Cerca negli script per "Volatility"
GARCH Volatility Estimation - The Quant ScienceThe GARCH (Generalized Autoregressive Conditional Heteroskedasticity) model is a statistical model used to forecast the volatility of a financial asset. This model takes into account the fluctuations in volatility over time, recognizing that volatility can vary in a heteroskedastic (i.e., non-constant variance) manner and can be influenced by past events.
The general formula of the GARCH model is:
σ²(t) = ω + α * ε²(t-1) + β * σ²(t-1)
where:
σ²(t) is the conditional variance at time t (i.e., squared volatility)
ω is the constant term (intercept) representing the baseline level of volatility
α is the coefficient representing the impact of the squared lagged error term on the conditional variance
ε²(t-1) is the squared lagged error term at the previous time period
β is the coefficient representing the impact of the lagged conditional variance on the current conditional variance
In the context of financial forecasting, the GARCH model is used to estimate the future volatility of the asset.
HOW TO USE
This quantitative indicator is capable of estimating the probable future movements of volatility. When the GARCH increases in value, it means that the volatility of the asset will likely increase as well, and vice versa. The indicator displays the relationship of the GARCH (bright red) with the trend of historical volatility (dark red).
USER INTERFACE
Alpha: select the starting value of Alpha (default value is 0.10).
Beta: select the starting value of Beta (default value is 0.80).
Lenght: select the period for calculating values within the model such as EMA (Exponential Moving Average) and Historical Volatility (default set to 20).
Forecasting: select the forecasting period, the number of bars you want to visualize data ahead (default set to 30).
Design: customize the indicator with your preferred color and choose from different types of charts, managing the design settings.
SOLANA Performance & Volatility Analysis BB%Overview:
The script provides an in-depth analysis of Solana's performance and volatility. It showcases Solana's price, its inverse relationship, its own volatility, and even juxtaposes it against Bitcoin's 24-hour historical volatility. All of these are presented using the Bollinger Bands Percentage (BB%) methodology to normalise the price and volatility values between 0 and 1.
Key Components:
Inputs:
SOLANA PRICE (SOLUSD): The price of Solana.
SOLANA INVERSE (SOLUSDT.3S): The inverse of Solana's price.
SOLANA VOLATILITY (SOLUSDSHORTS): Volatility for Solana.
BITCOIN 24 HOUR HISTORICAL VOLATILITY (BVOL24H): Bitcoin's volatility over the past 24 hours.
BB Calculations:
The script uses the Bollinger Bands methodology to calculate the mean (SMA) and the standard deviation of the prices and volatilities over a certain period (default is 20 periods). The calculated upper and lower bands help in normalising the values to the range of 0 to 1.
Normalised Metrics Plotting:
For better visualisation and comparative analysis, the normalised values for:
Solana Price
Solana Inverse
Solana Volatility
Bitcoin 24hr Volatility
are plotted with steplines.
Band Plotting:
Bands are plotted at 20%, 40%, 60%, and 80% levels to serve as reference points. The area between the 40% and 60% bands is shaded to highlight the median region.
Colour Coding:
Different colours are used for easy differentiation:
Solana Price: Blue
Solana Inverse: Red
Solana Volatility: Green
Bitcoin 24hr Volatility: White
Licence & Creator:
The script adheres to the Mozilla Public Licence 2.0 and is credited to the author, "Volatility_Vibes".
Works well with Breaks and Retests with Volatility Stop
VIX Volatility Trend Analysis With Signals - Stocks OnlyVIX VOLATILITY TREND ANALYSIS CLOUD WITH BULLISH & BEARISH SIGNALS - STOCKS ONLY
This indicator is a visual aid that shows you the bullish or bearish trend of VIX market volatility so you can see the VIX trend without switching charts. When volatility goes up, most stocks go down and vice versa. When the cloud turns green, it is a bullish sign. When the cloud turns red, it is a bearish sign.
This indicator is meant for stocks with a lot of price action and volatility, so for best results, use it on charts that move similar to the S&P 500 or other similar charts.
This indicator uses real time data from the stock market overall, so it should only be used on stocks and will only give a few signals during after hours. It does work ok for crypto, but will not give signals when the US stock market is closed.
**HOW TO USE**
When the VIX Volatility Index trend changes direction, it will give a green or red line on the chart depending on which way the VIX is now trending. The cloud will also change color depending on which way the VIX is trending. Use this to determine overall market volatility and place trades in the direction that the indicator is showing. Do not use this by itself as sometimes markets won’t react perfectly to the overall market volatility. It should only be used as a secondary confirmation in your trading/trend analysis.
For more signals with earlier entries, go into settings and reduce the number. 10-100 is best for scalping. For less signals with later entries, change the number to a higher value. Use 100-500 for swing trades. Can go higher for long swing trades. Our favorite settings are 20, 60, 100, 500 and 1000.
***MARKETS***
This indicator should only be used on the US stock markets as signals are given based on the VIX volatility index which measures volatility of the US Stock Markets.
***TIMEFRAMES***
This indicator works on all time frames, but after hours will not change much at all due to the markets being closed.
**INVERSE CHARTS**
If you are using this on an inverse ETF and the signals are showing backwards, please comment with what chart it is and I will configure the indicator to give the correct signals. I have included over 50 inverse ETFs into the code to show the correct signals on inverse charts, but I'm sure there are some that I have missed so feel free to let me know and I will update the script with the requested tickers.
***TIPS***
Try using numerous indicators of ours on your chart so you can instantly see the bullish or bearish trend of multiple indicators in real time without having to analyze the data. Some of our favorites are our Auto Fibonacci, Directional Movement Index, Volume Profile with buy & sell pressure, Auto Support And Resistance, Vix Scalper and Money Flow Index in combination with this Vix Trend Analysis. They all have real time Bullish and Bearish labels as well so you can immediately understand each indicator's trend.
Rainbow EMA Areas with Volatility HighlightThe indicator provides traders with an enhanced visual tool to observe price movements, trend strength, and market volatility on their charts. It combines multiple EMAs (Exponential Moving Averages) with color-coded areas to indicate the market’s directional bias and a high-volatility highlight for detecting times of increased market activity.
Explanation of Key Components
Multiple EMAs (Exponential Moving Averages):
Six different EMAs are calculated for various periods (15, 45, 100, 150, 200, 300).
Each EMA period represents a different timeframe, from short-term to long-term trends, providing a well-rounded view of price behavior across different market cycles.
The EMAs are color-coded for easy differentiation:
Green shades indicate bullish trends when prices are above the EMAs.
Red shades indicate bearish trends when prices are below the EMAs.
The space between each EMA is filled with a gradient color, creating a "wave" effect that helps identify the market’s overall direction.
