Historical Volatility MOEXIndicator of historical volatility.
The indicator is optimized for hourly bars (1h) and displays - red line - 1 day, yellow line - 3 day, green line - 5 day historical volatility .
The indicator is intended for use on futures of the Moscow Exchange MOEX
White lines - confidence interval HV (normal distribution) for a given sigma and days
Parameters
WindowInput - the number of bars calculating the HV red line
WindowInput2 - number of bars calculating the HV yellow line
WindowInput3 - the number of bars calculating the HV green line
SigmaMultiplicatorInput - set the sigma value for calculating the HV confidence interval
Exp_Day - set the number of days to calculate the confidence interval HV
Индикатор исторической волатильности.
Индикатор оптимизирован под часовые бары и отображает - красная линия - 1 дневная, желтая линия - 3 дневная, зеленая линия - 5 дневная историческая волатильность.
The indicator is intended for use on futures of the Moscow Exchange MOEX
Белые линии - доверительный интервал HV (нормальное распределение) при заданной сигма и дней
Параметры
WindowInput - количество баров расчета HV красная линия
WindowInput2 - количество баров расчета HV желтая линия
WindowInput3 - количество баров расчета HV зеленая линия
SigmaMultiplicatorInput - задаем значение сигма для расчета доверительного интервала HV
Exp_Day - задаем количестве дней для расчета доверительного интервала HV
Use the link below to obtain access to this indicator
Search in scripts for "Volatility"
Historical Volatility CMEIndicator of historical volatility.
The indicator is optimized for hourly bars (1h) and displays - red line - 1 day, yellow line - 3 day, green line - 5 day historical volatility .
The indicator is intended for use on futures of the CME NYMEX
White lines - confidence interval HV (normal distribution) for a given sigma and days
Parameters
WindowInput - the number of bars calculating the HV red line
WindowInput2 - number of bars calculating the HV yellow line
WindowInput3 - the number of bars calculating the HV green line
SigmaMultiplicatorInput - set the sigma value for calculating the HV confidence interval
Exp_Day - set the number of days to calculate the confidence interval HV
Индикатор исторической волатильности.
Индикатор оптимизирован под часовые бары и отображает - красная линия - 1 дневная, желтая линия - 3 дневная, зеленая линия - 5 дневная историческая волатильность.
Индикатор предназначен для использования на фьючерсах бирж CME NYMEX
Белые линии - доверительный интервал HV (нормальное распределение) при заданной сигма и дней
Параметры
WindowInput - количество баров расчета HV красная линия
WindowInput2 - количество баров расчета HV желтая линия
WindowInput3 - количество баров расчета HV зеленая линия
SigmaMultiplicatorInput - задаем значение сигма для расчета доверительного интервала HV
Exp_Day - задаем количестве дней для расчета доверительного интервала HV
Use the link below to obtain access to this indicator
Historical Volatility US StoksIndicator of historical volatility.
The indicator is optimized for hourly bars (1h) and displays - red line - 1 day, yellow line - 3 day, green line - 5 day historical volatility .
The indicator is intended for use on U.S. Stocks
White lines - confidence interval HV (normal distribution) for a given sigma and days
Parameters
WindowInput - the number of bars calculating the HV red line
WindowInput2 - number of bars calculating the HV yellow line
WindowInput3 - the number of bars calculating the HV green line
SigmaMultiplicatorInput - set the sigma value for calculating the HV confidence interval
Exp_Day - set the number of days to calculate the confidence interval HV
Индикатор исторической волатильности.
Индикатор оптимизирован под часовые бары и отображает - красная линия - 1 дневная, желтая линия - 3 дневная, зеленая линия - 5 дневная историческая волатильность.
Индикатор предназначен для использования на акциях, ETF , ETN и индексах американских бирж NYSE NASDAQ и др.
Белые линии - доверительный интервал HV (нормальное распределение) при заданной сигма и дней
Параметры
WindowInput - количество баров расчета HV красная линия
WindowInput2 - количество баров расчета HV желтая линия
WindowInput3 - количество баров расчета HV зеленая линия
SigmaMultiplicatorInput - задаем значение сигма для расчета доверительного интервала HV
Exp_Day - задаем количестве дней для расчета доверительного интервала HV
Use the link below to obtain access to this indicator
Volatility Based Momentum Oscillator (VBMO)There is a frequent and definitive pattern in price movement, whereby price will steadily drift lower, then accelerate before bottoming out. Similarly, price will often steadily rise, then accelerate into a climax top.
The Volatility Based Momentum Oscillator (VBMO) is designed to delineate between steady versus more accelerated and climactic price movements.
VBMO is calculated using a short-term moving average, the distance of price from this moving average, and the trading instrument’s historical volatility. Even though VBMO’s calculation is relatively simple, the resulting values can help traders identify, analyze and act upon many scenarios, such as climax tops, reversals, and capitulation. Moreover, since the units and scale for VBMO are always the same, the indicator can be used in a consistent manner across multiple timeframes and instruments.
For more details, there is an article further describing VBMO and its applicability.
Volatility ChannelThis script is based on an idea I have had for bands that react better to crypto volatility. It calculates a Donchian Channel, SMMA-Smoothed True Range, Bollinger Bands (standard deviation), and a Keltner Channel (average true range) and averages the components to construct its bands/envelopes. This way, hopefully band touches are a more reliable indicator of a temporary bottom, and so on. Secondary coloring for strength of trend is given as a gradient based on RSI.
