practical Trading: This approach provides realistic stop-loss levels, clear entry points, and a “Profit Target” line that aligns with your risk tolerance, while filtering out false signals with longer-term trends.
Key Features
Layered Trend Zones: Short, Medium, Long, and Extra Long Trend layers (up to multipliers 4 and 5) for timing entries and exits.
Strong & Weak Zones: See when the trend is reliable (Strength Zone) or needs caution (Weak Zone).
Trade Entry Zone: A dedicated zone starting from the Mid Point (first layer’s background hidden) to show the best entry points.
Dynamic Profit Targets: A “Profit Target” line that adjusts with the trend for clear goals.
Volatility-Adaptive: Uses ATR to adapt to market conditions, ensuring reliable signals.
Color-Coded: Green for uptrends, red for downtrends—simple and clear.
How It Works
VLS enhances the main long-term Supertrend by dividing it into two zones:
Weak Zone: Indicates a less reliable trend—use tighter stop-losses or wait for the price to reach the Trade Entry Zone.
Strength Zone: Signals a strong trend—ideal for entries with wider stop-losses for bigger moves.
The “Trade Entry Zone” starts at the Mid Point (last layer’s background hidden for clarity), showing you the best area to enter trades. Each zone includes Short, Medium, Long, and Extra Long Trend sublevels (up to multipliers 4 and 5) for precise trade timing and to filter out fakeouts. The “Profit Target” updates dynamically based on trend direction and volatility, giving you a clear goal.
How to Use
Spot the Trend: Green bands = buy, red bands = sell.
Check Strength: Price in Strength Zone? Trend’s reliable—trade confidently. In Weak Zone? Use tighter stops or wait.
Enter Trades: Use the “Trade Entry Zone” (from the Mid Point upward) for the best entry points.
Use Sublevels: Short, Medium, Long, and Extra Long layers in each zone help fine-tune entries and exits.
Set Targets: Follow the Profit Target line for goals—it updates automatically.
Combine Tools: Pair with RSI, MACD, or support/resistance for added confirmation.
Settings
ATR Length: Adjust the ATR period (default 10) to change sensitivity.
Up/Down Colors: Customize colors—green for up, red for down, by default.
VIX Spike StrategyThis script implements a trading strategy based on the Volatility Index (VIX) and its standard deviation. It aims to enter a long position when the VIX exceeds a certain number of standard deviations above its moving average, which is a signal of a volatility spike. The position is then exited after a set number of periods.
VIX Symbol (vix_symbol): The input allows the user to specify the symbol for the VIX index (typically "CBOE:VIX").
Standard Deviation Length (stddev_length): The number of periods used to calculate the standard deviation of the VIX. This can be adjusted by the user.
Standard Deviation Multiplier (stddev_multiple): This multiplier is used to determine how many standard deviations above the moving average the VIX must exceed to trigger a long entry.
Exit Periods (exit_periods): The user specifies how many periods after entering the position the strategy will exit the trade.
Strategy Logic:
Data Loading: The script loads the VIX data, both for the current timeframe and as a rescaled version for calculation purposes.
Standard Deviation Calculation: It calculates both the moving average (SMA) and the standard deviation of the VIX over the specified period (stddev_length).
Entry Condition: A long position is entered when the VIX exceeds the moving average by a specified multiple of its standard deviation (calculated as vix_mean + stddev_multiple * vix_stddev).
Exit Condition: After the position is entered, it will be closed after the user-defined number of periods (exit_periods).
Visualization:
The VIX is plotted in blue.
The moving average of the VIX is plotted in orange.
The threshold for the VIX, which is the moving average plus the standard deviation multiplier, is plotted in red.
The background turns green when the entry condition is met, providing a visual cue.
Sources:
The VIX is often used as a measure of market volatility, with high values indicating increased uncertainty in the market.
Standard deviation is a statistical measure of the variability or dispersion of a set of data points. In financial markets, it is used to measure the volatility of asset prices.
References:
Bollerslev, T. (1986). "Generalized Autoregressive Conditional Heteroskedasticity." Journal of Econometrics.
Black, F., & Scholes, M. (1973). "The Pricing of Options and Corporate Liabilities." Journal of Political Economy.
Elder Impulse System + ATR BandsDisregard the above chart, I am not sure why it isn't showing the one I want, which is linked below:
This is as far as I can tell the closest representation to Dr. Alexander Elder's updated "Elder Impulse System" that has added ATR-volatility bands up to 3x deviations from price. I got the idea from watching this recent video (www.youtube.com) of Dr. Elder reviewing some recent trades and noticed he had updated his system from his original books. The Impulse System colour coding was inspired by AstralLoverFlow and LazyBear. ATR Bands are pre-programmed Keltner Channels with some modifications such as filing in the ATR Zones with user-selected colour bands and modifying the ATR value to better suit the volatility of the market being traded.
