BONK 1H Long Volatility StrategyGrok 1hr bonk strategy:
Key Changes and Why They’re Made
1. Indicator Adjustments
Moving Averages:
Fast MA: Changed to 5 periods (from, e.g., 9 on a higher timeframe).
Slow MA: Changed to 13 periods (from, e.g., 21).
Why: Shorter periods make the moving averages more sensitive to quick price changes on the 1-hour chart, helping identify trends faster.
ATR (Average True Range):
Length: Set to 10 periods (down from, e.g., 14).
Multiplier: Reduced to 1.5 (from, e.g., 2.0).
Why: A shorter ATR length tracks recent volatility better, and a lower multiplier lets the strategy catch smaller price swings, which are more common hourly.
RSI:
Kept at 14 periods with an overbought level of 70.
Why: RSI stays the same to filter out overbought conditions, maintaining consistency with the original strategy.
2. Entry Conditions
Trend: Requires the fast MA to be above the slow MA, ensuring a bullish direction.
Volatility: The candle’s range (high - low) must exceed 1.5 times the ATR, confirming a significant move.
Momentum: RSI must be below 70, avoiding entries at potential peaks.
Price: The close must be above the fast MA, signaling a pullback or trend continuation.
Why: These conditions are tightened to capture frequent volatility spikes while filtering out noise, which is more prevalent on a 1-hour chart.
3. Exit Strategy
Profit Target: Default is 5% (adjustable from 3-7%).
Stop-Loss: Default is 3% (adjustable from 1-5%).
Why: These levels remain conservative to lock in gains quickly and limit losses, suitable for the faster pace of a 1-hour timeframe.
4. Risk Management
The strategy may trigger more trades on a 1-hour chart. To avoid overtrading:
The ATR filter ensures only volatile moves are traded.
Trading fees (e.g., 0.5% on Coinbase) reduce the net profit to ~4% on winners and -3.5% on losers, requiring a win rate above 47% for profitability.
Suggestion: Risk only 1-2% of your capital per trade to manage exposure.
5. Visuals and Alerts
Plots: Blue fast MA, red slow MA, and green triangles for buy signals.
Alerts: Trigger when an entry condition is met, so you don’t need to watch the chart constantly.
How to Use the Strategy
Setup:
Load TradingView, select BONK/USD on the 1-hour chart (Coinbase pair).
Paste the script into the Pine Editor and add it to your chart.
Customize:
Adjust the profit target (e.g., 5%) and stop-loss (e.g., 3%) to your preference.
Tweak ATR or MA lengths if BONK’s volatility shifts.
Trade:
Look for green triangle signals and confirm with market context (e.g., volume or news).
Enter trades manually or via TradingView’s broker tools if supported.
Exit when the profit target or stop-loss is hit.
Test:
Use TradingView’s Strategy Tester to backtest on historical data and refine settings.
Benefits of the 1-Hour Timeframe
Faster Opportunities: Captures shorter-term uptrends in BONK’s volatile price action.
Responsive: Adjusted indicators react quickly to hourly changes.
Conservative: Maintains the 3-7% profit goal with tight risk control.
Potential Challenges
Noise: The 1-hour chart has more false signals. The ATR and MA filters help, but caution is needed.
Fees: Frequent trading increases costs, so ensure each trade’s potential justifies the expense.
Volatility: BONK can move unpredictably—monitor broader market trends or Solana ecosystem news.
Final Thoughts
Switching to a 1-hour timeframe makes the strategy more active, targeting shorter volatility spikes while keeping profits conservative at 3-7%. The adjusted indicators and conditions balance responsiveness with reliability. Backtest it on TradingView to confirm it suits BONK’s behavior, and always use proper risk management, as meme coins are highly speculative.
Disclaimer: This is for educational purposes, not financial advice. Cryptocurrency trading, especially with assets like BONK, is risky. Test thoroughly and trade responsibly.
Recherche dans les scripts pour "Volatility"
SV Volatility Indicator BasicThe SV Volatility Indicator Basic in TradingView calculates and visualizes daily and average volatility over specified periods using three lines. Here’s what it does:
1. Daily Volatility Calculation. The indicator computes daily volatility as the percentage difference between the high and low prices relative to the closing price:
2. 30-day Moving Average of Volatility. A simple moving average (SMA) is applied to the daily volatility values over the last 30 days to smooth short-term fluctuations.
3. 90-day Moving Average of Volatility. Similarly, an SMA is calculated over the last 90 days to provide a longer-term view of volatility trends.
4. Visualization:
Three lines are plotted:
Red line: Represents the daily volatility in percentage terms.