Parabolic SAR with Volatility Filter: Buy Alerts for 3commasHey folks and fellow 3commas users !
Here is a new signal generator for your DCA bot on 3commas.
This is a classic Parabolic SAR indicator with a filter for volatility.
NOTE: This is a repainting strategy by design. Recommended to use with "Once per bar" alert style for PSAR
Return Volatility (σ) — auto-annualized [v6]Overview
This indicator calculates and visualizes the return-based volatility (standard deviation) of any asset, automatically adjusting for your chart's timeframe to provide both absolute and annualized volatility values.
It’s designed for traders who want to filter trades, adjust position sizing, and detect volatility events based on statistically significant changes in market activity.
Key Features
Absolute Volatility (abs σ%) – Standard deviation of returns for the current timeframe (e.g., 1H, 4H, 1D).
Annualized Volatility (ann σ%) – Converts abs σ% into an annualized figure for easier cross-timeframe and cross-asset comparison.
Relative Volatility (rel σ) – Ratio of current volatility to the long-term average (default: 120 periods).
Z-Score – Number of standard deviations the current volatility is above or below its historical average.
Auto-Timeframe Adjustment – Detects your chart’s bar size (seconds per bar) and calculates bars/year automatically for crypto’s 24/7 market.
Highlight Mode – Optional yellow background when volatility exceeds set thresholds (rel σ ≥ threshold OR z-score ≥ threshold).
Alert Conditions – Alerts trigger when relative volatility or z-score exceed defined limits.
How It Works
Return Calculation
Log returns: ln(Pt / Pt-1) (default)
or Simple returns: (Pt / Pt-1) – 1
Volatility Measurement
Standard deviation of returns over the lookback period N (default: 20 bars).
Absolute volatility = σ × 100 (% per bar).
Annualization
Uses: σₐₙₙ = σ × √(bars/year) × 100 (%)
Bars/year auto-calculated based on timeframe:
1H = 8,760 bars/year
4H ≈ 2,190 bars/year
1D = 365 bars/year
Relative and Statistical Context
Relative σ = Current σ / Historical average σ (baseLen, default: 120)
Z-score = (Current σ – Historical average σ) / Std. dev. of σ over baseLen
Trading Applications
Volatility Filter – Only allow trade entries when volatility exceeds historical norms (trend traders often benefit from this).
Risk Management – Reduce position size during high volatility spikes to manage risk; increase size in low-volatility trending environments.
Market Scanning – Identify assets with the highest relative volatility for momentum or breakout strategies.
Event Detection – Highlight significant volatility surges that may precede large moves.
Suggested Settings
Lookback (N): 20 bars for short/medium-term trading.
Base Length (M): 120 bars to establish long-term volatility baseline.
Relative Threshold: 1.5× baseline σ.
Z-score Threshold: ≥ 2.0 for statistically significant volatility shifts.
Use Log Returns: Recommended for more consistent scaling across prices.
Notes & Limitations
Volatility measures movement magnitude, not direction. Combine with trend or momentum filters for directional bias.
Very low volatility may still produce false breakouts; combine with volume and market structure analysis.
Crypto markets trade 24/7 — annualization assumes no market closures; adjust for other asset classes if needed.
💡 Best Practice: Use this indicator as a pre-trade filter for breakout or trend-following strategies, or as a risk control overlay in mean-reversion systems.
[LeonidasCrypto]EMA with Volatility GlowEMA Volatility Glow - Advanced Moving Average with Dynamic Volatility Visualization
Overview
The EMA Volatility Glow indicator combines dual exponential moving averages with a sophisticated volatility measurement system, enhanced by dynamic visual effects that respond to real-time market conditions.
Technical Components
Volatility Calculation Engine
BB Volatility Curve: Utilizes Bollinger Band width normalized through RSI smoothing
Multi-stage Noise Filtering: 3-layer exponential smoothing algorithm reduces market noise
Rate of Change Analysis: Dual-timeframe RoC calculation (14/11 periods) processed through weighted moving average
Dynamic Normalization: 100-period lookback for relative volatility assessment
Moving Average System
Primary EMA: Default 55-period exponential moving average with volatility-responsive coloring
Secondary EMA: Default 100-period exponential moving average for trend confirmation
Trend Analysis: Real-time bullish/bearish determination based on EMA crossover dynamics
Visual Enhancement Framework
Gradient Band System: Multi-layer volatility bands using Fibonacci ratios (0.236, 0.382, 0.618)
Dynamic Color Mapping: Five-tier color system reflecting volatility intensity levels
Configurable Glow Effects: Customizable transparency and intensity settings
Trend Fill Visualization: Directional bias indication between moving averages
Key Features
Volatility States:
Ultra-Low: Minimal market movement periods
Low: Reduced volatility environments
Medium: Normal market conditions
High: Increased volatility phases
Extreme: Exceptional market stress periods
Customization Options:
Adjustable EMA periods
Configurable glow intensity (1-10 levels)
Variable transparency controls
Toggleable visual components
Customizable gradient band width
Technical Calculations:
ATR-based gradient bands with noise filtering
ChartPrime-inspired multi-layer fill system
Real-time volatility curve computation
Smooth color gradient transitions
Applications
Trend Identification: Dual EMA system for directional bias assessment
Volatility Analysis: Real-time market stress evaluation
Risk Management: Visual volatility cues for position sizing decisions
Market Timing: Enhanced visual feedback for entry/exit consideration
Angular Volatility📘 Angular Volatility – Technical Indicator for Trend Intensity Analysis
Angular Volatility is an advanced technical analysis tool developed specifically for cryptocurrency markets on the Binance platform. Its primary objective is to detect structural shifts in price dynamics with greater precision by analyzing the combined behavior of market volume and the angular slope of a customizable moving average.