The script has several components, which I will detail below:
Exponential Moving Averages:
1) A 13-period EMA that is used as a staple in all of Dr. Elder's technical analysis. He uses this EMA as the basis for all of his indicators and why it is included here.
2) A 26-period EMA which can be used as a base-line of sorts to filter when to go long or when to go short. For instance, price over the 26-EMA, price is strong and the rally upwards is likely to continue, underneath it, price is weak and likely to continue downwards for a time.
Volatility Bands:
By definition these are nothing more than 3 separate Keltner Channels of a 13-period EMA each set to one additional multiplier from the moving average. This gives us a 1x, 2x, and 3x multiplier of average volatility from the 13-period EMA based on a 14-period Average True Range (ATR) reading. The ATR was chosen as it accommodates price gaps and also is the standard formula calculation in TradingView. The values of the bands cannot be adjusted but the colour coding of them can be.
Elder Impulse System:
These colour-coded bars show you the strength and direction of the current chart resolution, calculated by the slope of a 13-period EMA and the slope of a MACD histogram. These are used not as a buying or selling recommendation alone but as trend filters, as per Dr. Elder's own description of them.
Green Bars = The 13-period EMA is sloping positively and the MACD histogram is rising compared to previous bars. The trader should only consider buying/long opportunities when a green bar is most recent.
Red Bars = The 13-period EMA is sloping negatively and the MACD histogram is falling compared to previous bars. The trader should only consider selling/short opportunities when a red bar is most recent.
Blue Bars = The 13-period EMA and the MACD histogram are not aligned. One of the indicators is sloping opposite to the other indicator. These are known as indecision bars and are typically seen near the end of a previously established trend. The trader can choose to wait for either a green or red bar to shape their trading bias if they are more risk-averse while a counter-trend trader may decide to try opening a position against the currently-established trend.
How To Trade the System:
This system is unique in that it is so versatile and will fit the styles of many traders, be it trend following traders (generally the original Elder Impulse System design) or mean-reversion/counter-trend trading (the original Keltner Channel design). None of the examples below or in the chart above are financial advice and are just there for demonstration purposes only.
1) The most basic signal given would be the moving average cross up or down. A cross of the 13-EMA over the 26-EMA signals upward trend strength and the trader could look for buying opportunities. Conversely, the 13-EMA under the 26-EMA shows downward trend strength and the trader could look for selling opportunities.
2) Following the Elder Impulse system in conjunction with the EMAs. Look for long opportunities when a green bar is printed and price is over both of the 13- and 26-period EMAs. Look for short opportunities when a red bar is printed and price is below both of the 13- and 26-period EMAs. Keep in mind this does not necessarily need a moving average cross to be viable, a green or red bar over both EMAs is a valid signal in this system, usually. Examine price more closely for better entry signals when a blue bar is printed and price is either above or below both EMAs if you are a trend trader. This is how Dr. Elder originally intended the system to be used in conjunction with his famous Triple Screen Trading System. I am not going into detail here as it is a deep subject but I would suggest an interested trader to examine this Triple Screen System further as it is widely accepted as a strong strategy.
3) Mean Reversion and Counter-Trend Trading. Dr. Elder mentions that the zone between the two EMAs is called the Value Zone. A mean reversion trader could look for buying opportunities if price has generally been in an uptrend and falls back to value, conversely, they could look for shorting opportunities if price has generally been in a downtrend and rises back to value. These are your very basic pull backs found in trends that create your higher lows in an uptrend or your lower highs in a downtrend. A mean reversion/scalper trader may also look to use the upper and lower most ATR bands as an indication of price being overbought or oversold and could look to enter a counter-trend trade here once a blue indecision bar is printed and to ride that move back down to the Value Zone.
Taking Profits and Risk Management
This system again is very versatile and will fit a wide range of trading styles. It has built in take profit levels and risk management depending on your style of trading.
1a) In original Triple Screen Trading (and the original Elder Impulse system), a trader was to place a buy order one tick above a newly printed green bar with a stop loss one tick below the most recent 2-day low, and vice-versa for red bars on short selling. as long as other criteria were met, that I will not go into. It is all over YouTube and in his books and on Investopedia if you want more information. The general idea is to continue the trend in the direction if price is strong and you are bought into that move with a close stop, or if price falls back a little bit, you can get in at a better price. This would be a system typically better suited to a scalper.
1b) The updated risk management according to the above video is to place a stop loss at least 2ATR away from price. These bands already have calculated these values so a trader can place a stop one tick below the 2 or even 3ATR zones depending on their risk appetite. This is assuming you have already received a strong buy signal based on the system you follow. This would be a system typically better suited to a trend-trader.
2a) Taking profits if you are a trend trader has several possibilities. The first, as Dr. Elder suggests, is to place a price target 2ATR values away from your entry giving you approximately a 1:1 risk-reward ratio.