ATR-Based Volatility Detection:
The ATR (Average True Range), a measure of market volatility, is used to assess how much the price is fluctuating. When volatility is high, price movements are typically more significant, indicating potential trading opportunities or times to exercise caution.
The indicator calculates ATR and uses a customizable multiplier to set a high-volatility threshold.
When the ATR exceeds this threshold, it signals that the market is experiencing high volatility.
Visual High Volatility Highlight:
A yellow background appears on the chart during periods of high volatility, giving a subtle but clear visual indication that the market is active.
This highlight helps traders spot potential breakout areas or increased activity zones without obstructing the EMA areas.
Volatility Signal Markers:
Small, red triangular markers are plotted above price bars when high volatility is detected, marking these areas for additional emphasis.
These signals serve as alerts to help traders quickly recognize high volatility moments where price moves may be stronger.
How to Use This Indicator
Identify Trends Using EMA Areas:
Bullish Trend: When the price is above most or all EMAs, and the EMA areas are colored in shades of green, it indicates a strong bullish trend. Traders might look for buy opportunities in this scenario.
Bearish Trend: When the price is below most or all EMAs, and the EMA areas are colored in shades of red, it signals a bearish trend. This condition can suggest potential sell opportunities.
Consolidation or Neutral Trend: If the price is moving within the EMA bands without a clear green or red dominance, the market may be in a consolidation phase. This period often precedes a breakout in either direction.
Volatility-Based Entries and Exits:
High Volatility Areas: The yellow background and red triangular markers signal high-volatility areas. This information can be valuable for identifying potential breakout points or strong moves.
Trading in High Volatility: During high-volatility phases, the market may experience rapid price changes, which can be ideal for breakout trades. However, high volatility also involves higher risk, so traders may adjust their strategies accordingly (e.g., setting wider stops or adjusting position sizes).
Trading in Low Volatility: When the yellow background and markers are absent, volatility is lower, indicating a calmer market. In these times, traders may choose to look for range-bound trading opportunities or wait for the next trend to develop.
Combining with Other Indicators:
This indicator works well in combination with momentum or oscillating indicators like RSI or MACD, providing a well-rounded view of the market.
For example, if the indicator shows a bullish EMA area with high volatility, and an RSI is trending up, it could be a stronger buy signal. Conversely, if the indicator shows a bearish EMA area with high volatility and RSI is trending down, this could be a stronger sell signal.
Practical Trading Examples
Bullish Trend in High Volatility:
Price is above the EMAs, showing green EMA areas, and the high volatility background is active.
This indicates a strong bullish trend with significant price movement potential.
A trader could look for breakout or continuation entries in the direction of the trend.
Bearish Reversal Signal:
Price crosses below the EMAs, showing red EMA areas, while high volatility is also detected.
This suggests that the market may be reversing to a bearish trend with increased price movement.
Traders could consider taking short positions or setting stops on existing long trades.
This indicator is designed to provide a rich visual experience, making it easy to spot trends, consolidations, and volatility zones at a glance. It is best used by traders who benefit from visual cues and who seek a quick understanding of both trend direction and market activity. Let me know if you'd like further customization or additional functionalities!
Z-Score Based Momentum Zones with Advanced Volatility ChannelsThe indicator "Z-Score Based Momentum Zones with Advanced Volatility Channels" combines various technical analysis components, including volatility, price changes, and volume correction, to calculate Z-Scores and determine momentum zones and provide a visual representation of price movements and volatility based on multi timeframe highest high and lowest low values.
Note: THIS IS A IMPROVEMNT OF "Multi Time Frame Composite Bands" INDICATOR OF MINE WITH MORE EMPHASIS ON MOMENTUM ZONES CALULATED BASED ON Z-SCORES
Input Options
look_back_length: This input specifies the look-back period for calculating intraday volatility. correction It is set to a default value of 5.
lookback_period: This input sets the look-back period for calculating relative price change. The default value is 5.
zscore_period: This input determines the look-back period for calculating the Z-Score. The default value is 500.
avgZscore_length: This input defines the length of the momentum block used in calculations, with a default value of 14.
include_vc: This is a boolean input that, if set to true, enables volume correction in the calculations. By default, it is set to false.
1. Volatility Bands (Composite High and Low):
Composite High and Low: These are calculated by combining different moving averages of the high prices (high) and low prices (low). Specifically:
a_high and a_low are calculated as the average of the highest (ta.highest) and lowest (ta.lowest) high and low prices over various look-back periods (5, 8, 13, 21, 34) to capture short and long-term trends.
b_high and b_low are calculated as the simple moving average (SMA) of the high and low prices over different look-back periods (5, 8, 13) to smooth out the trends.
high_c and low_c are obtained by averaging a_high with b_high and a_low with b_low respectively.
IDV Correction Calulation : In this script the Intraday Volatility (IDV) is calculated as the simple moving average (SMA) of the daily high-low price range divided by the closing price. This measures how much the price fluctuates in a given period.
Composite High and Low with Volatility: The final c_high and c_low values are obtained by adjusting high_c and low_c with the calculated intraday volatility (IDV). These values are used to create the "Composite High" and "Composite Low" plots.
Composite High and Low with Volatility Correction: The final c_high and c_low values are obtained by adjusting high_c and low_c with the calculated intraday volatility (IDV). These values are used to create the "Composite High" and "Composite Low" plots.
2. Momentum Blocks Based on Z-Score:
Relative Price Change (RPC):
The Relative Price Change (rpdev) is calculated as the difference between the current high-low-close average (hlc3) and the previous simple moving average (psma_hlc3) of the same quantity. This measures the change in price over time.
Additionally, std_hlc3 is calculated as the standard deviation of the hlc3 values over a specified look-back period. The standard deviation quantifies the dispersion or volatility in the price data.
The rpdev is then divided by the std_hlc3 to normalize the price change by the volatility. This normalization ensures that the price change is expressed in terms of standard deviations, which is a common practice in quantitative analysis.
Essentially, the rpdev represents how many standard deviations the current price is away from the previous moving average.
Volume Correction (VC): If the include_vc input is set to true, volume correction is applied by dividing the trading volume by the previous simple moving average of the volume (psma_volume). This accounts for changes in trading activity.
Volume Corrected Relative Price Change (VCRPD): The vcrpd is calculated by multiplying the rpdev by the volume correction factor (vc). This incorporates both price changes and volume data.
Z-Scores: The Z-scores are calculated by taking the difference between the vcrpd and the mean (mean_vcrpd) and then dividing it by the standard deviation (stddev_vcrpd). Z-scores measure how many standard deviations a value is away from the mean. They help identify whether a value is unusually high or low compared to its historical distribution.