Unlike conventional indicators that operate directly over the price chart, this script displays all of its metrics within a dedicated secondary window, allowing a cleaner and more isolated view of critical movements such as acceleration, pause, or potential reversals. In addition, it includes a robust system for volatility intensity classification, automated alerts, and a live technical info table that summarizes key real-time values.
🎯 What does Angular Volatility analyze?
Angular Volatility measures the interaction between traded volume and the angle of a moving average selected by the user from six types (SMA, EMA, WMA, HMA, ALMA, and SWMA). From these variables, the system generates:
- Angular Volatility Index: A composite value representing the product of volume and angular slope, reflecting the true strength behind a move.
- Angular Oscillator: A standalone line that displays the directional angle (in degrees) of the selected moving average, limited between ±90°.
- Volatility Intensity Levels: Automatic classification of peaks into four levels—moderate, elevated, high, and extreme—displayed with distinct colors and geometric shapes.
- Technical Data Table: A real-time panel showing both the current angle of the moving average and the current value of the Angular Volatility Index in a compact, user-friendly format.
- Custom Alerts System: Five built-in alert conditions allow users to monitor key volatility events without needing to watch the chart constantly.
⚙️ Configuration Parameters
The script includes multiple configuration sections that allow users to fine-tune both its analytical precision and visual appearance:
- High Volume Detection: Adjustable historical depth and sensitivity to identify significant volume spikes.
- Initial Moving Average Settings: Selection of MA type, length, offset, and dynamic coloring based on slope angle.
- Volatility Index Options: Fully customizable visuals, synced with the angle values set in the moving average section.
- Volatile Intensity Styling: Choose which levels to display, customize their colors and icons, and optionally color the main chart candles for quick interpretation.
- Information Table: Options to show/hide the table, adjust size and position, and customize background/text colors.
🧠 Compatibility and Technical Recommendations
This indicator was developed to operate exclusively on Binance using the following timeframes only: 1m – 5m – 15m – 30m – 1h – 4h – 1D.
This restriction is deliberate, ensuring consistency in the mathematical model used to calculate angular data. Using this script on other platforms or timeframes may result in inaccurate readings or logic errors, as asset types like stocks, forex, or indices behave differently in terms of volume structure and slope normalization.
If applied to unsupported markets or timeframes, the script will automatically display a warning message without calculating or drawing technical values.
🔬 Practical Example
The following case study—applied to the BTC chart on a 1-hour timeframe—demonstrates how volatility intensity levels behave in structured scenarios such as channel breakdowns, rebound phases, false breakouts, and high-energy consolidation zones:
🔻 Letter A: Downward breakout and full intensity sequence
- The price was moving within a fairly uniform descending channel, which ends with a false breakout to the upside—quickly invalidated as a market trap.
- The true breakout occurs to the downside through a strong red candle, categorized by the system as moderate intensity (gray).
- This candle is followed by a Doji, then a smaller red candle also marked as moderate intensity, followed by a larger red candle showing high intensity (white), and finally a stronger red candle painted yellow, indicating extreme intensity.
- This full sequence (moderate → moderate → high → extreme) marks a technical climax, after which the price begins a progressive reversal.
- Although the drop unfolds over five red candles, the subsequent recovery takes place over 18 candles, mostly green and smaller in size, forming a “V” shape: sharp decline followed by a steady upward climb.
- This entire section is enclosed within an oval labeled A, with the four intensity levels clearly reflected on both the main chart and the Angular Volatility panel.
🔼 Letter B: Ascending channel and breakout with increasing bullish pressure
- After the rebound described in section A, the price begins forming a new ascending channel, marked with the letter B. This channel starts right where the previous range ends, with a very slight upward offset—nearly indistinguishable.
- In the final stage of this channel, a green candle classified as moderate intensity (gray) attempts a breakout. It is followed by a stronger green candle, painted brown, indicating elevated intensity and confirming bullish acceleration.
- Both candles and the corresponding peak on the Angular Volatility indicator are enclosed in an oval labeled B, representing a second wave of directional energy.
⛓️ Letter C: Resistance zone and consolidation following extreme volatility
- The upward movement continues until it reaches a resistance level, where a large green candle emerges, painted yellow to denote extreme intensity.
- Unlike the previous case in section A, this movement does not trigger a sharp reversal, but rather a technical pause followed by sideways consolidation, forming a horizontal range.
- This zone is marked on the chart with an oval labeled C, representing a classic case of stopping volume and range formation.
Volatility & Market Regimes [AlgoXcalibur]Analyze Market Conditions Like a Pro.
Volatility & Market Regimes is a specialized, institution-inspired indicator designed to help traders instantly identify the current conditions of the market with clarity and confidence.
