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.
Volatilityindicator
EMA 12/26 With ATR Volatility StoplossThe EMA 12/26 With ATR Volatility Stoploss
The EMA 12/26 With ATR Volatility Stoploss strategy is a meticulously designed systematic trading approach tailored for navigating financial markets through technical analysis. By integrating the Exponential Moving Average (EMA) and Average True Range (ATR) indicators, the strategy aims to identify optimal entry and exit points for trades while prioritizing disciplined risk management. At its core, it is a trend-following system that seeks to capitalize on price momentum, employing volatility-adjusted stop-loss mechanisms and dynamic position sizing to align with predefined risk parameters. Additionally, it offers traders the flexibility to manage profits either by compounding returns or preserving initial capital, making it adaptable to diverse trading philosophies. This essay provides a comprehensive exploration of the strategy’s underlying concepts, key components, strengths, limitations, and practical applications, without delving into its technical code.
=====
Core Philosophy and Objectives
The EMA 12/26 With ATR Volatility Stoploss strategy is built on the premise of capturing short- to medium-term price trends with a high degree of automation and consistency. It leverages the crossover of two EMAs—a fast EMA (12-period) and a slow EMA (26-period)—to generate buy and sell signals, which indicate potential trend reversals or continuations. To mitigate the inherent risks of trading, the strategy incorporates the ATR indicator to set stop-loss levels that adapt to market volatility, ensuring that losses remain within acceptable bounds. Furthermore, it calculates position sizes based on a user-defined risk percentage, safeguarding capital while optimizing trade exposure.
A distinctive feature of the strategy is its dual profit management modes:
SnowBall (Compound Profit): Profits from successful trades are reinvested into the capital base, allowing for progressively larger position sizes and potential exponential portfolio growth.
ZeroRisk (Fixed Equity): Profits are withdrawn, and trades are executed using only the initial capital, prioritizing capital preservation and minimizing exposure to market downturns.
This duality caters to both aggressive traders seeking growth and conservative traders focused on stability, positioning the strategy as a versatile tool for various market environments.
=====
Key Components of the Strategy
1. EMA-Based Signal Generation
The strategy’s trend-following mechanism hinges on the interaction between the Fast EMA (12-period) and Slow EMA (26-period). EMAs are preferred over simple moving averages because they assign greater weight to recent price data, enabling quicker responses to market shifts. The key signals are:
Buy Signal: Triggered when the Fast EMA crosses above the Slow EMA, suggesting the onset of an uptrend or bullish momentum.
Sell Signal: Occurs when the Fast EMA crosses below the Slow EMA, indicating a potential downtrend or the end of a bullish phase.
To enhance signal reliability, the strategy employs an Anchor Point EMA (AP EMA), a short-period EMA (e.g., 2 days) that smooths the input price data before calculating the primary EMAs. This preprocessing reduces noise from short-term price fluctuations, improving the accuracy of trend detection. Additionally, users can opt for a Consolidated EMA (e.g., 18-period) to display a single trend line instead of both EMAs, simplifying chart analysis while retaining trend insights.
=====
2. Volatility-Adjusted Risk Management with ATR
Risk management is a cornerstone of the strategy, achieved through the use of the Average True Range (ATR), which quantifies market volatility by measuring the average price range over a specified period (e.g., 10 days). The ATR informs the placement of stop-loss levels, which are set at a multiple of the ATR (e.g., 2x ATR) below the entry price for long positions. This approach ensures that stop losses are proportionate to current market conditions—wider during high volatility to avoid premature exits, and narrower during low volatility to protect profits.
For example, if a stock’s ATR is $1 and the multiplier is 2, the stop loss for a buy at $100 would be set at $98. This dynamic adjustment enhances the strategy’s adaptability, preventing stop-outs from normal market noise while capping potential losses.
=====
3. Dynamic Position Sizing
The strategy calculates position sizes to align with a user-defined Risk Per Trade, typically expressed as a percentage of capital (e.g., 2%). The position size is determined by:
The available capital, which varies depending on whether SnowBall or ZeroRisk mode is selected.
The distance between the entry price and the ATR-based stop-loss level, which represents the per-unit risk.
The desired risk percentage, ensuring that the maximum loss per trade does not exceed the specified threshold.
For instance, with a $1,000 capital, a 2% risk per trade ($20), and a stop-loss distance equivalent to 5% of the entry price, the strategy computes the number of units (shares or contracts) to ensure the total loss, if the stop loss is hit, equals $20. To prevent over-leveraging, the strategy includes checks to ensure that the position’s dollar value does not exceed available capital. If it does, the position size is scaled down to fit within the capital constraints, maintaining financial discipline.
=====
4. Flexible Capital Management
The strategy’s dual profit management modes—SnowBall and ZeroRisk—offer traders strategic flexibility:
SnowBall Mode: By compounding profits, traders can increase their capital base, leading to larger position sizes over time. This is ideal for those with a long-term growth mindset, as it harnesses the power of exponential returns.
ZeroRisk Mode: By withdrawing profits and trading solely with the initial capital, traders protect their gains and limit exposure to market volatility. This conservative approach suits those prioritizing stability over aggressive growth.
These options allow traders to tailor the strategy to their risk tolerance, financial goals, and market outlook, enhancing its applicability across different trading styles.
=====
5. Time-Based Trade Filtering
To optimize performance and relevance, the strategy includes an option to restrict trading to a specific time range (e.g., from 2018 onward). This feature enables traders to focus on periods with favorable market conditions, avoid historically volatile or unreliable data, or align the strategy with their backtesting objectives. By confining trades to a defined timeframe, the strategy ensures that performance metrics reflect the intended market context.
=====
Strengths of the Strategy
The EMA 12/26 With ATR Volatility Stoploss strategy offers several compelling advantages:
Systematic and Objective: By adhering to predefined rules, the strategy eliminates emotional biases, ensuring consistent execution across market conditions.
Robust Risk Controls: The combination of ATR-based stop losses and risk-based position sizing caps losses at user-defined levels, fostering capital preservation.
Customizability: Traders can adjust parameters such as EMA periods, ATR multipliers, and risk percentages, tailoring the strategy to specific markets or preferences.
Volatility Adaptation: Stop losses that scale with market volatility enhance the strategy’s resilience, accommodating both calm and turbulent market phases.
Enhanced Visualization: The use of color-coded EMAs (green for bullish, red for bearish) and background shading provides intuitive visual cues, simplifying trend and trade status identification.
=====
Limitations and Considerations
Despite its strengths, the strategy has inherent limitations that traders must address:
False Signals in Range-Bound Markets: EMA crossovers may generate misleading signals in sideways or choppy markets, leading to whipsaws and unprofitable trades.
Signal Lag: As lagging indicators, EMAs may delay entry or exit signals, causing traders to miss rapid trend shifts or enter trades late.
Overfitting Risk: Excessive optimization of parameters to fit historical data can impair the strategy’s performance in live markets, as past patterns may not persist.
Impact of High Volatility: In extremely volatile markets, wider stop losses may result in larger losses than anticipated, challenging risk management assumptions.
Data Reliability: The strategy’s effectiveness depends on accurate, continuous price data, and discrepancies or gaps can undermine signal accuracy.
=====
Practical Applications
The EMA 12/26 With ATR Volatility Stoploss strategy is versatile, applicable to diverse markets such as stocks, forex, commodities, and cryptocurrencies, particularly in trending environments. To maximize its potential, traders should adopt a rigorous implementation process:
Backtesting: Evaluate the strategy’s historical performance across various market conditions to assess its robustness and identify optimal parameter settings.
Forward Testing: Deploy the strategy in a demo account to validate its real-time performance, ensuring it aligns with live market dynamics before risking capital.
Ongoing Monitoring: Continuously track trade outcomes, analyze performance metrics, and refine parameters to adapt to evolving market conditions.