Momentum Blocks: The "Momentum Blocks" are essentially derived from the Z-scores (avgZScore). The script assigns different colors to the "Fill Area" based on predefined Z-score ranges. These colored areas represent different momentum zones:
Positive Z-scores indicate bullish momentum, and different shades of green are used to fill the area.
Negative Z-scores indicate bearish momentum, and different shades of red are used.
Z-scores near zero (between -0.25 and 0.25) suggest neutrality, and a yellow color is used.
TechniTrend: Volatility and MACD Trend Highlighter🟦 Overview
The "Candle Volatility with Trend Prediction" indicator is a powerful tool designed to identify market volatility based on candle movement relative to average volume while also incorporating trend predictions using the MACD. This indicator is ideal for traders who want to detect volatile market conditions and anticipate potential price movements, leveraging both price changes and volume dynamics.
It not only highlights candles with significant price movements but also integrates a trend analysis based on the MACD (Moving Average Convergence Divergence), allowing traders to gauge whether the market momentum aligns with or diverges from the detected volatility.
🟦 Key Features
🔸Volatility Detection: Identifies candles that exceed normal price fluctuations based on average volume and recent price volatility.
🔸Trend Prediction: Uses the MACD indicator to overlay trend analysis, signaling potential market direction shifts.
🔸Volume-Based Analysis: Integrates customizable moving averages (SMA, EMA, WMA, etc.) of volume, providing a clear visualization of volume trends.
🔸Alert System: Automatically notifies traders of high-volatility situations, aiding in timely decision-making.
🔸Customizability: Includes multiple settings to tailor the indicator to different market conditions and timeframes.
🟦 How It Works
The indicator operates by evaluating the price volatility in relation to average volume and identifying when a candle's volatility surpasses a threshold defined by the user. The key calculations include:
🔸Average Volume Calculation: The user selects the type of moving average (SMA, EMA, etc.) to calculate the average volume over a set period.
🔸Volatility Measurement: The indicator measures the body change (difference between open and close) and the high-low range of each candle. It then calculates recent price volatility using a standard deviation over a user-defined length.
🔸Weighted Index: A unique index is created by dividing price change by average volume and recent volatility.
🔸Highlighting Volatility: If the weighted index exceeds a customizable threshold, the candle is highlighted, indicating potential trading opportunities.
🔸Trend Analysis with MACD: The MACD line and signal line are plotted and adjusted with a user-defined multiplier to visualize trends alongside the volatility signals.
🟦 Recommended Settings
🔸Volume MA Length: A default of 14 periods for the average volume calculation is recommended. Adjust to higher periods for long-term trends and shorter periods for quick trades.
🔸Volatility Threshold Multiplier: Set at 1.2 by default to capture moderately significant movements. Increase for fewer but stronger signals or decrease for more frequent signals.
🔸MACD Settings: Default MACD parameters (12, 26, 9) are suggested. Tweak based on your trading strategy and asset volatility.
🔸MACD Multiplier: Adjust based on how the MACD should visually compare to the average volume. A multiplier of 1 works well for most cases.
🟦 How to Use
🔸Volatile Market Detection:
Look for highlighted candles that suggest a deviation from typical price behavior. These candles often signify an entry point for short-term trades.
🔸Trend Confirmation:
Use the MACD trend analysis to verify if the highlighted volatile candles align with a bullish or bearish trend.
For example, a bullish MACD crossover combined with a highlighted candle suggests a potential uptrend, while a bearish crossover with volatility signals may indicate a downtrend.
🔸Volume-Driven Strategy:
Observe how volume changes impact candle volatility. When volume rises significantly and candles are highlighted, it can suggest strong market moves influenced by big players.
🟦 Best Use Cases
🔸Trend Reversals: Detect potential trend reversals early by spotting divergences between price and MACD within volatile conditions.
🔸Breakout Strategies: Use the indicator to confirm price breakouts with significant volume changes.
🔸Scalping or Day Trading: Customize the indicator for shorter timeframes to capture rapid market movements based on volatility spikes.
🔸Swing Trading: Combine volatility and trend insights to optimize entry and exit points over longer periods.
🟦 Customization Options
🔸Volume-Based Inputs: Choose from SMA, EMA, WMA, and more to define how average volume is calculated.
🔸Threshold Adjustments: Modify the volatility threshold multiplier to increase or decrease sensitivity based on your trading style.
🔸MACD Tuning: Adjust MACD settings and the multiplier for trend visualization tailored to different asset classes and market conditions.
🟦 Indicator Alerts
🔸High Volatility Alerts: Automatically triggered when candles exceed user-defined volatility levels.
🔸Bullish/Bearish Trend Alerts: Alerts are activated when highlighted volatile candles align with bullish or bearish MACD crossovers, making it easier to spot opportunities without constantly monitoring the chart.
🟦 Examples of Use
To better understand how this indicator works, consider the following scenarios:
🔸Example 1: In a strong uptrend, observe how volume surges and volatility highlight candles right before price consolidations, indicating optimal exit points.
🔸Example 2: During a downtrend, see how the MACD aligns with volume-driven volatility, signaling potential short-selling opportunities.
Bandwidth Volatility - Silverman Rule of thumb EstimatorOverview
This indicator calculates volatility using the Rule of Thumb bandwidth estimator and incorporating the standard deviations of returns to get historical volatility. There are two options: one for the original rule of thumb bandwidth estimator, and another for the modified rule of thumb estimator. This indicator comes with the bandwidth , which is shown with the color gradient columns, which are colored by a percentile of the bandwidth, and the moving average of the bandwidth, which is the dark shaded area.
The rule of thumb bandwidth estimator is a simple and quick method for estimating the bandwidth parameter in kernel density estimation (KSE) or kernel regression. It provides a rough approximation of the bandwidth without requiring extensive computation resources or fine-tuning. One common rule of thumb estimator is Silverman rule, which is given by
h = 1.06*σ*n^(-1/5)
where
h is the bandwidth
σ is the standard deviation of the data
n is the number of data points
This rule of thumb is based on assuming a Gaussian kernel and aims to strike a balance between over-smoothing and under-smoothing the data. It is simple to implement and usually provides reasonable bandwidth estimates for a wide range of datasets. However , it is important to note that this rule of thumb may not always have optimal results, especially for non-Gaussian or multimodal distributions. In such cases, a modified bandwidth selection, such as cross-validation or even applying a log transformation (if the data is right-skewed), may be preferable.
How it works:
This indicator computes the bandwidth volatility using returns, which are used in the standard deviation calculation. It then estimates the bandwidth based on either the Silverman rule of thumb or a modified version considering the interquartile range. The percentile ranks of the bandwidth estimate are then used to visualize the volatility levels, identify high and low volatility periods, and show them with colors.