By combining a real-time Volatility Histogram and Strength Line with a compact Regime Table, this tool reveals four essential market dimensions—Volatility, Strength, Participation, and Noise—in a clean and intuitive format. Whether you’re confirming trade setups or managing risk, knowing the current regimes enhances awareness across all assets and timeframes.
🧠 Algorithm Logic
This sophisticated tool continuously monitors four independent regimes, each reflecting a distinct dimension of market behavior:
• Volatility – Gauges how active or dormant the market is by comparing current price action movement to historical averages. A dynamic, color-gradient Volatility Histogram transitions from Low (ice blue/white) to Medium (green/yellow) to High (orange/red), giving you an immediate assessment of volatility and risk.
• Strength – Measures directional intensity by assessing trend momentum, pressure, and persistence. A color-gradient Strength Line ranges from weak (red) to strong (green), helping traders determine if directional strength is trending, weakening, or consolidating.
• Participation – Analyzes relative volume to assess the level of trader engagement. Higher volume indicates stronger participation and conviction, while low volume may signal uncertainty, fading momentum, or even liquidity traps.
• Noise – Evaluates structural stability by measuring how orderly or chaotic the price action is. High noise suggests choppy, unstable conditions, while low noise reflects clean, stable moves.
Each regime includes a High / Medium / Low classification and a color-coded directional arrow to indicate whether condition parameters are increasing or decreasing. Together, these components deliver real-time market context—helping you stay grounded in logic, not emotion.
⚙️ User-Selectable Features
Each component of the indicator—the Volatility Histogram, Strength Line, and Regime Table—can be independently made visible or hidden to match your preference. This flexibility allows you to display only the Regime Table and move it directly to your main chart, where it auto-positions to the center-right and integrates seamlessly with other AlgoXcalibur indicators that also use data tables for a cohesive and refined experience.
📊 Clarity, Not Guesswork
Volatility & Market Regimes is a unique, institution-inspired algorithm rarely seen in retail trading. Not only does it clearly display volatility—it translates complex market behavior into a clear context to reveal what’s happening behind the candles. By decoding core regimes in real-time, this tool transforms uncertainty into structured insight—empowering traders to act with clarity, not guesswork.
🔐 To get access or learn more, visit the Author’s Instructions section.
Volatility-Adjusted Momentum Score (VAMS) [QuantAlgo]🟢 Overview
The Volatility-Adjusted Momentum Score (VAMS) measures price momentum relative to current volatility conditions, creating a normalized indicator that identifies significant directional moves while filtering out market noise. It divides annualized momentum by annualized volatility to produce scores that remain comparable across different market environments and asset classes.
The indicator displays a smoothed VAMS Z-Score line with adaptive standard deviation bands and an information table showing real-time metrics. This dual-purpose design enables traders and investors to identify strong trend continuation signals when momentum persistently exceeds normal levels, while also spotting potential mean reversion opportunities when readings reach statistical extremes.
🟢 How It Works
The indicator calculates annualized momentum using a simple moving average of logarithmic returns over a specified period, then measures annualized volatility through the standard deviation of those same returns over a longer timeframe. The raw VAMS score divides momentum by volatility, creating a risk-adjusted measure where high volatility reduces scores and low volatility amplifies them.
This raw VAMS value undergoes Z-Score normalization using rolling statistical parameters, converting absolute readings into standardized deviations that show how current conditions compare to recent history. The normalized Z-Score receives exponential moving average smoothing to create the final VAMS line, reducing false signals while preserving sensitivity to meaningful momentum changes.
The visualization includes dynamically calculated standard deviation bands that adjust to recent VAMS behavior, creating statistical reference zones. The information table provides real-time numerical values for VAMS Z-Score, underlying momentum percentages, and current volatility readings with trend indicators.
🟢 How to Use
1. VAMS Z-Score Bands and Signal Interpretation
Above Mean Line: Momentum exceeds historical averages adjusted for volatility, indicating bullish conditions suitable for trend following
Below Mean Line: Momentum falls below statistical norms, suggesting bearish conditions or downward pressure
Mean Line Crossovers: Primary transition signals between bullish and bearish momentum regimes
1 Standard Deviation Breaks: Strong momentum conditions indicating statistically significant directional moves worth following
2 Standard Deviation Extremes: Rare momentum readings that often signal either powerful breakouts or exhaustion points
2. Information Table and Market Context
Z-Score Values: Current VAMS reading displayed in standard deviations (σ), showing how far momentum deviates from its statistical norm
Momentum Percentage: Underlying annualized momentum displayed as percentage return, quantifying the directional strength
Volatility Context: Current annualized volatility levels help interpret whether VAMS readings occur in high or low volatility environments
Trend Indicators: Directional arrows and change values provide immediate feedback on momentum shifts and market transitions
3. Strategy Applications and Alert System
Trend Following: Use sustained readings beyond the mean line and 1σ band penetrations for directional trades, especially when VAMS maintains position in upper or lower statistical zones
Mean Reversion: Focus on 2σ extreme readings for contrarian opportunities, particularly effective in sideways markets where momentum tends to revert to statistical norms
Alert Notifications: Built-in alerts for mean crossovers (regime changes), 1σ breaks (strong signals), and 2σ touches (extreme conditions) help monitor multiple instruments for both continuation and reversal setups
ATR Volatility Expansion FilterThe ATR Volatility Expansion indicator helps traders identify when market volatility is increasing.