Additionally, traders should consider market-specific factors, such as liquidity and volatility, when applying the strategy. For instance, highly liquid markets like forex may require tighter ATR multipliers, while less liquid markets like small-cap stocks may benefit from wider stop losses.
=====
Conclusion
The EMA 12/26 With ATR Volatility Stoploss strategy is a sophisticated, systematic trading framework that blends trend-following precision with disciplined risk management. By leveraging EMA crossovers for signal generation, ATR-based stop losses for volatility adjustment, and dynamic position sizing for risk control, it offers a balanced approach to capturing market trends while safeguarding capital. Its flexibility—evident in customizable parameters and dual profit management modes—makes it suitable for traders with varying risk appetites and objectives. However, its limitations, such as susceptibility to false signals and signal lag, necessitate thorough testing and prudent application. Through rigorous backtesting, forward testing, and continuous refinement, traders can harness this strategy to achieve consistent, risk-adjusted returns in trending markets, establishing it as a valuable tool in the arsenal of systematic trading.
Exponential Trend [AlgoAlpha]OVERVIEW
This script plots an adaptive exponential trend system that initiates from a dynamic anchor and accelerates based on time and direction. Unlike standard moving averages or trailing stops, the trend line here doesn't follow price directly—it expands exponentially from a pivot determined by a modified Supertrend logic. The result is a non-linear trend curve that starts at a specific price level and accelerates outward, allowing traders to visually assess trend strength, persistence, and early-stage reversal points through both base and volatility-adjusted extensions.
CONCEPTS
This indicator builds on the idea that trend-following tools often need dynamic, non-static expansion to reflect real market behavior. It uses a simplified Supertrend mechanism to define directional context and anchor levels, then applies an exponential growth function to simulate trend acceleration over time. The exponential growth is unidirectional and resets only when the direction flips, preserving trend memory. This method helps avoid whipsaws and adds time-weighted confirmation to trends. A volatility buffer—derived from ATR and modifiable by a width multiplier—adds a second layer to indicate zones of risk around the main trend path.
FEATURES
Exponential Trend Logic : Once a directional anchor is set, the base trend line accelerates using an exponential formula tied to elapsed bars, making the trend stronger the longer it persists.
Volatility-Adjusted Extension : A secondary band is plotted above or below the base trend line, widened by ATR to visualize volatility zones, act as soft stop regions or as a better entry point (Dynamic Support/Resistance).
Color-Coded Visualization : Clear green/red base and extension lines with shaded fills indicate trend direction and confidence levels.
Signal Markers & Alerts : Triangle markers indicate confirmed trend reversals. Built-in alerts notify users of bullish or bearish direction changes in real-time.
USAGE
Use this script to identify strong trends early, visually measure their momentum over time, and determine safe areas for entries or exits. Start by adjusting the *Exponential Rate* to control how quickly the trend expands—the higher the rate, the more aggressive the curve. The *Initial Distance* sets how far the anchor band is placed from price initially, helping filter out noise. Increase the *Width Multiplier* to widen the volatility zone for more conservative entries or exits. When the price crosses above or below the base line, a new trend is assumed and the exponential projection restarts from the new anchor. The base trend and its extension both shift over time, but only reset on a confirmed reversal. This makes the tool especially useful for momentum continuation setups or trailing stop logic in trending markets.
Normalized FX Weighted Daily % Change vs DXYThis indicator tracks international liquidity flows by measuring the USD’s relative strength against major currencies—EUR, CNY, JPY, GBP, and CAD. It calculates the weighted percentage change of each pair over a specified interval. A positive reading means the USD is weakening (liquidity flowing out of the US), while a negative reading indicates the USD is strengthening (liquidity flowing in). Additionally, the indicator incorporates the DXY index and VIX, with all components normalized using Z-scores for clear, comparable insights into market dynamics.
Hourly Volatility Explorer📊 Hourly Volatility Explorer: Master The Market's Pulse
Unlock the hidden rhythms of price action with this sophisticated volatility analysis tool. The Hourly Volatility Explorer reveals the most potent trading hours across multiple time zones, giving you a strategic edge in timing your trades.
🌟 Key Features:
⏰ Multi-Timezone Analysis
• GMT (UTC+0)
• EST (UTC-5) - New York
• BST (UTC+1) - London
• JST (UTC+9) - Tokyo
• AEST (UTC+10) - Sydney
Perfect for tracking major market sessions and their overlaps!
📈 Dynamic Visualization
• Color-gradient hourly bars for instant pattern recognition
• Real-time volatility comparison
• Interactive data table with comprehensive statistics
• Automatic highlighting of peak volatility periods
🎯 Strategic Applications:
Day Trading:
• Identify optimal trading windows
• Avoid low-liquidity periods
• Capitalize on session overlaps
• Fine-tune entry/exit timing
Risk Management:
• Set appropriate stop losses based on hourly volatility
• Adjust position sizes for different market hours
• Optimize risk-reward ratios
• Plan around high-impact hours
Global Market Analysis:
• Track volatility across all major sessions
• Spot institutional trading patterns
• Identify quiet vs. active periods
• Monitor 24/7 market dynamics
💡 Perfect For:
• Forex traders navigating global sessions
• Crypto traders in 24/7 markets
• Day traders optimizing execution times
• Algorithmic traders fine-tuning strategies
• Risk managers calibrating exposure
📊 Advanced Features:
• Rolling 3-month analysis for reliable patterns
• Precise pip movement calculations
• Sample size tracking for statistical validity
• Real-time current hour comparison
• Color-coded visual system for instant insights
⚡ Pro Trading Tips:
• Use during major session overlaps for maximum opportunity
• Compare patterns across different instruments
• Combine with volume analysis for deeper insights
• Track seasonal variations in hourly patterns
• Build trading schedules around peak hours
🎓 Educational Value:
• Understand market microstructure
• Learn global market dynamics
• Master timezone relationships
• Develop timing intuition
🛠️ Customization:
• Adjustable lookback period
• Flexible pip multiplier
• Multiple timezone options
• Visual preference settings
Whether you're scalping the 1-minute chart or managing longer-term positions, the Hourly Volatility Explorer provides the precise timing intelligence needed for today's global markets.
Transform your trading schedule from guesswork to science. Know exactly when markets move, why they move, and how to position yourself for maximum opportunity.
#TechnicalAnalysis #Trading #Volatility #MarketTiming #DayTrading #Forex #Crypto #TradingView #PineScript #MarketAnalysis #TradingStrategy #RiskManagement #GlobalMarkets #FinancialMarkets #TradingTools #MarketStructure #PriceAction #Scalping #SwingTrading #AlgoTrading
BTC-USDT Liquidity Trend [Ajit Pandit]his script helps traders visualize trend direction and identify liquidity zones where price might react due to past pivot levels. The color-coded candles and extended pivot lines make it easier to spot support/resistance levels and potential breakout points.
Key Features:
1. Trend Detection Using EMA
Uses two EMA calculations to determine the trend:
emaValue: Standard EMA based on length1
correction: Adjusted price movement relative to EMA
Trend: Another EMA of the corrected value
Determines bullish (signalUp) and bearish (signalDn) signals when Trend crosses emaValue.
2. Candlestick Coloring Based on Trend
Candlesticks are colored:
Uptrend → Blue (up color)
Downtrend → Pink (dn color)
Neutral → No color
3. Liquidity Zones (Pivot Highs & Lows)
Identifies pivot highs and lows using a customizable pivot length.
Draws liquidity lines:
High pivot lines (Blue, adjustable width)
Low pivot lines (Pink, adjustable width)
Extends lines indefinitely until price breaks above/below the level.
Removes broken pivot levels dynamically.