Modified Rule of thumb Bandwidth:
The modified rule of thumb bandwidth formula combines elements of standard deviations and interquartile ranges, scaled by a multiplier of 0.9 and inversely with a number of periods. This modification aims to provide a more robust and adaptable bandwidth estimation method, particularly suitable for financial time series data with potentially skewed or heavy-tailed data.
Formula for Modified Rule of Thumb Bandwidth:
h = 0.9 * min(σ, (IQR/1.34))*n^(-1/5)
This modification introduces the use of the IQR divided by 1.34 as an alternative to the standard deviation. It aims to improve the estimation, mainly when the underlying distribution deviates from a perfect Gaussian distribution.
Analysis
Rule of thumb Bandwidth: Provides a broader perspective on volatility trends, smoothing out short-term fluctuations and focusing more on the overall shape of the density function.
Historical Volatility: Offers a more granular view of volatility, capturing day-to-day or intra-period fluctuations in asset prices and returns.
Modelling Requirements
Rule of thumb Bandwidth: Provides a broader perspective on volatility trends, smoothing out short-term fluctuations and focusing more on the overall shape of the density function.
Historical Volatility: Offers a more granular view of volatility, capturing day-to-day or intra-period fluctuations in asset prices and returns.
Pros of Bandwidth as a volatility measure
Robust to Data Distribution: Bandwidth volatility, especially when estimated using robust methods like Silverman's rule of thumb or its modifications, can be less sensitive to outliers and non-normal distributions compared to some other measures of volatility
Flexibility: It can be applied to a wide range of data types and can adapt to different underlying data distributions, making it versatile for various analytical tasks.
How can traders use this indicator?
In finance, volatility is thought to be a mean-reverting process. So when volatility is at an extreme low, it is expected that a volatility expansion happens, which comes with bigger movements in price, and when volatility is at an extreme high, it is expected for volatility to eventually decrease, leading to smaller price moves, and many traders view this as an area to take profit in.
In the context of this indicator, low volatility is thought of as having the green color, which indicates a low percentile value, and also being below the moving average. High volatility is thought of as having the yellow color and possibly being above the moving average, showing that you can eventually expect volatility to decrease.
Grid by Volatility (Expo)█ Overview
The Grid by Volatility is designed to provide a dynamic grid overlay on your price chart. This grid is calculated based on the volatility and adjusts in real-time as market conditions change. The indicator uses Standard Deviation to determine volatility and is useful for traders looking to understand price volatility patterns, determine potential support and resistance levels, or validate other trading signals.
█ How It Works
The indicator initiates its computations by assessing the market volatility through an established statistical model: the Standard Deviation. Following the volatility determination, the algorithm calculates a central equilibrium line—commonly referred to as the "mid-line"—on the chart to serve as a baseline for additional computations. Subsequently, upper and lower grid lines are algorithmically generated and plotted equidistantly from the central mid-line, with the distance being dictated by the previously calculated volatility metrics.
█ How to Use
Trend Analysis: The grid can be used to analyze the underlying trend of the asset. For example, if the price is above the Average Line and moves toward the Upper Range, it indicates a strong bullish trend.
Support and Resistance: The grid lines can act as dynamic support and resistance levels. Price tends to bounce off these levels or breakthrough, providing potential trade opportunities.
Volatility Gauge: The distance between the grid lines serves as a measure of market volatility. Wider lines indicate higher volatility, while narrower lines suggest low volatility.
█ Settings
Volatility Length: Number of bars to calculate the Standard Deviation (Default: 200)
Squeeze Adjustment: Multiplier for the Standard Deviation (Default: 6)
Grid Confirmation Length: Number of bars to calculate the weighted moving average for smoothing the grid lines (Default: 2)
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Realized volatility differentialAbout
This is a simple indicator that takes into account two types of realized volatility: Close-Close and High-Low (the latter is more useful for intraday trading).
The output of the indicator is two values / plots:
an average of High-Low volatility minus Close-Close volatility (10day period is used as a default)
the current value of the indicator
When the current value is:
lower / below the average, then it means that High-Low volatility should increase.
higher / above then obviously the opposite is true.
How to use it
It might be used as a timing tool for mean reversion strategies = when your primary strategy says a market is in mean reversion mode, you could use it as a signal for opening a position.
For example: let's say a security is in uptrend and approaching an important level (important to you).
If the current value is:
above the average, a short position can be opened, as High-Low volatility should decrease;
below the average, a trend should continue.
Intended securities
Futures contracts
LS Volatility Index█ OVERVIEW
This indicator serves to measure the volatility of the price in relation to the average.
It serves four purposes:
1. Identify abnormal prices, extremely stretched in relation to an average;
2. Identify acceptable prices in the context of the main trend;
3. Identify market crashes;
4. Identify divergences.
█ CONCEPTS
The LS Volatility Index was originally described by Brazilian traders Alexandre Wolwacz (Stormer) , Fabrício Lorenz , and Fábio Figueiredo (Vlad)
Basically, this indicator can be used in two ways:
1. In a mean reversion strategy , when there is an unusual distance from it;
2. In a trend following strategy , when the price is in an acceptable region.
Perhaps the version presented here may have some slight differences, but the core is the same.
The original indicator is presented with a 21-period moving average, but here this value is customizable.
I made some fine tuning available, namely:
1. The possibility of smoothing the indicator;
2. Choose the type of moving average;
3. Customizable period;
4. Possibility to show a moving average of the indicator;
5. Color customization.
█ CALCULATION
First, the distance of the price from a given average in percentage terms is measured.
Then, the historical average volatility is obtained.
Finally the indicator is calculated through the ratio between the distance and the historical volatility.
To facilitate visualization, the result is normalized in a range from 0 to 100.
When it reaches 0, it means the price is on average.
When it hits 100, it means the price is way off average (stretched).