2b) The second possibility if the trade is successful is to ride the trend upwards until a blue bar is printed, suggesting indecision in the market. A modified version of this that could let a winning trade run longer is to wait for the price to close under the 13-EMA in fast markets, or close under the 26-EMA in slightly slower markets to maximize potential winnings.
2c) A scalper trader may wish to have a target at either the value zone if they are playing an extended buy/short back to the mean, or if they are being at the mean, to sell or cover when price extends back out to the 2x or 3x zone.
3) Trend traders can additionally use the ATR zones as a sort of safety guidelines for entering a trade. Anything within the 1ATR zone is typically a safer entry as the market is less volatile at this time. Entering when price has gone into the 2ATR zone is signaled as a strong momentum move and can signal a stronger move in the direction of the current closing bar. While not always the case, it is suggested by Dr. Elder to not enter trend trades at the 3ATR zone as this is where you will be likely looking for a counter-trend retracement back to value and a trader entering here in the direction of the trade has a higher chance of being stopped out or not getting in at the best possible price.
vol_bracketThis simple script shows an "N" standard deviation volatility bracket, anchored at the opening price of the current month, week, or quarter. This anchor is meant to coincide roughly with the expiration of options issued at the same interval. You can choose between a manually-entered IV or the hv30 volatility model.
Unlike my previous scripts, which all show the volatility bracket as a rolling figure, the anchor helps to visualize the volatility estimate in relation to price as it ranges over the (approximate) lifetime of a single, real contract.
Bollinger Band Calculation ToolIntroducing the Bollinger Band Calculation Tool
What are Bollinger Bands ?
According to Investopedia ....
"In the 1980s, John Bollinger, a long-time technician of the markets, developed the technique of using a moving average with two trading bands above and below it.
Unlike a percentage calculation from a normal moving average, Bollinger Bands® simply add and subtract a standard deviation calculation.
Standard deviation is a mathematical formula that measures volatility, showing how the stock price can vary from its true value.
By measuring price volatility, Bollinger Bands® adjust themselves to market conditions.
This is what makes them so handy for traders; they can find almost all of the price data needed between the two bands."
Classic interpretations of Bollinger bands from Fidelity Investments....
"When the bands tighten during a period of low volatility, it raises the likelihood of a sharp price move in either direction.
This may begin a trending move. Watch out for a false move in opposite direction which reverses before the proper trend begins.
When the bands separate by an unusual large amount, volatility increases and any existing trend may be ending.
Prices have a tendency to bounce within the bands' envelope, touching one band then moving to the other band.
You can use these swings to help identify potential profit targets.
For example, if a price bounces off the lower band and then crosses above the moving average, the upper band then becomes the profit target.
Price can exceed or hug a band envelope for prolonged periods during strong trends.
On divergence with a momentum oscillator, you may want to do additional research to determine if taking additional profits is appropriate for you.
A strong trend continuation can be expected when the price moves out of the bands.
However, if prices move immediately back inside the band, then the suggested strength is negated."
This indicator contains a standard set of Bollinger Bands with the addition of a Test Closing Price calculation function.
It displays a standard set of Bollinger Bands by default.
How do I use the Test Closing Price function ?
Enter a test price in the Test Closing Price box in the settings, and then click the "Use Test Price" button.
The indicator will then replace the current Bollinger upper, lower and basis-lines with plots showing the resultant lines if price were to close at the Test Closing Price.
An information panel will appear which displays the test closing price and the resulting Bollinger-upper, Bollinger-lower and basis-line prices.
Can display up to 10 decimal places and has adjustable label offset.
It will also plot lines outlining the resultant closed candle body for clarity.
To return to "Standard Bollingers" just click off the "Use Test Price" button.
Knowing exactly what the Bollinger bands and Basis will do if a particular closing price is met can be useful in a variety of ways to traders who use Bollinger Bands® in their trading.
It is possible to work out exactly what closing price is required to get above or below a Bollinger band which is normally difficult as Bollingers react to the change in price.
Users can also experiment with different Test Closing Prices [/i to see exactly what effect this would have on the Basis moving average and on the Bollinger bands themselves.
MOVE/VXTLT CorrelationMany know of the VIX for equity trading. Yet, many are unaware that there is the same kind of volatility measure for trading bonds, called the MOVE Index.
"The Merrill Lynch Option Volatility Estimate (MOVE) Index is a yield curve weighted index of the normalized implied volatility on 1-month Treasury options which are weighted on the 2, 5, 10, and 30 year contracts."
With this script one can see the the correlation and divergences between bonds and its volatility measure to make educated decisions in trading or hedging.
The idea of this script comes from NicTheMajestic.
Multi-Exchange Volume (30 Tickers) by kurtsmock + BV + rVolauthor: kurtsmock
Fully Customizable ticker set. Up to 30 Tickers. Bitcoin set as default.