Trendchange Zones Indicator | iSolani
Spotting Reversals Before They Happen: The iSolani Trendshift System
Where RSI Meets Smart Volume Analysis - Your Visual Guide to Market Turns
Core Methodology
RSI-Powered Zones
Identifies critical levels using:
14-period RSI (default) with 70/30 thresholds
Semi-transparent boxes marking overbought (red) and oversold (green) territories
Zone persistence until RSI returns to neutral range
Dynamic Level Tracking
Plots evolving support/resistance using:
Pivot highs/lows with 15-bar lookback (default)
Auto-extending lines that adapt to new price extremes
Volume-Confirmed Breakouts
Flags significant moves with:
5/10 EMA volume oscillator
20% volume threshold (default) for confirmation
Technical Innovation
Three-Layer Confirmation
Unique combination of:
Classic RSI extremes
Price structure through pivot points
Volume-fueled momentum shifts
Adaptive Visualization
Zones maintain historical context at 33% transparency
Dynamic lines extend indefinitely until invalidated
Discreet labels for breakout events
System Workflow
Calculates RSI values in real-time
Draws colored zones when RSI crosses 70/30
Marks pivot points every 15 bars (default)
Updates support/resistance lines on new pivots
Triggers alerts when price breaks levels with volume confirmation
Standard Configuration
RSI Settings : 14-period length
Pivot Detection : 15-bar left/right lookback
Visuals : 33% transparency zones with thin borders
Volume Threshold : 20% oscillator difference
Alerts : Breakout signals with "B" labels
This system transforms the classic RSI into a spatial analysis tool - not just showing when markets are overextended, but where they're likely to reverse. The dynamic lines act as moving barriers that adapt to market structure, while the volume filter ensures only high-conviction breaks get flagged. By layering momentum, price action, and volume dynamics, it creates a multi-spectrum view of potential trend changes.
Volatility with Sigma BandsOverview
The Volatility Analysis with Sigma Bands indicator is a powerful and flexible tool designed for traders who want to gain deeper insights into market price fluctuations. It calculates historical volatility within a user-defined time range and displays ±1σ, ±2σ, and ±3σ standard deviation bands, helping traders identify potential support, resistance levels, and extreme price behaviors.
Key Features
Multiple Volatility Band Displays:
±1σ Range (Yellow line): Covers approximately 68% of price fluctuations.
±2σ Range (Blue line): Covers approximately 95% of price fluctuations.
±3σ Range (Fuchsia line): Covers approximately 99% of price fluctuations.
Dynamic Probability Mode:
Toggle between standard normal distribution probabilities (68.2%, 95.4%, 99.7%) and actual historical probability calculations, allowing for more accurate analysis tailored to varying market conditions.
Highly Customizable Label Display:
The label shows:
Real-time volatility
Annualized volatility
Current price
Price ranges for each σ level
Users can adjust the label’s position and horizontal offset to prevent it from overlapping key price areas.
Real-Time Calculation & Visualization:
The indicator updates in real-time based on the selected time range and current market data, making it suitable for day trading, swing trading, and long-term trend analysis.
Use Cases
Risk Management:
Understand the distribution probabilities of price within different standard deviation bands to set more effective stop-loss and take-profit levels.
Trend Confirmation:
Determine trend strength or spot potential reversals by observing whether the price breaks above or below ±1σ or ±2σ ranges.
Market Sentiment Analysis:
Price movement beyond the ±3σ range often indicates extreme market sentiment, providing potential reversal opportunities.
Backtesting and Historical Analysis:
Utilize the customizable time range feature to backtest volatility during various periods, providing valuable insights for strategy refinement.
The Volatility Analysis with Sigma Bands indicator is an essential tool for traders seeking to understand market volatility patterns. Whether you're a day trader looking for precise entry and exit points or a long-term investor analyzing market behavior, this indicator provides deep insights into volatility dynamics, helping you make more confident trading decisions.
Position resetThe "Position Reset" indicator
The Position Reset indicator is a sophisticated technical analysis tool designed to identify possible entry points into short positions based on an analysis of market volatility and the behavior of various groups of bidders. The main purpose of this indicator is to provide traders with information about the current state of the market and help them decide whether to open short positions depending on the level of volatility and the mood of the main players.
The main components of the indicator:
1. Parameters for the RSI (Relative Strength Index):
The indicator uses two sets of parameters to calculate the RSI: one for bankers ("Banker"), the other for hot money ("Hot Money").
RSI for Bankers:
RSIBaseBanker: The baseline for calculating bankers' RSI. The default value is 50.
RSIPeriodBanker: The period for calculating the RSI for bankers. The default period is 14.
RSI for hot money:
RSIBaseHotMoney: The baseline for calculating the RSI of hot money. The default value is 30.
RSIPeriodHotMoney: The period for calculating the RSI for hot money. The default period is 21.
These parameters allow you to adjust the sensitivity of the indicator to the actions of different groups of market participants.
2. Sensitivity:
Sensitivity determines how strongly changes in the RSI will affect the final result of calculations. It is configured separately for bankers and hot money:
SensitivityBanker: Sensitivity for bankers' RSI. It is set to 2.0 by default.
SensitivityHotMoney: Sensitivity for hot money RSI. It is set to 1.0 by default.
Changing these parameters allows you to adapt the indicator to different market conditions and trader preferences.
3. Volatility Analysis:
Volatility is measured based on the length of the period, which is set by the volLength parameter. The default length is 30 candles. The indicator calculates the difference between the highest and lowest value for the specified period and divides this difference by the lowest value, thus obtaining the volatility coefficient.
Based on this coefficient, four levels of volatility are distinguished.:
Extreme volatility: The coefficient is greater than or equal to 0.25.
High volatility: The coefficient ranges from 0.125 to 0.2499.
Normal volatility: The coefficient ranges from 0.05 to 0.1249.
Low volatility: The coefficient is less than 0.0499.
Each level of volatility has its own significance for making decisions about entering a position.
4. Calculation functions:
The indicator uses several functions to process the RSI and volatility data.:
rsi_function: This function applies to every type of RSI (bankers and hot money). It adjusts the RSI value according to the set sensitivity and baseline, limiting the range of values from 0 to 20.
Moving Averages: Simple moving averages (SMA), exponential moving averages (EMA), and weighted moving averages (RMA) are used to smooth fluctuations. They are applied to different time intervals to obtain the average values of the RSI.
Thus, the indicator creates a comprehensive picture of market behavior, taking into account both short-term and long-term dynamics.
5. Bearish signals:
Bearish signals are considered situations when the RSI crosses certain levels simultaneously with a drop in indicators for both types of market participants (bankers and hot money).:
The bankers' RSI crossing is below the level of 8.5.
The current hot money RSI is less than 18.
The moving averages for banks and hot money are below their signal lines.
The RSI values for bankers are less than 5.
These conditions indicate a possible beginning of a downtrend.
6. Signal generation:
Depending on the current level of volatility and the presence of bearish signals, the indicator generates three types of signals:
Orange circle: Extremely high volatility and the presence of a bearish signal.
Yellow circle: High volatility and the presence of a bearish signal.
Green circle: Low volatility and the presence of a bearish signal.
These visual markers help the trader to quickly understand what level of risk accompanies each specific signal.
7. Notifications:
The indicator supports the function of sending notifications when one of the three types of signals occurs. The notification contains a brief description of the conditions under which the signal was generated, which allows the trader to respond promptly to a change in the market situation.
Advantages of using the "Position Reset" indicator:
Multi-level analysis: The indicator combines technical analysis (RSI) and volatility assessment, providing a comprehensive view of the current market situation.
Flexibility of settings: The ability to adjust the sensitivity parameters and the RSI baselines allows you to adapt the indicator to any market conditions and personal preferences of the trader.
Clear visualization: The use of colored labels on the chart simplifies the perception of information and helps to quickly identify key points for entering a trade.