█ HOW TO USE IT
Here are some examples:
1. In a return-to-average strategy
2. In a trend following strategy
3. Identification of crashes and divergences
█ THANKS AND CREDITS
- Alexandre Wolwacz (Stormer), Fabrício Lorenz, Fábio Figueiredo (Vlad)
- Feature scaler (for normalization)
- HPotter (for calc of Historical Volatility)
Volume and Volatility Ratio Indicator-WODI策略名称
交易量与波动率比例策略-WODI
一、用户自定义参数
vol_length：交易量均线长度，计算基础交易量活跃度。
index_short_length / index_long_length：指数短期与长期均线长度，用于捕捉中短期与中长期趋势。
index_magnification：敏感度放大倍数，调整指数均线的灵敏度。
index_threshold_magnification：阈值放大因子，用于动态过滤噪音。
lookback_bars：形态检测回溯K线根数，用于捕捉反转模式。
fib_tp_ratio / fib_sl_ratio：斐波那契止盈与止损比率，分别对应黄金分割（0.618/0.382 等）级别。
enable_reversal：反转信号开关，开启后将原有做空信号反向为做多信号，用于单边趋势加仓。
二、核心计算逻辑
交易量百分比
使用 ta.sma 计算 vol_ma，并得到 vol_percent = volume / vol_ma * 100。
价格波动率
volatility = (high – low) / close * 100。
构建复合指数
volatility_index = vol_percent * volatility，并分别计算其短期与长期均线（乘以 index_magnification）。
动态阈值
index_threshold = index_long_ma * index_threshold_magnification，过滤常规波动。
三、信号生成与策略执行
做多/做空信号
当短期指数均线自下而上突破长期均线，且 volatility_index 突破 index_threshold 时，发出做多信号。
当短期指数均线自上而下跌破长期均线，且 volatility_index 跌破 index_threshold 时，发出做空信号。
反转信号模式（可选）
若 enable_reversal = true，则所有做空信号反向为做多，用于在强趋势行情中加仓。
止盈止损管理
进场后自动设置斐波那契止盈位（基于入场价 × fib_tp_ratio）和止损位（入场价 × fib_sl_ratio）。
支持多级止盈：可依次以 0.382、0.618 等黄金分割比率分批平仓。
四、图表展示
策略信号标记：图上用箭头标明每次做多/做空（或反转加仓）信号。
斐波那契区间：在K线图中显示止盈/止损水平线。
复合指数与阈值线：与原版相同，在独立窗口绘制短、长期指数均线、指数曲线及阈值。
量能柱状：高于均线时染色，反转模式时额外高亮。
Strategy Name
Volume and Volatility Ratio Strategy – WODI
1. User-Defined Parameters
vol_length: Length for volume SMA.
index_short_length / index_long_length: Short and long MA lengths for the composite index.
index_magnification: Sensitivity multiplier for index MAs.
index_threshold_magnification: Threshold multiplier to filter noise.
lookback_bars: Number of bars to look back for pattern detection.
fib_tp_ratio / fib_sl_ratio: Fibonacci take-profit and stop-loss ratios (e.g. 0.618, 0.382).
enable_reversal: Toggle for reversal mode; flips short signals to long for trend-following add-on entries.
2. Core Calculation
Volume Percentage:
vol_ma = ta.sma(volume, vol_length)
vol_percent = volume / vol_ma * 100
Volatility:
volatility = (high – low) / close * 100
Composite Index:
volatility_index = vol_percent * volatility
Short/long MAs applied and scaled by index_magnification.
Dynamic Threshold:
index_threshold = index_long_ma * index_threshold_magnification.
3. Signal Generation & Execution
Long/Short Entries:
Long when short MA crosses above long MA and volatility_index > index_threshold.
Short when short MA crosses below long MA and volatility_index < index_threshold.
Reversal Mode (optional):
If enable_reversal is on, invert all short entries to long to scale into trending moves.
Fibonacci Take-Profit & Stop-Loss:
Automatically set TP/SL levels at entry price × respective Fibonacci ratios.
Supports multi-stage exits at 0.382, 0.618, etc.
4. Visualization
Signal Arrows: Marks every long/short or reversal-add signal on the chart.
Fibonacci Zones: Plots TP/SL lines on the price panel.
Index & Threshold: Same as v1.0, with MAs, index curve, and threshold in a separate sub-window.
Volume Bars: Colored when above vol_ma; extra highlight if a reversal-add signal triggers
RSI and Dev Advanced Volatility IndexEnglish Explanation of the "RSI and Dev Advanced Volatility Index" Pine Script Code
Understanding the Code
Purpose:
This Pine Script code creates a custom indicator that combines the Relative Strength Index (RSI) and Deviation (DEV) to provide insights into market volatility.
Key Components:
* Deviation (DEV): Calculates the difference between the closing price and the 10-period simple moving average. This measures the extent to which the price deviates from its recent average, indicating volatility.
* RSI: The traditional RSI is then applied to the calculated deviations. This helps to smooth the data and identify overbought or oversold conditions in terms of volatility.
Calculation Steps:
* Deviation Calculation: The difference between the closing price and its 10-period simple moving average is calculated.
* RSI Calculation: The RSI is calculated on the deviations, providing a measure of the speed and change of volatility relative to recent volatility changes.
* Plotting:
* The RSI of the deviations is plotted on the chart.
* Horizontal lines are plotted at 50, 0, and 110 to visually represent different volatility zones.
* The area between the lines is filled with color to highlight low and high volatility regions.
Interpretation and Usage
* Volatility Analysis:
* High Volatility: When the RSI is above 50, it indicates high volatility, suggesting the market might be in a consolidation or trend reversal phase.
* Low Volatility: When the RSI is below 50, it indicates low volatility, suggesting a relatively calm market.
* Trading Signals:
* Buy Signal: When the RSI crosses above 50 from below, it might signal increasing volatility, which could be a buying opportunity.
* Sell Signal: When the RSI crosses below 50 from above, it might signal decreasing volatility, which could be a selling opportunity.
* Risk Management:
* By monitoring volatility, traders can better manage their risk. During periods of high volatility, traders might reduce their position size or adopt more conservative strategies.
Advantages
* Comprehensive: Combines RSI and DEV for a more holistic view of volatility.
* Sensitivity: Quickly responds to changes in market volatility.
* Visual Clarity: Color-coded zones provide a clear visual representation of different volatility levels.
Limitations
* Parameter Sensitivity: The indicator's performance is sensitive to parameter changes, such as the lookback period for the moving average.
* Lag: Like most technical indicators, it has some lag and might not capture every market movement.
* Not Predictive: It can only indicate current and past volatility, not future movements.
Summary
This custom indicator offers a valuable tool for analyzing market volatility. By combining RSI and DEV, it provides a more nuanced perspective on price fluctuations. However, it should be used in conjunction with other technical indicators and fundamental analysis for more robust trading decisions.
Key points to remember:
* Higher RSI values indicate higher volatility.
* Lower RSI values indicate lower volatility.
* Crossovers of the RSI line above or below 50 can provide potential trading signals.
* The indicator should be used in conjunction with other analysis tools for a more complete picture of the market.