-- IMPORTANT NOTE: --
30 Exchanges are a lot. It can take a while to load. You can fully customize this indicator to your liking. Here's how:
1. Load indicator
2. Open Settings
3. Uncheck the switch box for exchanges you want unincluded
4. At the bottom of the settings menu click "Defaults" and hit "Save as Default"
5. To turn them all back on, hit "Reset Settings" in that same "Defaults" menu and click "Save as Default" again.
Also, you don't have to use this with Bitcoin. This works with any asset, just change the ticker in the settings.
There's a lot going on with this indicator so the following is descriptions and instructions to help you better understand what's going on here. Thanks!
Goal:
- To provide a mechanism for assets on multiple exchanges to have their volume evaluated together
Edge:
- Having better and more complete volume information
Notes:
- The Default Exchanges for this indicator are highest volume bitcoin exchanges, but may contain "fake volume"
- Indicator is set for Bitcoin by default. However, you can change the tickers to reflect any asset you want
////// rVol //////
Goal:
- To understand how much volume is being executed relative to the same candle on previous days/periods
Edge:
- Higher rVol implies higher volatility and market interest.
- High rVol = higher than average volume . Markets move on volume so higher than average volume indicates increased market activity/volatility
- rVol is an indirect measure of active or anticipated volatility
Definitions:
- rVol: The volume of a period compared to the Average Volume of that same period in past sessions
- Important to note it does NOT add up the last 10 (default) candles, but rather the last 10 candles at session intervals.
- Example:
-- On a Tuesday, 1h chart it will add up the last ten Tuesday, 9:00 am candles, not including the current, active candle.
-- It then averages those lookback candles.
-- It then plots the percentage relationship between the most recent candle and the average of the lookback candles
-- Avg Vol of Lookback candles = 5000,
-- Volume of most recent candle = 4000: Output = rVol = 80:
-- Volume of most recent candle was 80% of the average volume in the 9 am time period of the last ten Tuesdays in the 9 am, 1h period
Notes:
- rVol does not add current candle volume into lookback sum. So, you set lookback to be: (not including the current day)
- rVol is on a switch. So, if you want to see rVol instead of volume, hit the switch in the settings
- If you want to see both, load 2 instances of the indicator.
////// Better-er Volume //////
Goal:
To Identify:
- When a candle closes at the highest volume * range relative to the lookback period and close > open
- When a candle closes at the highest volume * range relative to the lookback period and close < open
- When a candle closes at the highest volume / price relative to the lookback period
Edge:
- Identifies beginnings of price expansion, climax of price expansion, breakouts, pivots, and take profit points on the volume chart
Notes:
- Based generally on Barry Taylor's "Better Volume" indicator and ideas from Pascal Willain's book "Value in Time."
- Better-er Volume rules are applied to both Total Volume or rVol.
-- When rVol is displayed Better-er Volume is applied to rVol
-- When Total Volume is displayed Better-er Volume is applied to Total Volume
// Plot Key: //
Green Triangle Up = Often marks the beginning and/or end of price expansion to the upside
Red Triangle Up = Often marks the beginning and/or end of price expansion to the downside
Yellow Square = High Volume but Tight Range. Implies a Battle of Bulls and Bears. High Liquidity area. Provided Liquidity is not enough to move price. Thick Limit Order Book.
Purple Triangle Up or Down = Implies high market participation. Typically at the end of expansion when very significant s/r is hit
category: volume Volatility
tags: Volume rVol relativevolume Bitcoin cryptocurrency bettervolume
Many More Volume Indicators Coming Out Soon!
HV ID/ND4 BreakoutThis indicator is based on Linda Raschke's ID/ND4 Historical Volatility Breakout strategy. It finds days where the high and low are within the previous day high and lows (Inside days), that have also, the narrowest trading range within the last 4 days (it basically checks if the current day has the narrowest range comparing it with the previous 3 days) when the short term historical volatility (6 period default) is relatively low compared to the longer term historical volatility (100 period default) (The condition is that the 6/100 Historical volatility is below 50% of its annual range).
More information about how to trade this strategy is described in the book but basically, you would want to place a resting buy and sell stops at the high and low of the day highlighted and enter if you get filled the next day.
QMA/SMA DifferenceIntroduction
The quadratic moving average (QMA) or quadratic weighted moving average (QWMA) is a type of moving average who is closer to the price when price is up trending. This moving average is defined as the square root of the moving average of the squared price. The QMA-SMA difference use this moving average to provide a new volatility indicator who aim to be reactive and filter noisy volatility in order to only provide essential information.
QMA - SMA
This indicator is defined as the difference between a quadratic moving average and a simple moving average of same period. Since the QMA emphasize up movements and tend to be away from down movements she is always greater than the simple moving average, so a simple difference between those moving average provide our volatility indicator. Below is a comparison with a standard deviation and the indicator of both period 100.