Notification support: The notification sending feature makes it much easier to monitor the market, allowing you to respond to important events in time.
Choppiness IndexThis Pine Script v6 indicator calculates the Choppiness Index over a user-defined length and segments it based on user-defined thresholds for choppy and trending market conditions. The indicator allows users to toggle the visibility of choppy, trending, and neutral segments using checkboxes.
Here's how it works:
Inputs: Users can set the length for the Choppiness Index calculation and thresholds for choppy and trending conditions. They can also choose which segments to display.
Choppiness Index Calculation: The script calculates the Choppiness Index using the ATR and the highest-high and lowest-low over the specified length.
Segment Determination: The script determines which segment the current Choppiness Index value falls into based on the thresholds. The color changes exactly at the threshold values.
Dynamic Plotting: The Choppiness Index is plotted with a color that changes based on the segment. The plot is only visible if the segment is "turned on" by the user.
Threshold Lines: Dashed horizontal lines are plotted at the choppy and trending thresholds for reference.
This indicator helps traders visualize market conditions and identify potential transitions between choppy and trending phases, with precise color changes at the threshold values.
RSI Volatility Suppression Zones [BigBeluga]RSI Volatility Suppression Zones is an advanced indicator that identifies periods of suppressed RSI volatility and visualizes these suppression zones on the main chart. It also highlights breakout dynamics, giving traders actionable insights into potential market momentum.
🔵 Key Features:
Detection of Suppression Zones:
Identifies periods where RSI volatility is suppressed and marks these zones on the main price chart.
Breakout Visualization:
When the price breaks above the suppression zone, the box turns aqua, and an upward label is drawn to indicate a bullish breakout.
If the price breaks below the zone, the box turns purple, and a downward label is drawn for a bearish breakout.
Breakouts accompanied by a "+" label represent strong moves caused by short-lived, tight zones, signaling significant momentum.
Wave Labels for Consolidation:
If the suppression zone remains unbroken, a "wave" label is displayed within the gray box, signifying continued price stability within the range.
Gradient Intensity Below RSI:
A gradient strip below the RSI line increases in intensity based on the duration of the suppressed RSI volatility period.
This visual aid helps traders gauge how extended the low volatility phase is.
🔵 Usage:
Identify Breakouts: Use color-coded boxes and labels to detect breakouts and their direction, confirming potential trend continuation or reversals.
Evaluate Market Momentum: Leverage "+" labels for strong breakout signals caused by short suppression phases, indicating significant market moves.
Monitor Price Consolidation: Observe gray boxes and wave labels to understand ongoing consolidation phases.
Analyze RSI Behavior: Utilize the gradient strip to measure the longevity of suppressed volatility phases and anticipate breakout potential.
RSI Volatility Suppression Zones provides a powerful visual representation of RSI volatility suppression, breakout signals, and price consolidation, making it a must-have tool for traders seeking to anticipate market movements effectively.
Volatility Footprint CandlesVolatility Footprint is an innovative volume profile indicator that dynamically adapts to real-time market conditions, providing traders with a powerful tool to visualize and interpret market structure, order flow, and potential areas of support and resistance.
At its core, Volatility Footprint combines the concepts of market profile, volume analysis, and volatility measurement to create a unique and adaptive charting experience. The indicator intelligently adjusts its display based on the current market volatility, ensuring that traders always have a clear and readable chart, regardless of the instrument or timeframe they are analyzing.
The footprint chart is composed of a series of color-coded boxes, each representing a specific price level. The color of the box indicates whether there is a net buying or selling pressure at that level, while the opacity reflects the relative strength of the volume. This intuitive visualization allows traders to quickly identify areas of high and low volume, as well as potential imbalances in order flow.
In addition to the individual box volumes, Volatility Footprint also calculates and displays the cumulative volume delta. This running total of buy and sell volumes across all price levels provides valuable insight into the overall market sentiment and potential trends.
One of the key features of Volatility Footprint is its ability to identify and highlight the Point of Control (POC). The POC represents the price level with the highest volume concentration and serves as a key reference point for potential support or resistance. By drawing attention to this crucial level, the indicator helps traders make more informed decisions about potential entry and exit points.
Volatility Footprint is designed to be highly customizable, allowing traders to tailor the appearance of the footprint chart to their specific preferences. Users can easily modify the colors, opacity, and size of the boxes, labels, and POC marker to enhance readability and clarity.
The indicator's versatility makes it suitable for a wide range of trading styles and strategies. Whether you are a scalper looking for short-term opportunities or a swing trader aiming to identify potential trend reversals, Volatility Footprint can provide valuable insights into market dynamics.
By combining Volatility Footprint with other forms of analysis, such as price action, key levels, and technical indicators, traders can gain a more comprehensive understanding of market behavior and make better-informed trading decisions.
Volatility Footprint's adaptive approach to volume profile analysis sets it apart from traditional fixed-resolution volume profile indicators. By dynamically adjusting to the unique characteristics of each instrument and timeframe, the indicator ensures that traders always have a clear and meaningful representation of market structure and order flow.
Volatility Footprint is a powerful tool that traders can incorporate into their market analysis and decision-making process. By providing a dynamic, visual representation of volume and order flow at different price levels, this indicator offers valuable insights into market structure, sentiment, and potential areas of support and resistance. Let's explore how traders might effectively utilize Volatility Footprint in their trading approach.
1. Identifying Key Levels:
One of the primary uses of Volatility Footprint is to identify key price levels where significant trading activity has occurred. The color-coded boxes allow traders to quickly spot areas of high volume concentration, which may indicate potential support or resistance zones. For example, if a trader notices a cluster of boxes with high opacity at a specific price level, they may interpret this as a strong support or resistance area, depending on the prevailing market context. By paying attention to these key levels, traders can make more informed decisions about potential entry and exit points, as well as placement of stop-loss orders and profit targets.
2. Assessing Market Sentiment:
The cumulative volume delta feature of Volatility Footprint provides traders with a valuable gauge of overall market sentiment. By analyzing the running total of buy and sell volumes across all price levels, traders can gain insight into the dominant market forces at play. If the cumulative delta is significantly positive, it may suggest a bullish sentiment, as buying pressure has been consistently outpacing selling pressure. Conversely, a negative cumulative delta may indicate a bearish sentiment. Traders can use this information to confirm or question their bias and adjust their trading plan accordingly.
3. Confirming Breakouts and Trend Reversals:
Volatility Footprint can be particularly useful in confirming the strength and validity of breakouts and potential trend reversals. When a price level is breached, traders can refer to the footprint chart to assess the volume and order flow characteristics around that level. If the breakout is accompanied by a surge in volume and a clear imbalance between buying and selling pressure, it may suggest a strong and sustainable move. On the other hand, if the volume is relatively low or evenly distributed, the breakout may be less reliable. By using Volatility Footprint to confirm breakouts, traders can make more informed decisions about whether to enter or exit a trade, or to adjust their position size.
4. Detecting Imbalances and Potential Reversals:
Imbalances between buying and selling pressure at specific price levels can often precede significant market moves or reversals. Volatility Footprint makes it easy for traders to spot these imbalances visually. For instance, if a trader observes a price level with a significantly larger number of sell boxes compared to buy boxes, it may indicate a potential exhaustion point for a bullish trend, and a reversal might be imminent. Traders can use this information in conjunction with other technical analysis tools, such as trendlines, moving averages, or momentum oscillators, to identify high-probability trading opportunities.
5. Adapting to Market Conditions:
One of the key strengths of Volatility Footprint is its ability to dynamically adapt to the unique volatility characteristics of different instruments and timeframes. This adaptability ensures that the indicator remains relevant and informative across a wide range of market conditions. Traders can use Volatility Footprint to gauge the relative volatility and volume of a particular instrument or timeframe, and adjust their trading approach accordingly. For example, in a highly volatile market, traders may opt for wider stop-loss levels and smaller position sizes to account for the increased risk.