Volume and Volatility Ratio Indicator-WODI该指标名为“交易量与波动率比例指标-WODI”，主要基于交易量和价格波动率构造一个复合指数，帮助识别市场内可能存在的异常或转折信号。具体实现如下：
用户自定义参数
用户可以设置交易量均线长度（vol_length）、指数的短期与长期均线长度（index_short_length、index_long_length）、均线敏感度（index_magnification）、阈值放大因子（index_threshold_magnification）以及检测K线形态的区间（lookback_bars）。这些参数为后续计算提供了灵活性，允许用户根据不同市场环境自定义指标的敏感度和响应速度。
交易量均线与百分比计算
首先通过 ta.sma 计算指定长度的交易量简单均线（vol_ma）。
接下来，将当前交易量与均线进行比较，计算出当前交易量占均线的百分比（vol_percent），这反映了短期内交易量的相对活跃程度。
波动率的衡量
使用当前K线的最高价和最低价计算振幅，再除以收盘价乘以100得到波动率（volatility），从而反映市场价格波动的幅度。
构建交易量/波动率指数
将交易量百分比与波动率相乘，形成了“交易量/波动率指数”（volatility_index）。该指数能够同时反映市场的交易活跃度和价格波动性，两者的联合作用帮助捕捉市场的“热度”。
计算指标均线与阈值
对交易量/波动率指数分别计算短期均线（index_short_ma）和长期均线（index_long_ma），并通过乘以一个敏感度参数（index_magnification）进行调整。
同时，依据长期均线计算一个阈值（index_threshold），起到过滤噪音的作用。当指数突破该阈值时，可能预示着市场的重要变化。
K线形态与反转模式检测
通过遍历最近几根K线（由lookback_bars控制），指标会检测是否符合一系列预定条件（涉及交易量、价格振幅、K线形态等），以判断是否存在反转模式。若符合条件，则标记为反转模式，从而为潜在的转折点提供提示。
图表展示
最终在独立窗口中绘制多个元素：
指数短均线与长均线：经过敏感度调整后显示，用于分析指数趋势。
交易量/波动率指数：采用阶梯线风格绘制，直观展示指数变化。
阈值线：作为参考水平，便于判断指数是否突破常规范围。
交易量柱状图：当当前交易量高于均线时，通过不同颜色显示；当检测到反转模式时，颜色会进一步强化，帮助用户迅速识别潜在信号。
English Description
This indicator, titled “Volume and Volatility Ratio Indicator - WODI”, is designed to construct a composite index based on trading volume and price volatility, aiding in the identification of abnormal market conditions or potential reversal signals. Its functionality is broken down as follows:
User-Defined Parameters
The indicator allows users to set parameters such as the moving average length for volume (vol_length), the short and long moving average lengths for the index (index_short_length and index_long_length), a sensitivity multiplier (index_magnification), a threshold magnification factor (index_threshold_magnification), and the number of bars for pattern detection (lookback_bars). These parameters provide flexibility to adjust the sensitivity and responsiveness of the indicator based on different market conditions.
Volume Moving Average and Percentage Calculation
A simple moving average (SMA) of volume is computed over the specified length (vol_ma) using the ta.sma function.
The current volume is then compared to its moving average to calculate the volume percentage (vol_percent), reflecting the relative trading intensity in the short term.
Measuring Volatility
Volatility is calculated based on the current bar’s high and low prices, normalized by the closing price and multiplied by 100, which provides a measure of the market’s price fluctuation magnitude.
Constructing the Volume/Volatility Index
The index (volatility_index) is derived by multiplying the volume percentage by the calculated volatility. This composite metric reflects both market activity and price movement, effectively capturing the overall “heat” of the market.
Calculating the Index Moving Averages and Threshold
Two moving averages for the volatility_index are computed: one short-term (index_short_ma) and one long-term (index_long_ma). These are then adjusted by the sensitivity multiplier (index_magnification).
A threshold level (index_threshold) is calculated based on the long-term moving average multiplied by the threshold magnification factor, serving to filter out market noise. When the index exceeds this threshold, it may signal significant market shifts.
Detection of Reversal Patterns
The indicator iterates through the recent bars (as determined by lookback_bars) to check whether a set of predetermined conditions (involving trends in the volatility_index, volume comparisons, price closes, and K-line patterns) are met. If these conditions are satisfied, it flags a reversal pattern, which may serve as a warning for a potential market turnaround.
Visualization on the Chart
The final display includes several elements plotted in a separate indicator window:
The short-term and long-term moving averages of the index (after sensitivity adjustment) which help visualize the trend of the composite index.
The volatility index itself is drawn using a step-line style for clarity.
A threshold line is plotted to provide a reference level against which index movements can be compared.
A volume histogram is also displayed, where bars are colored differently when the current volume exceeds the moving average; the color is further enhanced if a reversal pattern is detected, making it easy for users to quickly spot potential signals.
L&S Volatility Index Refurbished█ Introduction
This is my second version of the L&S Volatility Index, hence the name "Refurbished".
The first version can be found at this link:
The reason I released a separate version is because I rewrote the source code from scratch with the aim of both improving the indicator and staying as close as possible to the original concept.
I feel that the first version was somewhat exotic and polluted in relation to the indicator originally described by the authors.
In short, the main idea remains the same, however, the way of presenting the result has been changed, reiterating what was said.
█ CONCEPTS
The L&S Volatility Index measures the volatility of price in relation to a moving average.
The indicator was originally described by Brazilian traders Alexandre Wolwacz (Stormer) and Fábio Figueiredo (Vlad) from L&S Educação Financeira.
Basically, this indicator can be used in two ways:
1. In a mean reversion strategy, when there is an unusual distance from it;
2. In a trend following strategy, when the price is in an acceptable region.
As an indicator of volatility, the greatest utility is shown in first case.
This is because it allows identifying abnormal prices, extremely stretched in relation to an average, including market crashes.
How the calculation is done:
First, the distance of the price from a given average in percentage terms is measured.
Then, the historical average volatility is obtained.
Finally the indicator is calculated through the ratio between the distance and the historical volatility.
According to the description proposed by the creators, when the L&S Volatility Index is above 30 it means that the price is "stretched".
The closer to 100 the more stretched.
When it reaches 0, it means the price is on average.
█ What to look for
Basically, you should look at non-standard prices.
How to identify it?
When the oscillator is outside the Dynamic Zone and/or the Fixed Zone (above 30), it is because the price is stretched.
Nothing on the market is guaranteed.
As with the RSI, it is not because the RSI is overbought or oversold that the price will necessarily go down or up.
It is critical to know when NOT to buy, NOT to sell or NOT to do anything.
It is always important to consider the context.
█ Improvements
The following improvements have been implemented.
It should be noted that these improvements can be disabled, thus using the indicator in the "purest" version, the same as the one conceived by the creators.
Resources:
1. Customization of limits and zones:
2. Customization of the timeframe, which can be different from the current one.
3. Repaint option (prints the indicator in real time even if the bar has not yet closed. This produces more signals).
4. Customization of price inputs. This affects the calculation.
5. Customization of the reference moving average (the moving average used to calculate the price distance).
6. Customization of the historical volatility calculation strategy.
- Accumulated ATR: calculates the historical volatility based on the accumulated ATR.