Since its a difference between two moving average it can be interesting to use a simple moving as source for the standard deviation to provide another comparison
The standard deviation is smoother but still contain more information as well as having less reactivity.
Conclusion
I have a presented a new volatility indicator based on the quadratic moving average and compared it with a classic standard deviation. It is possible to change the power order of the QMA in order to provide different results, in order to do so you must also change the root, this is done in pine with : pow(sma(pow(close,w),length),1/w) where w is the power order, notice that an high power order can provide non attributed values.
BKSqueezeThis is a price volatility compression and expansion indicator that uses the ratio of the Bollinger Band and Keltner Ratio.
Red segments indicate extreme price volatility compression that can be ideal entry points for stock/futures/forex and/or options positions.
Aqua segments indicate price volatility is expanding.
Blue segments indicate price volatility is compressing - can be used as an exit point or partial scale out point.
Note that the indicator doesn't indicate direction. One suggestion is to use the DMI indicator for this purpose - really depends on how early you enter the trade.
Suggest using a time period of 15 bars for volatile stocks, such as TSLA for example, otherwise a period of 20 bars suits most stocks/futures/forex symbols.
Rolling Log Returns [BackQuant]Rolling Log Returns
The Rolling Log Returns indicator is a versatile tool designed to help traders, quants, and data-driven analysts evaluate the dynamics of price changes using logarithmic return analysis. Widely adopted in quantitative finance, log returns offer several mathematical and statistical advantages over simple returns, making them ideal for backtesting, portfolio optimization, volatility modeling, and risk management.
What Are Log Returns?
In quantitative finance, logarithmic returns are defined as:
ln(Pₜ / Pₜ₋₁)
or for rolling periods:
ln(Pₜ / Pₜ₋ₙ)
where P represents price and n is the rolling lookback window.
Log returns are preferred because:
They are time additive : returns over multiple periods can be summed.
They allow for easier statistical modeling , especially when assuming normally distributed returns.
They behave symmetrically for gains and losses, unlike arithmetic returns.
They normalize percentage changes, making cross-asset or cross-timeframe comparisons more consistent.
Indicator Overview
The Rolling Log Returns indicator computes log returns either on a standard (1-period) basis or using a rolling lookback period , allowing users to adapt it to short-term trading or long-term trend analysis.
It also supports a comparison series , enabling traders to compare the return structure of the main charted asset to another instrument (e.g., SPY, BTC, etc.).
Core Features
✅ Return Modes :
Normal Log Returns : Measures ln(price / price ), ideal for day-to-day return analysis.
Rolling Log Returns : Measures ln(price / price ), highlighting price drift over longer horizons.
✅ Comparison Support :
Compare log returns of the primary instrument to another symbol (like an index or ETF).
Useful for relative performance and market regime analysis .
✅ Moving Averages of Returns :
Smooth noisy return series with customizable MA types: SMA, EMA, WMA, RMA, and Linear Regression.
Applicable to both primary and comparison series.
✅ Conditional Coloring :
Returns > 0 are colored green ; returns < 0 are red .
Comparison series gets its own unique color scheme.
✅ Extreme Return Detection :
Highlight unusually large price moves using upper/lower thresholds.
Visually flags abnormal volatility events such as earnings surprises or macroeconomic shocks.
Quantitative Use Cases
🔍 Return Distribution Analysis :
Gain insight into the statistical properties of asset returns (e.g., skewness, kurtosis, tail behavior).
📉 Risk Management :
Use historical return outliers to define drawdown expectations, stress tests, or VaR simulations.
🔁 Strategy Backtesting :
Apply rolling log returns to momentum or mean-reversion models where compounding and consistent scaling matter.
📊 Market Regime Detection :
Identify periods of consistent overperformance/underperformance relative to a benchmark asset.
📈 Signal Engineering :
Incorporate return deltas, moving average crossover of returns, or threshold-based triggers into machine learning pipelines or rule-based systems.
Recommended Settings
Use Normal mode for high-frequency trading signals.
Use Rolling mode for swing or trend-following strategies.
Compare vs. a broad market index (e.g., SPY or QQQ ) to extract relative strength insights.
Set upper and lower thresholds around ±5% for spotting major volatility days.
Conclusion
The Rolling Log Returns indicator transforms raw price action into a statistically sound return series—equipping traders with a professional-grade lens into market behavior. Whether you're conducting exploratory data analysis, building factor models, or visually scanning for outliers, this indicator integrates seamlessly into a modern quant's toolbox.
ATRWhat the Indicator Shows:
A compact table with four cells is displayed in the bottom-left corner of the chart:
| ATR | % | Level | Lvl+ATR |
Explanation of the Columns:
ATR — The averaged daily range (volatility) calculated with filtering of abnormal bars (extremely large or small daily candles are ignored).
% — The percentage of the daily ATR that the price has already covered today (the difference between the daily Open and Close relative to ATR).