Incorporating Volatility Footprint into a trading strategy requires a combination of technical analysis, market understanding, and risk management. Traders should use this indicator as part of a comprehensive approach, combining it with other forms of analysis, such as price action, key levels, and technical indicators. By doing so, traders can gain a more complete picture of market dynamics and make better-informed trading decisions.
It's important to note that while Volatility Footprint provides valuable insights, it should not be relied upon as a standalone trading signal. Traders should always consider the broader market context, their risk tolerance, and their overall trading plan when making decisions based on the information provided by this indicator.
In conclusion, Volatility Footprint offers traders a dynamic and visually intuitive way to analyze market structure, volume, and order flow. By identifying key levels, assessing market sentiment, confirming breakouts, detecting imbalances, and adapting to market conditions, traders can leverage this powerful tool to make more informed and confident trading decisions. As with any technical analysis tool, Volatility Footprint should be used in conjunction with sound risk management principles and a well-defined trading strategy to maximize its effectiveness.
HV-RV Oscillator by DINVESTORQ(PRABIR DAS)Description:
The HV-RV Oscillator is a powerful tool designed to help traders track and compare two types of volatility measures: Historical Volatility (HV) and Realized Volatility (RV). This indicator is useful for identifying periods of market volatility and can be employed in various trading strategies. It plots both volatility measures on a normalized scale (0 to 100) to allow easy comparison and analysis.
How It Works:
Historical Volatility (HV):
HV is calculated by taking the log returns of the closing prices and finding the standard deviation over a specified period (default is 14 periods).
The value is then annualized assuming 252 trading days in a year.
Realized Volatility (RV):
RV is based on the True Range, which is the maximum of the current high-low range, the difference between the high and the previous close, and the difference between the low and the previous close.
Like HV, the standard deviation of the True Range over a specified period is calculated and annualized.
Normalization:
Both HV and RV values are normalized to a 0-100 scale, making it easy to see their relative magnitude over time.
The highest and lowest values within the period are used to normalize the data, which smooths out short-term volatility spikes.
Smoothing:
The normalized values of both HV and RV are then smoothed using a Simple Moving Average (SMA) to reduce noise and provide a clearer trend.
Crossover Signals:
Buy Signal : When the Normalized HV crosses above the Normalized RV, it indicates that the historical volatility is increasing relative to the realized volatility, which could be interpreted as a buy signal.
Sell Signal : When the Normalized HV crosses below the Normalized RV, it suggests that the historical volatility is decreasing relative to the realized volatility, which could be seen as a sell signal.
Features:
Two Volatility Lines: The blue line represents Normalized HV, and the orange line represents Normalized RV.
Neutral Line: A gray dashed line at the 50 level indicates a neutral state between the two volatility measures.
Buy/Sell Markers: Green upward arrows are shown when the Normalized HV crosses above the Normalized RV, and red downward arrows appear when the Normalized HV crosses below the Normalized RV.
Inputs:
HV Period: The number of periods used to calculate Historical Volatility (default = 14).
RV Period: The number of periods used to calculate Realized Volatility (default = 14).
Smoothing Period: The number of periods used for smoothing the normalized values (default = 3).
How to Use:
This oscillator is designed for traders who want to track the relationship between Historical Volatility and Realized Volatility.
Buy signals occur when HV increases relative to RV, which can indicate increased market movement or potential breakout conditions.
Sell signals occur when RV is greater than HV, signaling reduced volatility or potential trend exhaustion.
Example Use Cases:
Breakout/Trend Strategy: Use the oscillator to identify potential periods of increased volatility (when HV crosses above RV) for breakout trades.
Mean Reversion: Use the oscillator to detect periods of low volatility (when RV crosses above HV) that might signal a return to the mean or consolidation.
This tool can be used on any asset class such as stocks, forex, commodities, or indices to help you make informed decisions based on the comparison of volatility measures.
NOTE: FOR INTRDAY PURPOSE USE 30/7/9 AS SETTING AND FOR DAY TRADE USE 14/7/9
Profitability Visualization with Bid-Ask Spread ApproximationOverview
The " Profitability Visualization with Bid-Ask Spread Approximation " indicator is designed to assist traders in assessing potential profit and loss targets in relation to the current market price or a simulated entry price. It provides flexibility by allowing users to choose between two methods for calculating the offset from the current price:
Bid-Ask Spread Approximation: The indicator attempts to estimate the bid-ask spread by using the highest (high) and lowest (low) prices within a given period (typically the current bar or a user-defined timeframe) as proxies for the ask and bid prices, respectively. This method provides a dynamic offset that adapts to market volatility.
Percentage Offset: Alternatively, users can specify a fixed percentage offset from the current price. This method offers a consistent offset regardless of market conditions.
Key Features
Dual Offset Calculation Methods: Choose between a dynamic bid-ask spread approximation or a fixed percentage offset to tailor the indicator to your trading style and market analysis.
Entry Price Consideration: The indicator can simulate an entry price at the beginning of each trading session (or the first bar on the chart if no sessions are defined). This feature enables a more realistic visualization of potential profit and loss levels based on a hypothetical entry point.
Profit and Loss Targets: When the entry price consideration is enabled, the indicator plots profit target (green) and loss target (red) lines. These lines represent the price levels at which a trade entered at the simulated entry price would achieve a profit or incur a loss equivalent to the calculated offset amount.
Offset Visualization: Regardless of whether the entry price is considered, the indicator always displays upper (aqua) and lower (fuchsia) offset lines. These lines represent the calculated offset levels based on the chosen method (bid-ask approximation or percentage offset).
Customization: Users can adjust the percentage offset, toggle the bid-ask approximation and entry price consideration, and customize the appearance of the lines through the indicator's settings.
Inputs
useBidAskApproximation A boolean (checkbox) input that determines whether to use the bid-ask spread approximation (true) or the percentage offset (false). Default is false.
percentageOffset A float input that allows users to specify the percentage offset to be used when useBidAskApproximation is false. The default value is 0.63.
considerEntryPrice A boolean input that enables the consideration of a simulated entry price for calculating and displaying profit and loss targets. Default is true.
Calculations
Bid-Ask Approximation (if enabled): bidApprox = request.security(syminfo.tickerid, timeframe.period, low) Approximates the bid price using the lowest price (low) of the current period. askApprox = request.security(syminfo.tickerid, timeframe.period, high) Approximates the ask price using the highest price (high) of the current period. spreadApprox = askApprox - bidApprox Calculates the approximate spread.
Offset Amount: offsetAmount = useBidAskApproximation ? spreadApprox / 2 : close * (percentageOffset / 100) Determines the offset amount based on the selected method. If useBidAskApproximation is true, the offset is half of the approximated spread; otherwise, it's the current closing price (close) multiplied by the percentageOffset.
Entry Price (if enabled): var entryPrice = 0.0 Initializes a variable to store the entry price. if considerEntryPrice Checks if entry price consideration is enabled. if barstate.isnew Checks if the current bar is the first bar of a new session. entryPrice := close Sets the entryPrice to the closing price of the first bar of the session.
Profit and Loss Targets (if entry price is considered): profitTarget = entryPrice + offsetAmount Calculates the profit target price level. lossTarget = entryPrice - offsetAmount Calculates the loss target price level.
Plotting
Profit Target Line: Plotted in green (color.green) with a dashed line style (plot.style_linebr) and increased linewidth (linewidth=2) when considerEntryPrice is true.
Loss Target Line: Plotted in red (color.red) with a dashed line style (plot.style_linebr) and increased linewidth (linewidth=2) when considerEntryPrice is true.