It compares two ATR values: the Baseline ATR, which tracks long-term volatility, and the Current ATR, which measures recent price movements.
The core concept is that when short-term volatility significantly surpasses the long-term average, it signals a period of heightened price movement. Traders can use this information to adjust their strategies accordingly.
Baseline ATR (blue): Represents long-term volatility, serving as a benchmark.
Current ATR (orange): Measures short-term volatility, highlighting recent market shifts.
Threshold ATR (red): A customizable multiplier of the Baseline ATR, setting the threshold for volatility expansion.
When the Current ATR exceeds the Threshold ATR, the background turns green, indicating volatility expansion. This provides traders with ability to get involved in moving markets or avoid choppy conditions.
The indicator is fully customizable, allowing you to adjust the ATR lengths, timeframe, and threshold multiplier to align with your trading strategy.
Volatility Breaker Blocks [BigBeluga]The Volatility Breaker Blocks indicator identifies key market levels based on significant volatility at pivot highs and lows. It plots blocks that act as potential support and resistance zones, marked in green (support) and blue (resistance). Even after a breakout, these blocks leave behind shadow boxes that continue to impact price action. The sensitivity of block detection can be adjusted in the settings, allowing traders to customize the identification of volatility breakouts. The blocks print triangle labels (up or down) after breakouts, indicating potential areas of interest.
🔵 IDEA
The Volatility Breaker Blocks indicator is designed to highlight key areas in the market where volatility has created significant price action. These blocks, created at pivot highs and lows with increased volatility, act as potential support and resistance levels.
The idea is that even after price breaks through these blocks, the remaining shadow boxes continue to influence price movements. By focusing on volatility-driven pivot points, traders can better anticipate how price may react when it revisits these areas. The indicator also captures the natural tendency for price to retest broken resistance or support levels.
🔵 KEY FEATURES & USAGE
◉ High Volatility Breaker Blocks:
The indicator identifies areas of high volatility at pivot highs and lows, plotting blocks that represent these zones. Green blocks represent support zones (identified at pivot lows), while blue blocks represent resistance zones (identified at pivot highs).
Support:
Resistance:
◉ Shadow Blocks after Breakouts:
When price breaks through a block, the block doesn't disappear. Instead, it leaves behind a shadow box, which can still influence future price action. These shadow blocks act as secondary support or resistance levels.
If the price crosses these shadow blocks, the block stops extending, and the right edge of the box is fixed at the point where the price crosses it. This feature helps traders monitor important price levels even after the initial breakout has occurred.
◉ Triangle Labels for Breakouts:
After the price breaks through a volatility block, the indicator prints triangle labels (up or down) at the breakout points.
◉ Support and Resistance Retests:
One of the key concepts in this indicator is the retesting of broken blocks. After breaking a resistance block, price often returns to the shadow box, which then acts as support. Similarly, after breaking a support block, price tends to return to the shadow box, which becomes a resistance level. This concept of price retesting and bouncing off these levels is essential for understanding how the indicator can be used to identify potential entries and exits.
The natural tendency of price to retest broken resistance or support levels.
Additionaly indicator can display retest signals of broken support or resistance
◉ Customizable Sensitivity:
The sensitivity of volatility detection can be adjusted in the settings. A higher sensitivity captures fewer but more significant breakouts, while a lower sensitivity captures more frequent volatility breakouts. This flexibility allows traders to adapt the indicator to different trading styles and market conditions.
🔵 CUSTOMIZATION
Calculation Window: Defines the window of bars over which the breaker blocks are calculated. A larger window will capture longer-term levels, while a smaller window focuses on more recent volatility areas.
Volatility Sensitivity: Adjusts the threshold for volatility detection. Lower sensitivity captures smaller breakouts, while higher sensitivity focuses on larger, more significant moves.
Retest Signals: Display or hide retest signals of shadow boxes
Volatility Projection Levels (VPL)### Indicator Name: **Volatility Projection Levels (VPL)**
### Description:
The **Volatility Projection Levels (VPL)** indicator is a powerful tool designed to help traders anticipate key support and resistance levels for the E-mini S&P 500 (ES) by leveraging the CBOE Volatility Index (^VIX). This indicator utilizes historical volatility data to project potential price movements for the upcoming month, offering clear visual cues that enhance swing trading strategies.
### Key Features:
- **Volatility-Based Projections**: The VPL indicator uses the previous month’s closing value of the VIX, normalizing it for monthly analysis by dividing by the square root of 12. This calculated percentage is then applied to the E-mini S&P 500’s closing price from the last day of the previous month.
- **Upper and Lower Projection Levels**: The indicator calculates two essential levels:
- **Upper Projection Level**: The previous month’s closing price of the E-mini S&P 500 plus the calculated volatility percentage.
- **Lower Projection Level**: The previous month’s closing price of the E-mini S&P 500 minus the calculated volatility percentage.
- **Continuous Visualization**: The VPL indicator plots these projection levels on the chart throughout the entire month, providing traders with a consistent reference for potential support and resistance zones. This continuous visualization allows for better anticipation of market movements.
- **Previous Month's Close Reference**: Additionally, the indicator plots the previous month’s closing price as a reference point, offering further context for current price action.