Level — A custom user-defined level set through the indicator settings.
Lvl+ATR — The sum of the daily ATR and the user-defined level. This can be used, for example, as a target or stop-loss reference.
Color Highlighting of the "%" Cell:
The background color of the "%" ATR cell changes depending on the value:
✅ If the value is less than 10% — the cell is green (market is calm, small movement).
➖ If the value is between 10% and 50% — no highlighting (average movement, no signal).
🟡 If the value is between 50% and 70% — the cell is yellow (movement is increasing, be alert).
🔴 If the value is above 70% — the cell is red (the market is actively moving, high volatility).
Key Features:
✔ All ATR calculations and percentage progress are performed strictly based on daily data, regardless of the chart's current timeframe.
✔ The indicator is ideal for intraday traders who want to monitor daily volatility levels.
✔ The table always displays up-to-date information for quick decision-making.
✔ Filtering of abnormal bars makes ATR more stable and objective.
What is Adaptive ATR in this Indicator:
Instead of the classic ATR, which simply averages the true range, this indicator uses a custom algorithm:
✅ It analyzes daily bars over the past 100 days.
✅ Calculates the range High - Low for each bar.
✅ If the bar's range deviates too much from the average (more than 1.8 times higher or lower), the bar is considered abnormal and ignored.
✅ Only "normal" bars are included in the calculation.
✅ The average range of these normal bars is the adaptive ATR.
Detailed Algorithm of the getAdaptiveATR() Function:
The function takes the number of bars to include in the calculation (for example, 5):
The average of the last 5 normal bars is calculated.
pinescript
Копировать
Редактировать
adaptiveATR = getAdaptiveATR(5)
Step-by-Step Process:
An empty array ranges is created to store the ranges.
Daily bars with indices from 1 to 100 are iterated over.
For each bar:
🔹 The daily High and Low with the required offset are loaded via request.security().
🔹 The range High - Low is calculated.
🔹 The temporary average range of the current array is calculated.
🔹 The bar is checked for abnormality (too large or too small).
🔹 If the bar is normal or it's the first bar — its range is added to the array.
Once the array accumulates the required number of bars (count), their average is calculated — this is the adaptive ATR.
If it's not possible to accumulate the required number of bars — na is returned.
Что показывает индикатор:
На графике внизу слева отображается компактная таблица из четырех ячеек:
ATR % Уровень Ур+ATR
Пояснения к столбцам:
ATR — усреднённый дневной диапазон (волатильность), рассчитанный с фильтрацией аномальных баров (слишком большие или маленькие дневные свечи игнорируются).
% — процент дневного ATR, который уже "прошла" цена на текущий день (разница между открытием и закрытием относительно ATR).
Уровень — пользовательский уровень, который задаётся вручную через настройки индикатора.
Ур+ATR — сумма уровня и дневного ATR. Может использоваться, например, как ориентир для целей или стопов.
Цветовая подсветка ячейки "%":
Цвет фона ячейки с процентом ATR меняется в зависимости от значения:
✅ Если значение меньше 10% — ячейка зелёная (рынок пока спокоен, маленькое движение).
➖ Если значение от 10% до 50% — фон не подсвечивается (среднее движение, нет сигнала).
🟡 Если значение от 50% до 70% — ячейка жёлтая (движение усиливается, повышенное внимание).
🔴 Если значение выше 70% — ячейка красная (рынок активно движется, высокая волатильность).
Особенности работы:
✔ Все расчёты ATR и процентного прохождения производятся исключительно по дневным данным, независимо от текущего таймфрейма графика.
✔ Индикатор подходит для трейдеров, которые торгуют внутри дня, но хотят ориентироваться на дневные уровни волатильности.
✔ В таблице всегда отображается актуальная информация для принятия быстрых торговых решений.
✔ Фильтрация аномальных баров делает ATR более устойчивым и объективным.
Что такое адаптивный ATR в этом индикаторе
Вместо классического ATR, который просто усредняет истинный диапазон, здесь используется собственный алгоритм:
✅ Он берет дневные бары за последние 100 дней.
✅ Для каждого из них рассчитывает диапазон High - Low.
✅ Если диапазон бара слишком сильно отличается от среднего (более чем в 1.8 раза больше или меньше), бар считается аномальным и игнорируется.
✅ Только нормальные бары попадают в расчёт.
✅ В итоге считается среднее из диапазонов этих нормальных баров — это и есть адаптивный ATR.
Подробный алгоритм функции getAdaptiveATR()
Функция принимает количество баров для расчёта (например, 5):
Считается 5 последних нормальных баров
pinescript
Копировать
Редактировать
adaptiveATR = getAdaptiveATR(5)
Пошагово:
Создаётся пустой массив ranges для хранения диапазонов.
Перебираются дневные бары с индексами от 1 до 100.
Для каждого бара:
🔹 Через request.security() подгружаются дневные High и Low с нужным смещением.