Upper Offset Line: Always plotted in aqua (color.aqua) to show the offset level above the current price.
Lower Offset Line: Always plotted in fuchsia (color.fuchsia) to show the offset level below the current price.
Limitations
Approximation: The bid-ask spread approximation is based on high and low prices and may not perfectly reflect the actual bid-ask spread of a specific broker, especially during periods of high volatility or low liquidity.
Simplified Entry: The entry price simulation is basic and assumes entry at the beginning of each session. It does not account for specific entry signals or order types.
No Order Execution: This indicator is purely for visualization and does not execute any trades.
Data Discrepancies: The high and low values used for approximation might not always align with real-time bid and ask prices due to differences in data aggregation and timing between TradingView and various brokers.
Disclaimer
This indicator is for educational and informational purposes only and should not be considered financial advice. Trading involves substantial risk, and past performance is not indicative of future results. Always conduct thorough research and consider your own risk tolerance before making any trading decisions. It is recommended to combine this indicator with other technical analysis tools and a well-defined trading strategy.
Adaptive Volatility-Scaled Oscillator [AVSO] (Zeiierman)█ Overview
The Adaptive Volatility-Scaled Oscillator (AVSO) is a dynamic trading indicator that measures and visualizes volatility-adjusted market behavior. By scaling various metrics (such as volume, price changes, standard deviation, ATR, and Yang-Zhang volatility) and applying adaptive smoothing, AVSO helps traders identify market conditions where volatility deviates significantly from the norm.
This indicator uses standardized scaling (Z-Score logic) to highlight periods of abnormally high or low volatility relative to recent history. With gradient coloring and clear volatility zones, AVSO provides a visually intuitive way to analyze market volatility and adapt trading strategies accordingly.
█ How It Works
⚪ Scaling Metrics: The indicator scales user-selected metrics (e.g., volume, ATR, standard deviation) relative to the market and price, providing a standardized volatility measure.
⚪ Z-Score Standardization: The scaled metric is normalized using a Z-Score to measure how far current volatility deviates from its recent mean.
Positive Z-Score: Above-average volatility.
Negative Z-Score: Below-average volatility.
⚪ Adaptive Smoothing: An Adaptive EMA smooths the Z-Score, dynamically adjusting its length based on the strength of the volatility. Stronger deviations result in shorter smoothing, increasing responsiveness.
█ Unique Feature: Yang-Zhang Volatility
The Yang-Zhang volatility estimator sets this indicator apart by providing a more robust and accurate measure of volatility compared to traditional methods like ATR or standard deviation.
⚪ What Makes Yang-Zhang Volatility Unique?
Comprehensive Calculation: It combines overnight price gaps (log returns from the previous close to the current open) and intraday price movements (high, low, and close).
Accurate for Gapped Markets: Traditional volatility measures can misrepresent price movement when significant gaps occur between sessions. Yang-Zhang accounts for these gaps, making it highly reliable for assets prone to overnight price jumps, such as stocks, cryptocurrencies, and futures.
Adaptable to Real Market Conditions : By including both close-to-open returns and intraday volatility, it provides a balanced and adaptive measure that captures the full volatility picture.
⚪ Why This Matters to Traders
Better Volatility Insights: Yang-Zhang offers a clearer view of true market volatility, especially in markets with price gaps or uneven trading sessions.
Improved Trade Timing: By identifying volatility spikes and calm periods more effectively, traders can time their entries and exits with greater confidence.
█ How to Use
Identify High and Low Volatility
A high Z-Score (>2) indicates significant market volatility. This can signal momentum-driven moves, breakouts, or areas of increased risk.
A low Z-Score (<-2) suggests low volatility or a calm market environment. This often occurs before a potential breakout or reversal.
Trade Signals
High Volatility Zones (background highlight): Monitor for potential breakouts, trend continuations, or reversals.
Low Volatility Zones: Anticipate range-bound conditions or upcoming volatility spikes.
█ Settings
Source: Select the price source for scaling calculations (close, high, low, open).
Metric Measure: Choose the volatility measure:
Volume: Scales raw volume.
Close: Uses closing price changes.
Standard Deviation: Price dispersion.
ATR: Average True Range.
Yang: Yang-Zhang volatility estimate.
Bars to Analyze: Number of historical bars used to calculate the mean and standard deviation of the scaled metric.
ATR / Standard Deviation Period: Lookback period for ATR or Standard Deviation calculation.
Yang Volatility Period: Period for the Yang-Zhang volatility estimator.
Smoothing Period: Base smoothing length for the adaptive smoothing line.
-----------------
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!
Contraction & Expansion Multi-Screener █ Overview:
The Contraction & Expansion Multi-Screener analyzes market volatility across many symbols. It provides insights into whether a market is contracting or expanding in volatility. With using a range of statistical models for modeling realized volatility, the script calculates, ranks, and monitors the degree of contraction or expansions in market volatility. The objective is to provide actionable insights into the current market phases by using historical data to model current volatility conditions.
This indicator accomplishes this by aggregating a variety of volatility measures, computing ranks, and applying threshold-based methods to identify transitions in market behavior. Volatility itself helps you understand if the market is moving a lot. High volatility or volatility that is increasing over time, means that the price is moving a lot. Volatility also mean reverts so if its extremely low, you can eventually expect it to return to its expected value, meaning there will be bigger price moves, and vice versa.
█ Features of the Indicator
This indicator allows the user to select up to 14 different symbols and retrieve their price data. There is five different types of volatility models that you can choose from in the settings of this indicator for how to use the screener.
Volatility Settings:
Standard Deviation
Relative Standard Deviation
Mean Absolute Deviation
Exponentially Weighted Moving Average (EWMA)
Average True Range (ATR)
Standard Deviation, Mean Absolute Deviation, and EWMA use returns to model the volatility, meanwhile Relative Standard Deviation uses price instead due to its geometric properties, and Average True Range for capturing the absolute movement in price. In this indicator the volatility is ranked, so if the volatility is at 0 or near 0 then it is contracting and the volatility is low. If the volatility is near 100 or at 100 then the volatility is at its maximum.
For traders that use the Forex Master Pattern Indicator 2 and want to use this indicator for that indicator, it is recommended to set your volatility type to Relative Standard Deviation.
Users can also modify the location of the screener to be on the top left, top right, bottom left, or bottom right. You also can disable sections of the screener and show a smaller list if you want to.
The Contraction & Expansion Screener shows you the following information:
Confirmation of whether or not there is a contraction or expansion
Percentage Rank of the volatility
Volatility MA direction: This screener uses moving averages on the volatility to determine if its increasing over time or decreasing over time.
Volatility % (Standard Deviation of Returns)This script takes closing prices of candles to measure the Standard Deviation (σ) which is then used to calculate the volatility by taking the stdev of the last 30 candles and multiplying it by the root of the trading days in a year, month and week. It then multiplies that number by 100 to show a percentage.
Default settings are annual volatility (252 candles, red), monthly volatility (30 candles, blue) and weekly volatility (5 candles, green) if you use daily candles. It is open source so you can increase the number of candles with which the stdev is calculated, and change the number of the root that multiplies the stdev.
Volatility FinderVolatility Finder / Daily Range.
This indicator will measure the Average amount of Pips/Points movement of price, over an X amount of time.
This is often referred to as "Forex Volatility" Most pairs have different amounts of volatility. Exotics pairs are considered very volatile, Forex Majors is less volatile.
So this Indicator, will measure the amount of ADR/Average Daily Range.
Average amount of Pips/Points of movement, within a specific period of time, and tell you that.
- In the settings, you can choose how many days you want the indicator to measure from, and it will tell you the average amount of pips, based on the average movement on those days.
The Default setting is set to 90 days/3 months.