### Use Cases:
- **Swing Trading**: The VPL indicator is ideal for swing traders looking to exploit predicted price ranges within a monthly timeframe.
- **Support & Resistance Identification**: It aids traders in identifying critical levels where the market may encounter support or resistance, thus informing entry and exit decisions.
- **Risk Management**: By forecasting potential price levels, traders can set more strategic stop-loss and take-profit levels, enhancing risk management.
### Summary:
The **Volatility Projection Levels (VPL)** indicator equips traders with a forward-looking tool that incorporates volatility data into market analysis. By projecting key price levels based on historical VIX data, the VPL indicator enhances decision-making, helping traders anticipate market movements and optimize their trading strategies.
Made by Serpenttrading
Volatility Estimator - YZ & RSThe Yang-Zheng Volatility Estimator (YZVE) integrates both intra-candle and inter-candle dynamics, such as overnight and weekend price changes, offering a more detailed analysis compared to traditional methods. The YZVE is proposed to improve over the standard deviation by accounting for the open, high, low, and close prices of trading periods, instead of only the close prices, and attempts to supplant the Parkinson's Volatility Estimator (PVE) by a also capturing inter-candle dynamics. The YZVE is calculated by this formula:
YZ Volatility Squared σ_YZ² = k * σ_o² + σ_rs² + (1 - k) * σ_c²
where k is a weighting factor that adjusts the emphasis between the overnight and close-to-close components, popularly estimated as:
k = 0.34 / (1.34 + (N+1) / (N-1))
where N is the lookback period. Optionally, users may opt to override this calculation with a specified constant (off by default). Next, the
Overnight Volatility Squared σ_o² = (log(O_t / C_(t-1)))²
measures the volatility associated with overnight price changes, from the previous candle's closing price C_(t-1) to the current candle's opening price O_t. It captures the market's reaction to news and events that occur outside of regular trading hours to reflect risk associated with holding positions over non-trading hours and gaps.
Next, the The Rogers-Satchell Volatility Estimator (RSVE) serves as an intermediary step in the computation of YZVE. It aggregates the logarithmic ratios between high, low, open, and close prices within each trading period, focusing on intra-candle volatility without assuming zero inter-candle drift as commonly implicitly assumed in other volatility models:
Rogers-Satchell Volatility Squared σ_rs² = (log(H_t / C_t) * log(H_t / O_t)) + (log(L_t / C_t) * log(L_t / O_t))
Finally,
Close-to-Close Volatility Squared σ_c² = (log(C_t / C_(t-1)))²
measures the volatility from the close of one candle to the close of the next. It reflects the typical candle volatility, similar to naive standard deviation.
This script also includes an option for users to apply the simpler RS Volatility exclusively, focusing on intraday price movements. Additionally, it offers a choice for normalization between 0 and 1, turning the estimator into an oscillator for comparing current volatility to recent levels. Horizontal lines at user-defined levels are also available for clearer visualization. Both are off by default.
References:
Yang, D., & Zhang, Q. (2000). Drift-independent volatility estimation based on high, low, open, and close prices. The Journal of Business, 73(3), 477-491.
Rogers, L.C.G., & Satchell, S.E. (1991). Estimating variance from high, low and closing prices. Annals of Applied Probability, 1(4), 504-512.
L&S Volatility IndexOverview
L&S Volatility Index is a tool designed to helps traders identify overpriced or underpriced moments in the market and adjust their trading strategies accordingly.
Calculations
This tool calculates how far the price is from the 21-period simple moving average as a ratio of the average historical volatility calculated over the last 21 candles.
How It Works
A L&S Volatility Index with a value greater than 30% may indicate that the asset is overpriced or underpriced relative to its average price.
How To Use
If the L&S Volatility Index > 30, the asset is overpriced or underpriced. This means that there is a good probability of initiating a mean reversion.
If the L&S Volatility Index < 30, the asset is in a fair price region. This means that it is acceptable to buy or sell in that price region.
Where To Use
Mean Reversion Strategy
Breakout Strategy
What Makes it Original
There is already an indicator that use a normalized calculation and a different approach to calculate historical volatility, whereas this script calculation is non-normalized and historical volatility is calculated using Don Fishback's formula. All calculations are used as originally described.
Credits
The L&S Volatility Index indicator was originally written by L&S Educação Financeira.
Historical Volatility calculation is based on the book "Odds: The Key to 90% Winners" written by Don Fishback.
SFC Smart Money - VolatilityIn statistics, a normal distribution is a type of continuous probability distribution for a real-valued random variable. Normal distributions are important in statistics and are often used in the natural and social sciences to represent real-valued random variables whose distributions are not known.
The indicator provide a deep statistic for the specified period. It calculate the normal distribution of all candles in the particular period, in order to measure the volatility and the probabilities. Also it separate bull from bear candles and calculate the normal distribution of each group. The calculations are mode based on open-open data and high-low data.
Volatility
Volatility is a statistical measure of the dispersion of returns for a given security or market index. In most cases, the higher the volatility , the riskier the security. Volatility is often measured from either the standard deviation or variance between returns from that same security or market index.