🔹 Считается диапазон High - Low.
🔹 Считается временное среднее диапазона по текущему массиву.
🔹 Проверяется, не является ли бар аномальным (слишком большой или маленький).
🔹 Если бар нормальный или это самый первый бар — его диапазон добавляется в массив.
Как только массив набирает заданное количество баров (count), берётся их среднее значение — это и есть адаптивный ATR.
Если не удалось набрать нужное количество баров — возвращается na.
X-Day Capital Efficiency ScoreThis indicator helps identify the Most Profitable Movers for Your fixed Capital (ie, which assets offer the best average intraday profit potential for a fixed capital).
Unlike traditional volatility indicators (like ATR or % change), this script calculates how much real dollar profit you could have made each day over a custom lookback period — assuming you deployed your full capital into that ticker daily.
How it works:
Calculates the daily intraday range (high − low)
Filters for clean candles (where body > 60% of the candle range)
Assumes you invested the full amount of capital ($100K set as default) on each valid day
Computes an average daily profit score based on price action over the selected period (default set to 20 days)
Plots the score in dollars — higher = more efficient use of capital
Why It’s Useful:
Compare tickers based on real dollar return potential — not just % volatility
Spot low-priced, high-volatility stocks that are better suited for intraday or momentum trading
Inputs:
Capital ($): Amount you're hypothetically deploying (e.g., 100,000)
Look Back Period: Number of past days to average over (e.g., 20)
Linear % ST | QuantEdgeB🚀 Introducing Linear Percentile SuperTrend (Linear % ST) by QuantEdgeB
🛠️ Overview
Linear % SuperTrend (Linear % ST) by QuantEdgeB is a hybrid trend-following indicator that combines Linear Regression, Percentile Filters, and Volatility-Based SuperTrend Logic into one dynamic tool. This system is designed to identify trend shifts early while filtering out noise during choppy market conditions.
By utilizing percentile-based median smoothing and customized ATR multipliers, this tool captures both breakout momentum and pullback opportunities with precision.
✨ Key Features
🔹 Percentile-Based Median Filtering
Removes outliers and normalizes price movement for cleaner trend detection using the 50th percentile (median) of recent price action.
🔹 Linear Regression Smoothing
A smoothed baseline is computed with Linear Regression to detect the underlying trend while minimizing lag.
🔹 SuperTrend Structure with Adaptive Bands
The indicator implements an enhanced SuperTrend engine with custom ATR bands that adapt to trend direction. Bands tighten or loosen based on volatility and trend strength.
🔹 Dynamic Long/Short Conditions
Long and short signals are derived from the relationship between price and the SuperTrend threshold zones, clearly showing trend direction with optional "Long"/"Short" labels on the chart.
🔹 Multiple Visual Themes
Select from 6 built-in color palettes including Strategy, Solar, Warm, Cool, Classic, and Magic to match your personal style or strategy layout.
📊 How It Works
1️⃣ Percentile Filtering
The source price (default: close) is filtered using a nearest-rank 50th percentile over a custom lookback. This normalizes data to reflect the central tendency and removes noisy extremes.
2️⃣ Linear Regression Trend Base
A Linear Regression Moving Average (LSMA) is applied to the filtered median, forming the core trend line. This dynamic trendline provides a low-lag yet smooth view of market direction.
3️⃣ SuperTrend Engine
ATR is applied with custom multipliers (different for long and short) to create dynamic bands. The bands react to price movement and only shift direction after confirmation, preventing false flips.
4️⃣ Trend Signal Logic
• When price stays above the dynamic lower band → Bullish trend
• When price breaks below the upper band → Bearish trend
• Trend direction remains stable until violated by price.
⚙️ Custom Settings
• Percentile Length → Lookback for percentile smoothing (default: 35)
• LSMA Length → Determines the base trend via linear regression (default: 24)
• ATR Length → ATR period used in dynamic bands (default: 14)
• Long Multiplier → ATR multiplier for bullish thresholds (default: 0.8)
• Short Multiplier → ATR multiplier for bearish thresholds (default: 1.9)
✅ How to Use
1️⃣ Trend-Following Strategy
✔️ Go Long when price breaks above the lower ATR band, initiating an upward trend
✔️ Go Short when price falls below the upper ATR band, confirming bearish conditions
✔️ Remain in trend direction until the SuperTrend flips
2️⃣ Visual Confirmation
✔️ Use bar coloring and the dynamic bands to stay aligned with trend direction
✔️ Optional Long/Short labels highlight key signal flips
👥 Who Should Use Linear % ST?