IMPORTANT:
To see the number the indicator tells you, you have to RIGHT-click up in the Left-side corner, where you see the Pair you have open on your Chart. And make sure to Enable "INDICATOR VALUES". Then if you However over the Indicator area, where the indicators you have open. You will see the number that the indicator has found. Based on the Settings you have set in the Settings Menu.
* One applicable way to use this information is if you are inside a trade, and price has moved past the Daily Range. It could be less probable it will continue in the same direction when it has Met the Daily Range.
* Another is to use this, to find pairs that you might want to trade. If the Average Price movement over the time you input, is High, you can use this information to help you decide if this pair is to Volatile for you to consider trading, or if it moving to slow for you.
It's very accurate, if you want to compare, you can go to 3rd party websites like
Mataf / mataf.net/en/forex/tools/volatility
Investing.com / investing.com/tools/forex-volatility-calculator
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!
[BRAIN] Absolute Volatility of Price
Hello traders!
Today I want to share with you a series of scripts and strategies that I developed a few years ago. This is one of my first works, born from the curiosity of seeing a candlestick representation in a different way, without considering the price movement along the y-axis.
Imagine observing the price movement in dollars and percentages, always starting from the same reference point: the 0 axis. This approach can offer new insights and ideas on how and how much prices move.
To explain it better, the open of each candle does not start from the previous close negotiations but always starts from the 0 axis . In this way, it is possible to clearly compare the bodies of the candles with each other.
Script Visualization Methods and Input
- Study Normal: Simply reports the prices, including the negative ones of the red candles, on the same scale in absolute terms (ABS), as shown in the first indicator above.
- Study Normal Neg: In this version, the red candles vary negatively below zero, instead of in absolute terms above zero, as shown in the second indicator above.
- Study Perc: Similar to "Study Normal" but uses percentage values instead of dollars, useful for very low timeframes and low variations with many decimals, such as 1 minute on EUR/USD.
- Study Perc Neg: Similar to "Study Normal Neg" but uses percentage values.
Additionally, I have added the possibility to display or not, through two buttons, an average of the candle bodies adjustable in length via input and the range of each candle, always correlated in dollars or percentages, as per the main study setting.
I hope this work can be useful to many of you. I invite you to like if you appreciate my scripts and want to see more like these. Do not hesitate to comment or contact me for any doubts or questions.
PS: If you notice that in the script the sum of the percentage values between the shadow and the body of the candle does not correspond to the range, it is only a rounding issue. Change the precision setting to a lower value and you will see that the rounding disappears.
PS: In the script, to better visualize the percentage growth and decline of the instrument on very high timeframes, I decided to represent it as follows:
- If close ≥ open: (high - low) / low * 100
- If close < open: (high - low) / high * 100
The same method is also applied for calculating the percentage variations of the shadows relative to themselves.
I hope you like this version! If you need any further modifications or adjustments, let me know. Good luck with your project!
(In the photos below I show 3 versions of the indicator open on 3 different tickers as an example: from top to bottom in the 3 indicators are set these Study: Study Normal, Study Perc and Study Perc Neg)
Machine Learning Adaptive SuperTrend [AlgoAlpha]📈🤖 Machine Learning Adaptive SuperTrend - Take Your Trading to the Next Level! 🚀✨
Introducing the Machine Learning Adaptive SuperTrend , an advanced trading indicator designed to adapt to market volatility dynamically using machine learning techniques. This indicator employs k-means clustering to categorize market volatility into high, medium, and low levels, enhancing the traditional SuperTrend strategy. Perfect for traders who want an edge in identifying trend shifts and market conditions.
What is K-Means Clustering and How It Works
K-means clustering is a machine learning algorithm that partitions data into distinct groups based on similarity. In this indicator, the algorithm analyzes ATR (Average True Range) values to classify volatility into three clusters: high, medium, and low. The algorithm iterates to optimize the centroids of these clusters, ensuring accurate volatility classification.
Key Features
🎨 Customizable Appearance: Adjust colors for bullish and bearish trends.
🔧 Flexible Settings: Configure ATR length, SuperTrend factor, and initial volatility guesses.
📊 Volatility Classification: Uses k-means clustering to adapt to market conditions.
📈 Dynamic SuperTrend Calculation: Applies the classified volatility level to the SuperTrend calculation.
🔔 Alerts: Set alerts for trend shifts and volatility changes.
📋 Data Table Display: View cluster details and current volatility on the chart.
Quick Guide to Using the Machine Learning Adaptive SuperTrend Indicator
🛠 Add the Indicator: Add the indicator to favorites by pressing the star icon. Customize settings like ATR length, SuperTrend factor, and volatility percentiles to fit your trading style.
📊 Market Analysis: Observe the color changes and SuperTrend line for trend reversals. Use the data table to monitor volatility clusters.
🔔 Alerts: Enable notifications for trend shifts and volatility changes to seize trading opportunities without constant chart monitoring.
How It Works
The indicator begins by calculating the ATR values over a specified training period to assess market volatility. Initial guesses for high, medium, and low volatility percentiles are inputted. The k-means clustering algorithm then iterates to classify the ATR values into three clusters. This classification helps in determining the appropriate volatility level to apply to the SuperTrend calculation. As the market evolves, the indicator dynamically adjusts, providing real-time trend and volatility insights. The indicator also incorporates a data table displaying cluster centroids, sizes, and the current volatility level, aiding traders in making informed decisions.
Add the Machine Learning Adaptive SuperTrend to your TradingView charts today and experience a smarter way to trade! 🌟📊
ATR GerchikAverage True Range ( ATR ) is a technical analysis indicator that measures market volatility. It is a moving average of the true range over a period of time. Originally developed by a market technician J. Welles Wilder Jr. in the 1970s, ATR was utilized to measure the average volatility of an asset over a given time period. Wilder realized that measuring volatility using only closing prices would not yield accurate results, necessitating a more complex system. To calculate the Average True Range, one must first determine the True Range (TR).
ATR calculation procedure:
1. Determine the true maximum - this is the highest of the current maximum and yesterday's closing price of the day.
2. Determine the true minimum - this is the smallest of the current minimum and yesterday's closing price.
3. Determine the true range - this is the distance between the true maximum and minimum.
4. Exclude extremely large candles and extremely small ones from the obtained true ranges.
5. Calculate the average for the selected period based on the remaining range.
6. Calculate the percentage of the current True Range relative to the average ATR value for the previous period.
Description:
If you analyze market movements, you will find that 75-80% of the time, an instrument moves only 1 ATR per day. Understanding this is crucial; for example, if an instrument has already moved 80% of its daily range, it is not advisable to enter a new position. This concept is similar to a car's fuel tank; if the tank is nearly empty, the car won’t go far. Many indicators include anomalous candles in their ATR calculations, which can yield unreliable results and lead to incorrect decisions. This is why many traders prefer to calculate ATR manually.
However, the Gerchik ATR indicator accounts for anomalous candles by filtering out extremely large and small candles. Users can set the coefficient for the upper and lower filtering thresholds. Experiment with these settings to find your criteria for filtering out abnormal candles. Personally, I filter out candles larger than 2x ATR and smaller than 0.5x ATR. Additionally, this indicator displays the consumed “fuel” of the instrument for the entire day and the current percentages, so you don’t have to calculate the distance traveled manually. The indicator also visually displays the boundaries of the average true range on the chart, enabling quick and informed decisions. When building any strategy, relying on the average true range movement is essential.
This extended version of the indicator includes a NATP indicator (Normalized ATR), a variation of the ATR that measures volatility as a percentage of the current price. It helps gauge market volatility levels and assists traders in making informed decisions.