Volatility often refers to the amount of uncertainty or risk related to the size of changes in a security's value. A higher volatility means that a security's value can potentially be spread out over a larger range of values. This means that the price of the security can change dramatically over a short time period in either direction. A lower volatility means that a security's value does not fluctuate dramatically, and tends to be more steady.
While variance captures the dispersion of returns around the mean of an asset in general, volatility is a measure of that variance bounded by a specific period of time. Thus, we can report daily volatility , weekly, monthly, or annualized volatility .
This statistic gives very accurate information how the price moved in the past and what are normal movements and spikes. From this information, a future actions can be taken.
For better understanding, all data is calculated in pips.
Features:
- Mean - Mean is the one we are most used to, i.e. the average.
- Median -Sometimes, the data set values can have a few values which are at the extreme ends, and this might cause the mean of the data set to portray an incorrect picture.
Thus, we use the median, which gives the middle value of the sorted data set.
- Mode - In a given dataset, the mode will be the number which is occurring the most.
- Max - Maximum volatility for a given range.
- Min - Minimum volatility for a given range.
- Standard Deviation - The standard deviation tells us how far the value deviates from the mean.
- Range - Range simply gives the difference between the min and max values of the data set.
- ATR - Average True Range measures volatility, taking into account any gaps in the price movement.
- Normal Distribution - The basic premise is that given a range of observations, it is found that most of the values center around the mean and within one standard deviation
away from the mean.
- Probability - probability of outcomes.
We all know that the banks and professional traders do not trade with charts, but with different statistical methods, math. models and macroeconomics. This statistical indicator shows one of these methods.
It is recommended to use the indicator on daily timeframe . It also works on other timeframes, for example 1H for intraday analysis.
For more information how the normal distribution works, please search in internet.
Volatility Weighted Moving AverageVolatility Weighted Moving Average (VAWMA) :
The Volatility Weighted Moving Average is a short and long term trend filter that weightes asset price buy "volatility significance" (percentages of total volatility over specified period) unlike that of the WMA which formulates an average based on the product of asset price and a deceding period significance . The result is a less noisy average which weights price based on its potential significance in trend, VAWMA tends to price when volatility is high and conversaly tends away from price when volatility is low.
Example :
As seen above the VAWMA tends to price more than both the SMA and EMA. The high volatility weightings allow for the VWMA to act as a potential trailing stop.
Dynamics :
- symbol volatility watchlist, change the ticker and corrosponding exchange to watch volatility over other markets.
The Amplifier - Two Day Historical Bitcoin Volatility PlotThe 3rd piece to the other two pieces to our CoT study. This is the Amplifier, which turns select signals into 'Super' Buys/Sells
The other two being the 'Bitcoin Insider CoT Delta', and the on chart Price indicator most will have, if no others the 'Hunt Bitcoin CoT Buy/Sell Signals' that will indicate the key signals, ave 4 a year on the chart as they occur.
Why Bother another CoT signal?
Its different & focused on the Insider's.
Performance -
This Indicator provided a
1. Signal 1 = 26th March 2019 = SUPER LONG at $4,500 that saw a near $14,000 run up
2. Signal 2 = 18th & 24th June 2019 = SHORT at the second & final level $11,700 after repeated attempts & failure in the $13K range, the mini Echo Bitcoin Bull of 2019
3. Signal 3 = 17th December 2019 = LONG $6,900, Bitcoin rallied to Mid $10,500's
4. Signal 4 = 18th Feb 2020 = SUPER SHORT from $9,700's to a final extreme Low of $3,000, calling the CV-19 collapse
5. Signal 5 = 17th March 2020 = LONG from $5,400 no closure point yet
6. Signal 6 = 29th June 2020 = SUPER LONG reiterate from $10,700 no closure sell signal yet
7. Signal 7 = 17th May 2020 = LONG another accumulate LONG with no sell signal yet generated at Post H&S's low of $33,000
Note - This indicator only commences March 2019, as Bitcoin futures were a recent introduction and needed to settle for 6 months in both use and data, no signals were meaningful prior & data was light.
What is Provided. - Please note the need to also add the Hunt Bitcoin Historical Volatility Indicator for full understanding.
We provide 3 things with the 3 indicators.
'Insider' indications from Largest players in the futures market.
1. Bitcoin Macro Buy Signals.
a) The Bitcoin Commitment of Traders results see us focus solely on Largest 4 Short Open Interest & Largest 4 Long Open Interest aspects of the CoT Release data.
When the difference - is tight, a kind of pinch, these have been great Buy signals in Bitcoin.
We call this difference the Delta & When Delta is 5% or less Bitcoin is a Buy.
2. Bitcoin Macro Sells.
a) A sell signal is Triggered in Bitcoin at any point the Largest 4 short OI > or = to 70
3. AMPLIFIER Trade signals 'Super' Longs or Shorts -
Extreme low volatility events leads to highly impulsive & volatile subsequent moves, if either of 1 or 2 above occur, combined with extreme low volatility
a 'Super Long' or 'SUPER SELL' is generated. In the case of the short side, given Bitcoins general expansive and MACRO Bull trend since inception, we seek an additional component
that is an extreme differential/Delta reading between 4 biggest Longs & Shorts OI.
Namely CoT Delta also must be > 47.5%
We also have a Cautionary level, where it is not necessarily a good idea to accumulate Bitcon, as a better opportunity lower may avail itself, see conditions below.