- Returns: calculates the historical volatility based on the returns of the source.
Both forms of volatility calculation have their specific utilities and applications.
Therefore, it is worthwhile to have both approaches available, and one should not necessarily replace the other.
Each method has its advantages and may be more appropriate in different contexts.
The first approach, using the accumulated ATR, can be useful when you want to take into account the implied volatility of prices over time,
reflecting broader price movements and higher impact events. It can be especially relevant in scenarios where unexpected events can drastically affect prices.
The second approach, using the standard deviation of returns, is more common and traditionally used to measure historical volatility.
It considers the variability of prices relative to their average, providing a more general measure of market volatility.
Therefore, both forms of calculation have their merits and can be useful depending on the context and specific analysis needs.
Having both options available gives users flexibility in choosing the most appropriate volatility measure for the situation at hand.
* When choosing "Accumulated ATR", if the indicator becomes difficult to see, there are 3 possibilities:
a) manually adjust the Fixed Zone value;
b) disable the Fixed Zone and use only the Dynamic Zone;
c) normalize the indicator.
7. Signal line (a moving average of the oscillator).
8. Option to normalize the indicator or not.
9. Colors to facilitate direction interpretation.
Since the L&S is a volatility indicator, it does not show whether the price is rising or falling.
This can sometimes confuse the user.
That said, the idea here is to show certain colors where the price is relative to the average, making it easier to analyze.
10. Alert messages for automations.
Options Volatility Strategy Analyzer [TradeDots]The Options Volatility Strategy Analyzer is a specialized tool designed to help traders assess market conditions through a detailed examination of historical volatility, market benchmarks, and percentile-based thresholds. By integrating multiple volatility metrics (including VIX and VIX9D) with color-coded regime detection, the script provides users with clear, actionable insights for selecting appropriate options strategies.
📝 HOW IT WORKS
1. Historical Volatility & Percentile Calculations
Annualized Historical Volatility (HV): The script automatically computes the asset’s historical volatility using log returns over a user-defined period. It then annualizes these values based on the chart’s timeframe, helping you understand the asset’s typical volatility profile.
Dynamic Percentile Ranks: To gauge where the current volatility level stands relative to past behavior, historical volatility values are compared against short, medium, and long lookback periods. Tracking these percentile ranks allows you to quickly see if volatility is high or low compared to historical norms.
2. Multi-Market Benchmark Comparison
VIX and VIX9D Integration: The script tracks market volatility through the VIX and VIX9D indices, comparing them to the asset’s historical volatility. This reveals whether the asset’s volatility is outpacing, lagging, or remaining in sync with broader market volatility conditions.
Market Context Analysis: A built-in term-structure check can detect market stress or relative calm by measuring how VIX compares to shorter-dated volatility (VIX9D). This helps you decide if the present environment is risk-prone or relatively stable.
3. Volatility Regime Detection
Color-Coded Background: The analyzer assigns a volatility regime (e.g., “High Asset Vol,” “Low Asset Vol,” “Outpacing Market,” etc.) based on current historical volatility percentile levels and asset vs. market ratios. A color-coded background highlights the regime, enabling traders to quickly interpret the market’s mood.
Alerts on Regime Changes & Spikes: Automated alerts warn you about any significant expansions or contractions in volatility, allowing you to react swiftly in changing conditions.
4. Strategy Forecast Table
Real-Time Strategy Suggestions: At the close of each bar, an on-chart table generates suggested options strategies (e.g., selling premium in high volatility or buying premium in low volatility). These suggestions provide a quick summary of potential tactics suited to the current regime.
Contextual Market Data: The table also displays key statistics, such as VIX levels, asset historical volatility percentile, or ratio comparisons, helping you confirm whether volatility conditions warrant more conservative or more aggressive strategies.
🛠️ HOW TO USE
1. Select Your Timeframe: The script supports multiple timeframes. For short-term trading, intraday charts often reveal faster shifts in volatility. For swing or position trading, daily or weekly charts may be more stable and produce fewer false signals.
2. Check the Volatility Regime: Observe the background color and on-chart labels to identify the current regime (e.g., “HIGH ASSET VOL,” “LOW VOL + LAGGING,” etc.).
3. Review the Forecast Table: The table suggests strategy ideas (e.g., iron condors, long straddles, ratio spreads) depending on whether volatility is elevated, subdued, or spiking. Use these as a starting point for designing trades that match your risk tolerance.
4. Combine with Additional Analysis: For optimal results, confirm signals with your broader trading plan, technical tools (moving averages, price action), and fundamental research. This script is most effective when viewed as one component in a comprehensive decision-making process.
❗️LIMITATIONS
Directional Neutrality: This indicator analyzes volatility environments but does not predict price direction (up/down). Traders must combine with directional analysis for complete strategy selection.
Late or Missed Signals: Since all calculations require a bar to close, sharp intrabar volatility moves may not appear in real-time.
False Positives in Choppy Markets: Rapid changes in percentile ranks or VIX movements can generate conflicting or premature regime shifts.
Data Sensitivity: Accuracy depends on the availability and stability of volatility data. Significant gaps or unusual market conditions may skew results.
Market Correlation Assumptions: The system assumes assets generally correlate with S&P 500 volatility patterns. May be less effective for:
Small-cap stocks with unique volatility drivers
International stocks with different market dynamics
Sector-specific events disconnected from broad market
Cryptocurrency-related assets with independent volatility patterns
RISK DISCLAIMER
Options trading involves substantial risk and is not suitable for all investors. Options strategies can result in significant losses, including the total loss of premium paid. The complexity of options strategies requires thorough understanding of the risks involved.
This indicator provides volatility analysis for educational and informational purposes only and should not be considered as investment advice. Past volatility patterns do not guarantee future performance. Market conditions can change rapidly, and volatility regimes may shift without warning.
No trading system can guarantee profits, and all trading involves the risk of loss. The indicator's regime classifications and strategy suggestions should be used as part of a comprehensive trading plan that includes proper risk management, directional analysis, and consideration of broader market conditions.
The Ultimate ATR-BBW Market Volatility Indicator"The ATR-BBW Market Volatility Indicator combines the Average True Range (ATR) and Bollinger Bands Width (BBW) to provide a measure of market volatility. This indicator does not indicate bullish or bearish trends, but rather the magnitude of price fluctuations.
* Usage: When the indicator moves upward, it suggests increasing market volatility, indicating that prices are moving within a wider range. Conversely, a downward movement implies decreasing volatility, signifying that prices are moving within a narrower range.
* Note: This sub-indicator solely reflects market volatility and does not provide buy or sell signals.