Procedure for calculating NATR (Normalized ATR):
1. Determine the true maximum - the higher of the current high and the previous close.
2. Determine the true minimum - the lower of the current low and the previous close.
3. Determine the true range - the distance between the true maximum and minimum.
4. Filter out extremely large and small values from the obtained true ranges.
5. Calculate the average for n candles based on the remaining ranges.
Additionally in this version:
- Change table position
- Added NATP indicator
- Option to turn off the table description
- Option to turn off some indicators in the table
- Indication of the selected period in the table
- Changing coefficients for filtering abnormal candles
- Display of the number of invalid candles in the selected period
- Inclusion of labels with full ATR, NATR, candle range, and validity information
- Color-coding labels based on validity
- Selection of colors for valid and invalid candles
- Adjustable label size
- ATR graph display on the chart
- Customizable graph style, line thickness, and fill color
Detailed description:
Displays colored labels with detailed information. Labels can be color-coded based on validity and selected color. The text color will automatically adjust if a lighter color is chosen.
Panel of available settings
Graphic styles:
Line ATR graph style
Cross line ATR graph style
Step line ATR graph style
Step line diamond ATR graph style
Cross ATR graph style
Columns ATR graph style
Circles ATR graph style
Area ATR graph style
Cross area ATR graph style
Key Features:
- Anomalous Candle Filtering: Excludes extremely large and small candles for more reliable ATR values. Set filtering thresholds independently as coefficients.
- Consumed Fuel Indicator: Shows the percentage of the ATR consumed, aiding quick assessment of remaining movement potential.
- Daily Timeframe Focus: Designed for daily charts for accurate long-term analysis. The indicator is displayed on the daily timeframe if enabled, hiding it on lower timeframes.
- Visual Indicator Boundaries: Displays indicator boundaries on the chart with customizable styles and settings.
Practical Applications:
ATR helps traders predict potential future price movements, aiding in setting Stop Loss and Take Profit targets. Using ATR for SL/TP placement helps avoid market noise. ATR can also form an exit strategy by placing Trailing Stop Losses.
- Entry and Exit Points: Determine optimal entry and exit points by assessing market volatility and potential price movement.
- Stop-Loss Placement: Calculate stop-loss levels based on ATR to ensure appropriate placement, accounting for current market volatility.
- Trend Confirmation: Use ATR percentage consumption to confirm trend strength and decide on trade entries or exits.
Examples of Use:
- Trend Following: During strong trends, ATR identifies increased volatility periods, signaling potential breakouts or reversals.
- Range Trading: In ranging markets, ATR highlights low volatility periods, indicating consolidation and potential breakout zones.
[Pandora] Vast Volatility Treasure TroveINTRODUCTION:
Volatility enthusiasts, prepare for VICTORY on this day of July 4th, 2024! This is my "Vast Volatility Treasure Trove," intended mostly for educational purposes, yet these functions will also exhibit versatility when combined with other algorithms to garner statistical excellence. Once again, I am now ripping the lid off of Pandora's box... of volatility. Inside this script is a 'vast' collection of volatility estimators, reflecting the indicators name. Whether you are a seasoned trader destined to navigate financial strife or an eagerly curious learner, this script offers a comprehensive toolkit for a broad spectrum of volatility analysis. Enjoy your journey through the realm of market volatility with this code!
WHAT IS MARKET VOLATILITY?:
Market volatility refers to various fluctuations in the value of a financial market or asset over a period of time, often characterized by occasional rapid and significant deviations in price. During periods of greater market volatility, evolving conditions of prices can move rapidly in either direction, creating uncertainty for investors with results of sharp declines as well as rapid gains. However, market volatility is a typical aspect expected in financial markets that can also present opportunities for informed decision-making and potential benefits from the price flux.
SCRIPT INTENTION:
Volatility is assuredly omnipresent, waxing and waning in magnitude, and some readers have every intention of studying and/or measuring it. This script serves as an all-in-one armada of volatility estimators for TradingView members. I set out to provide a diverse set of tools to analyze and interpret market volatility, offering volatile insights, and aid with the development of robust trading indicators and strategies.
In today's fast-paced financial markets, understanding and quantifying volatility is informative for both seasoned traders and novice investors. This script is designed to empower users by equipping them with a comprehensive suite of volatility estimators. Each function within this script has been meticulously crafted to address various aspects of volatility, from traditional methods like Garman-Klass and Parkinson to more advanced techniques like Yang-Zhang and my custom experimental algorithms.
Ultimately, this script is more than just a collection of functions. It is a gateway to a deeper understanding of market volatility and a valuable resource for anyone committed to mastering the complexities of financial markets.
SCRIPT CONTENTS:
This script includes a variety of functions designed to measure and analyze market volatility. Where applicable, an input checkbox option provides an unbiased/biased estimate. Below is a brief description of each function in the original order they appear as code upon first publish:
Parkinson Volatility - Estimates volatility emphasizing the high and low range movements.
Alternate Parkinson Volatility - Simpler version of the original Parkinson Volatility that I realized.
Garman-Klass Volatility - Estimates volatility based on high, low, open, and close prices using a formula that adjusts for biases in price dynamics.
Rogers-Satchell-Yoon Volatility #1 - Estimates volatility based on logarithmic differences between high, low, open, and close values.
Rogers-Satchell-Yoon Volatility #2 - Similar estimate to Rogers-Satchell with the same result via an alternate formulation of volatility.
Yang-Zhang Volatility - An advanced volatility estimate combining both strengths of the Garman-Klass and Rogers-Satchell estimators, with weights determined by an alpha parameter.
Yang-Zhang (Modified) Volatility - My experimental modification slightly different from the Yang-Zhang formula with improved computational efficiency.
Selectable Volatility - Basic customizable volatility calculation based on the logarithmic difference between selected numerator and denominator prices (e.g., open, high, low, close).
Close-to-Close Volatility - Estimates volatility using the logarithmic difference between consecutive closing prices. Specifically applicable to data sources without open, high, and low prices.
Open-to-Close Volatility - (Overnight Volatility): Estimates volatility based on the logarithmic difference between the opening price and the last closing price emphasizing overnight gaps.
Hilo Volatility - Estimates volatility using a method similar to Parkinson's method, which considers the logarithm of the high and low prices.
Vantage Volatility - My experimental custom 'vantage' method to estimate volatility similar to Yang-Zhang, which incorporates various factors (Alpha, Beta, Gamma) to generate a weighted logarithmic calculation. This may be a volatility advantage or disadvantage, hence it's name.
Schwert Volatility - Estimates volatility based on arithmetic returns.
Historical Volatility - Estimates volatility considering logarithmic returns.
Annualized Historical Volatility - Estimates annualized volatility using logarithmic returns, adjusted for the number of trading days in a year.
If I omitted any other known varieties, detailed requests for future consideration can be made below for their inclusion into this script within future versions...
BONUS ALGORITHMS:
This script also includes several experimental and bonus functions that push the boundaries of volatility analysis as I understand it. These functions are designed to provide additional insights and also are my ideal notions for traders looking to explore other methods of volatility measurement.
VOLATILITY APPLICATIONS:
Volatility estimators serve a common role across various facets of trading and financial analysis, offering insights into market behavior. These tools are already in instrumental with enhancing risk management practices by providing a deeper understanding of market dynamics and the inherent uncertainty in asset prices. With volatility estimators, traders can effectively quantifying market risk and adjust their strategies accordingly, optimizing portfolio performance and mitigating potential losses. Additionally, volatility estimations may serve as indication for detecting overbought or oversold market conditions, offering probabilistic insights that could inform strategic decisions at turning points. This script
distinctly offers a variety of volatility estimators to navigate intricate financial terrains with informed judgment to address challenges of strategic planning.
CODE REUSE:
You don't have to ask for my permission to use/reuse these functions in your published scripts, simply because I have better things to do than answer requests for the reuse of these functions.
Notice: Unfortunately, I will not provide any integration support into member's projects at all. I have my own projects that require way too much of my day already.