So the required logic explicitly stated below for all Signals.
1. Long - Hunt Bitcoin CoT Delta < or = 5
2. SUPER Long - Hunt Bitcoin CoT Delta < or = 5; and 2 Day Historical Bitcoin Volatility = or < 20
3. Short - Largest 4 Sellers OI = or > 70
4. SUPER Short - Largest 4 Sellers OI = or > 70; AND..
Hunt Bitcoin CoT Delta = or > 47.5 AND 2 Day Historical BTC Volatility = or < 20
5. Caution - Largest 4 Sellers OI = or > 67.5 AND Hunt Bitcoin CoT Delta = or > 45
WARNING SEE Notes Below
Note 1 - = Largest 4 Open Interest Shorts
Note 2 - = Largest 4 Open Interest Longs
Note 3 - = Hunt Cot Delta = (Largest 4 sellers OI) -( Largest 4 Buyers OI)
Caution = Avoid new Bitcoin Accumulation Right Now, A sell signal might follow Enter on next Long
Note 4 - The Hunt Bitcoin COT Delta signal is a Largest 'Insider' Tracking tool based on a segment of Commitment of Traders data on Bitcoin Futures, released once a week on a Friday.
It is a Macro Timeframe signal , and should not be used for Day trading and Short Timeframe analysis , Entries may be optimised after a Hunt Bitcoin CoT Signal is generated by separate shorter Timeframe analysis.
Note 5 - The Historical Bitcoin Volatility is an additional 'Amplifier' component to the 'Hunt Bitcoin Cot Delta' Insider Signal
Note 6 - The Historical Bitcoin Volatility criteria varies by timeframe, the above levels are those applying on a Two Day TF Chart, select this custom timeframe in Trading View.
if additional criteria are met for LONG & SHORT insider signals, they may become 'Super Longs/Shorts', see conditions box above.
Scalpius Trend & Decreasing VolatilityScalpius Trend & Decreasing Volatility
Identify trends and 'decreasing volatility' trends (strong trends)
Can be used on any market
Setup usually used for 3 timeframes e.g. 2 min, 5 min, 10 min
Contains 2 parts:
I) Trend Indicator
Trends can be defined in several ways,
this indicator defines a trend that uses statistally significant price behaviour that includes the use of the Bollinger Bands
II) Decreasing Volatility Indicator
Trends that are accompanied by decreasing volatility are statistically more likely to go further and longer,
this indicator shows you when 'Decreasing Volalitility Mode' is on and when it turns off using 'pivot highs' and Average True Range
Using this indicator you can filter your trades to 2 types of trades: trend trades and mean reversion trades
I) Trend indicator
-----------------------
Trend Mode ON:
1) A candle touching the Bollinger Band (default settings: length=20, standard deviation=2) (the Bollinger Candle)
2a) (uptrend) A follow-up candle with a higher high and a higher close than the Bollinger Candle
2b) (downtrend) A follow-up candle with a lower low and a lower close than the low of the Bollinger Candle
Examples Trend Mode ON:
Uptrend
Downtrend
Trend Mode OFF when:
1) Price touches the opposite Bollinger Band
2) 20 candles without new high or low
3a) (uptrend) price closes consecutively below 2 EMA's (8 EMA & 21 EMA), above and below again, without making new trend highs
3b) (downternd) price closes consecutively above 2 EMA's (8 EMA & 21 EMA), below and above again, without making new trend lows
Examples Trend Mode OFF:
Uptrend ends because of opposite Bollinger Band touch:
Uptrend ends because of 20 candles without new high:
Uptrend ends because of price consecutively close below, above, below EMA 8 and EMA 21:
Downtrend ends because of opposite Bollinger Band touch:
Downtrend ends because of 20 candles without new low:
Downtrend ends because of price consecutively close above, below, above EMA 8 and EMA 21:
II) Decreasing Volatility Indicator
Decreasing Volatility Mode ON:
1) Trend Mode must be ON
2) Highest or lowest close in the trend must happen on a DOWNTICK in ATR (Average True Range, default setting=14)
Decreasing Volatility Mode OFF:
1) New ATR high in the trend
2) Breaking the pattern of lower lows and lower highs in ATR, aka 'pivot high' or '2 pivot high'
Examples DV Mode ON:
In an uptrend:
In a downtremd:
Examples DV Mode OFF:
In an uptrend:
In a downtremd:
If trend stops, DV Mode stays ON until DV OFF signal comes
[astropark] Volatility IndicatorDear Followers,
today another interesting script: Volatility Indicator .
This indicator measures the volatility of the market you see in the timeframe you see, in a scale between 0 and 1.
It works on cryptocurrencies, commodities, stocks, indexes and forex.
You will see 2 volatility waves:
a black one (with green and blue shadow for increasing and decreasing mode), which is the "faster" one
a red one (with orange and purple shadow for increasing and decreasing mode), which is the "slower" one
The indicator highlights high volatility when it's near the top (1), while low volatility when near the bottom (0).
You can combine this indicator with your own strategy and indicators to validate them :
on low volatility it often happens that a signal fails to be profitable, as it lacks fuel
while it's better if volatility is over low level as price has more room to run while volatility increasing to the top
This indicator also lets you set alerts when volatility exceeds high level or low level.
This is a premium indicator , so send me a private message in order to get access to this script.