✅ Swing & Position Traders → To ride trends confidently
✅ Trend Followers → As a primary directional filter
✅ Breakout Traders → For clean signal generation post-range break
✅ Quant/Systematic Traders → Integrate clean trend logic into algorithmic setups
📌 Conclusion
Linear % ST by QuantEdgeB blends percentile smoothing with linear regression and volatility bands to deliver a powerful, adaptive trend-following engine. Whether you're a discretionary trader seeking cleaner entries or a systems-based trader building logic for automation, Linear % ST offers clarity, adaptability, and precision in trend detection.
🔹 Key Takeaways:
1️⃣ Percentile + Regression = Noise-Reduced Core Trend
2️⃣ ATR-Based SuperTrend = Reliable Breakout Confirmation
3️⃣ Flexible Parameters + Color Modes = Custom Fit for Any Strategy
📈 Use it to spot emerging trends, filter false signals, and stay confidently aligned with market momentum.
📌 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.
[blackcat] L1 Reverse Choppiness IndexThe Choppiness Index is a technical indicator that is used to measure market volatility and trendiness. It is designed to help traders identify when the market is trending and when it is choppy, meaning that it is moving sideways with no clear direction. The Choppiness Index was first introduced by Australian commodity trader E.W. Dreiss in the late 1990s, and it has since become a popular tool among traders.
Today, I created a reverse version of choppiness index indicator, which uses upward direction as indicating strong trend rather than a traditional downward direction. Also, it max values are exceeding 100 compared to a traditional one. I use red color to indicate a strong trend, while yellow as sideways. Fuchsia zone are also incorporated as an indicator of sideways. One thing that you need to know: different time frames may need optimize parameters of this indicator. Finally, I'd be happy to explain more about this piece of code.
The code begins by defining two input variables: `len` and `atrLen`. `len` sets the length of the lookback period for the highest high and lowest low, while `atrLen` sets the length of the lookback period for the ATR calculation.
The `atr()` function is then used to calculate the ATR, which is a measure of volatility based on the range of price movement over a certain period of time. The `highest()` and `lowest()` functions are used to calculate the highest high and lowest low over the lookback period specified by `len`.
The `range`, `up`, and `down` variables are then calculated based on the highest high, lowest low, and closing price. The `sum()` function is used to calculate the sum of ranges over the lookback period.
Finally, the Choppiness Index is calculated using the ATR and the sum of ranges over the lookback period. The `log10()` function is used to take the logarithm of the sum divided by the lookback period, and the result is multiplied by 100 to get a percentage. The Choppiness Index is then plotted on the chart using the `plot()` function.
This code can be used directly in TradingView to plot the Choppiness Index on a chart. It can also be incorporated into custom trading strategies to help traders make more informed decisions based on market volatility and trendiness.
I hope this explanation helps! Let me know if you have any further questions.
VIX Monitor [Zero54]NSE:BANKNIFTY1!
This is a simple but invaluable tool for both day traders and positional traders. VIX is about market expectations of volatility
The VIX is a very good and sound measure of risk in the markets. It gives these stock traders who are in intraday trading and short term traders an idea of whether the volatility is going up or going down in the market. They can calibrate their strategy accordingly. When the volatility is likely to shoot up sharply, the intraday traders run the risk of stop losses getting triggered quickly. Hence they can either reduce their leverage or they can widen their stop losses accordingly.
Also if you notice VIX is a very good and reliable gauge of index movement. If you plot the VIX and the Nifty movement you will see a clear negative correlation in the charts itself. Markets typically tend to peak out when the VIX is bottoming out and the markets tend to bottom out when the VIX is peaking out. This is a useful input for index trades.
You can use this simple indicator to monitor VIX real time. You can use it for short time frame intraday and also multi-hour, multi-day charts. You can also plot a moving average to gauge the VIX trend.
Also is the ability to monitor, Nifty and BankNifty the same way you are able to monitor the VIX (as explained above). The overall market moves in correlation with these main Indexes. So if you are trading a specific counter, you can also keep an eye on the index to get an idea where the counter may be going next.
The source code is open, please feel to modify or re-use as you feel it’s necessary. Any changes, improvements, bugs, please let me know.
Please like/boost this indicator and also add your comments, if you find it useful.
HPK Crash IndicatorFrom Hari P. Krishnan's book, The Second Leg Down: Strategies for Profiting after a Market Sell-Off :
"We start by specifying the year on year (YoY) change in the index. Next, we calculate the 5 year trailing Z score of the YoY returns. We also calculate the 5 year trailing Z score of 1 month historical volatility for the index, using daily returns. Our crisis warning indicator flashes if both Z scores are above 2. In other words, recent price increases and current volatility need to be at least 2 standard deviations above normal.
It can be seen that this basic implementation is reasonably effective, accepting that the effective sample set is small. A false signal is given in mid-2006, but the signal is quickly washed away. The remaining signals occur fairly close to the point of collapse. The idea that elevated volatility is predictive of danger is not new and underpins many asset allocation schemes. However, Sornette deserves credit for moving away from a largely valuation-based approach to predicting crises to one that relies upon price action itself."