Investing involves risk. Please conduct thorough research before making any investment decisions.
ATR and BBW Explained:
* Average True Range (ATR): ATR is a technical analysis indicator used to measure market volatility. It calculates the average of a series of true ranges, where the true range is the greatest of the following:
* The current high minus the current low
* The absolute value of the current high minus the previous close
* The absolute value of the current low minus the previous close
* A higher ATR value indicates higher volatility, while a lower value suggests lower volatility.
* Bollinger Bands Width (BBW): Bollinger Bands are plotted two standard deviations above and below a simple moving average. BBW measures the distance between the upper and lower bands. A wider BBW indicates higher volatility, as prices are moving further away from the moving average. Conversely, a narrower BBW suggests lower volatility.
Combining ATR and BBW:
By combining ATR and BBW, the ATR-BBW indicator provides a more comprehensive view of market volatility. ATR captures the overall volatility of the market, while BBW measures the volatility relative to the moving average. Together, they provide a more robust indicator of market conditions and can be used to identify potential trading opportunities.
Why ATR and BBW are Effective for Measuring Volatility:
* ATR directly measures the actual price movement, regardless of the direction.
* BBW shows how much prices are deviating from their average, indicating the strength of the current trend.
* Combined: By combining these two measures, the ATR-BBW indicator provides a more comprehensive and accurate assessment of market volatility.
In essence, the ATR-BBW indicator helps traders understand the magnitude of price fluctuations, allowing them to make more informed trading decisions.
Fixed Volatility OscillatorA fixed volatility plotter set to a 0-100 range - Plots the current volatility % using the formula to calculate volatility and stdev (standard deviation) based on the candle lookback.
The indicator is Fixed, which means that regardless of the chart, the volatility will be plotted on a percentage of 0% - 100% with a 101% threshold set to indicate a volatility reset. While the volume of volatility will change depending on the chart, the volatility will ALWAYS stay within this range.
if a plot exceeds 100% it should be marked as volatility reset - not an expansion
and should also be noted that the volatility spikes are also very inconsistent in volume and vary greatly.
The candle lookbacks on standard are organized be from 10 candles to 100 candles. I found the best results using the 50 candles lookback, and therefore have set it as the default value. These different values can be used to pull the information from the # of candles on the selected option - and therefore the volatility will be calculated from the number of candles selected.
// note for other people versed in pinescript
While this indicator may be useful in trading or strategies, it is more meant to incorporated into other scripts or used as a basis that can be further expanded on. The visuals are not built at all - for that purpose.
This script has not been listed as a library for the fact that it can be used as an actual indicator within a strategy - hope you enjoy.
Implied Volatility Suite (TG Fork)Displays the Implied Volatility, which is usually calculated from options, but here is calculated indirectly from spot price directly, either using a model or model-free using the VIXfix.
The model-free VIXfix based approach can detect times of high volatility, which usually coincides with panic and hence lowest prices. Inversely, the model-based approach can detect times of highest greed.
Forked and updated by Tartigradia to fix some issues in the calculations, convert to pinescript v5 and reverse engineered to reproduce the "Implied Volatility Rank & Model Free IVR" indicator by the same author (but closed source) and allow to plot both model-based and model-free implied volatilities simultaneously.
If you like this indicator, please show the original author SegaRKO some love:
Implied Volatility SuiteThis is an updated, more robust, and open source version of my 2 previous scripts : "Implied Volatility Rank & Model-Free IVR" and "IV Rank & IV Percentile".
This specific script provides you with 4 different types of volatility data: 1)Implied volatility, 2) Implied Volatility Rank, 3)Implied Volatility Percentile, 4)Skew Index.
1) Implied Volatility is the market's forecast of a likely movement, usually 1 standard deviation, in a securities price.
2) Implied Volatility Rank, ranks IV in relation to its high and low over a certain period of time. For example if over the past year IV had a high of 20% and a low of 10% and is currently 15%; the IV rank would be 50%, as 15 is 50% of the way between 10 & 20. IV Rank is mean reverting, meaning when IV Rank is high (green) it is assumed that future volatility will decrease; while if IV rank is low (red) it is assumed that future volatility will increase.
3) Implied Volatility Percentile ranks IV in relation to how many previous IV data points are less than the current value. For example if over the last 5 periods Implied volatility was 10%,12%,13%,14%,20%; and the current implied volatility is 15%, the IV percentile would be 80% as 4 out of the 5 previous IV values are below the current IV of 15%. IV Percentile is mean reverting, meaning when IV Percentile is high (green) it is assumed that future volatility will decrease; while if IV percentile is low (red) it is assumed that future volatility will increase. IV Percentile is more robust than IV Rank because, unlike IV Rank which only looks at the previous highs and lows, IV Percentile looks at all data points over the specified time period.
4)The skew index is an index I made that looks at volatility skew. Volatility Skew compares implied volatility of options with downside strikes versus upside strikes. If downside strikes have higher IV than upside strikes there is negative volatility skew. If upside strikes have higher IV than downside strikes then there is positive volatility skew. Typically, markets have a negative volatility skew, this has been the case since Black Monday in 1987. All negative skew means is that projected option contract prices tend to go down over time regardless of market conditions.
Additionally, this script provides two ways to calculate the 4 data types above: a)Model-Based and b)VixFix.
a) The Model-Based version calculates the four data types based on a model that projects future volatility. The reason that you would use this version is because it is what is most commonly used to calculate IV, IV Rank, IV Percentile, and Skew; and is closest to real world IV values. This version is what is referred to when people normally refer to IV. Additionally, the model version of IV, Rank, Percentile, and Skew are directionless.
b) The VixFix version calculates the four data types based on the VixFix calculation. The reason that you would use this version is because it is based on past price data as opposed to a model, and as such is more sensitive to price action. Additionally, because the VixFix is meant to replicate the VIX Index (except it can be applied to any asset) it, just like the real VIX, does have a directional element to it. Because of this, VixFix IV, Rank, and Percentile tend to increase as markets move down, and decrease as markets move up. VixFix skew, on the other hand, is directionless.
How to use this suite of tools:
1st. Pick the way you want your data calculated: either Model-Based or VixFix.
2nd. Input the various length parameters according to their labels:
If you're using the model-based version and are trading options input your time til expiry, including weekends and holidays. You can do so in terms of days, hours, and minutes. If you're using the model-based version but aren't trading options you can just use the default input of 365 days.
If you're using the VixFix version, input how many periods of data you want included in the calculation, this is labeled as "VixFix length". The default value used in this script is 252.
3rd. Finally, pick which data you want displayed from the dropdown menu: Implied Volatility, IV Rank, IV Percentile, or Volatility Skew Index.