Blue line: Displays the 30-day moving average of volatility.
Green line: Shows the 90-day moving average of volatility.
This indicator helps traders analyze market volatility by providing both immediate (daily) and smoothed (30-day and 90-day) measures, aiding in trend identification and risk assessment.
Uptrick: Crypto Volatility Index** Crypto Volatility Index(VIX) **
Overview
The Crypto Volatility Index (VIX) is a specialized technical indicator designed to measure the volatility of cryptocurrency prices. Leveraging advanced statistical methods, including logarithmic returns and variance, the Crypto VIX offers a refined measure of market fluctuations. This approach makes it particularly useful for traders in the highly volatile cryptocurrency market, providing insights that traditional volatility indicators may not capture as effectively.
Purpose
The Crypto VIX aims to deliver a nuanced understanding of market volatility, tailored specifically for the cryptocurrency space. Unlike other volatility measures, the Crypto VIX employs sophisticated statistical methods to reflect the unique characteristics of cryptocurrency price movements. This makes it especially valuable for cryptocurrency traders, helping them navigate the inherent volatility of digital assets and manage their trading strategies and risk exposure more effectively.
Calculation
1. Indicator Declaration
The Crypto VIX is plotted in a separate pane below the main price chart for clarity:
indicator("Crypto Volatility Index (VIX)", overlay=false, shorttitle="Crypto VIX")
2. Input Parameters
Users can adjust the period length for volatility calculations:
length = input.int(14, title="Period Length")
3. Calculating Daily Returns
The daily returns are calculated using logarithmic returns:
returns = math.log(close / close )
- **Logarithmic Returns:** These returns provide a normalized measure of price changes, making it easier to compare returns over different periods and across different assets.
4. Average Return Calculation
The average return over the specified period is computed with a Simple Moving Average (SMA):
avg_return = ta.sma(returns, length)
5. Variance Calculation
Variance measures the dispersion of returns from the average:
variance = ta.sma(math.pow(returns - avg_return, 2), length)
- Variance : This tells us how much the returns deviate from the average, giving insight into how volatile the market is.
6. Standard Deviation (Volatility) Calculation
Volatility is derived as the square root of the variance:
volatility = math.sqrt(variance)
- Standard Deviation : This provides a direct measure of volatility, showing how much the price typically deviates from the mean return.
7. Plotting the Indicator
The volatility and average return are plotted:
plot(volatility, color=#21f34b, title="Volatility Index")
plot(avg_return, color=color.new(color.red, 80), title="Average Return", style=plot.style_columns)
Practical Examples
1. High Volatility Scenario
** Example :** During significant market events, such as major regulatory announcements or geopolitical developments, the Crypto VIX tends to rise sharply. For instance, if the Crypto VIX moves from a baseline level of 0.2 to 0.8, it indicates heightened market volatility. Traders might see this as a signal to adjust their strategies, such as reducing position sizes or setting tighter stop-loss levels to manage increased risk.
2. Low Volatility Scenario
** Example :** In a stable market, where prices fluctuate within a narrow range, the Crypto VIX will show lower values. For example, a drop in the Crypto VIX from 0.4 to 0.2 suggests lower volatility and stable market conditions. Traders might use this information to consider longer-term trades or take advantage of potential consolidation patterns.
Best Practices
1. Combining Indicators
- Moving Averages : Use the Crypto VIX with moving averages to identify trends and potential reversal points.
- Relative Strength Index (RSI): Combine with RSI to assess overbought or oversold conditions for better entry and exit points.
- Bollinger Bands : Pair with Bollinger Bands to understand volatility relative to price movements and spot potential breakouts.
2. Adjusting Parameters
- Short-Term Trading : Use a shorter period length (e.g., 7 days) to capture rapid volatility changes suitable for day trading.
- Long-Term Investing : A longer period length (e.g., 30 days) provides a smoother view of volatility, helping long-term investors navigate market trends.
Backtesting and Performance Insights
While specific backtesting data for the Crypto VIX is not yet available, the indicator is built on established principles of volatility measurement, such as logarithmic returns and standard deviation. These methods are well-regarded in financial analysis for accurately reflecting market volatility. The Crypto VIX is designed to offer insights similar to other effective volatility indicators, tailored specifically for the cryptocurrency markets. Its adaptation to digital assets and ability to provide precise volatility measures underscore its practical value for traders.
Originality and Uniqueness
The Crypto Volatility Index (VIX) distinguishes itself through its specialized approach to measuring volatility in the cryptocurrency markets. While the concepts of logarithmic returns and standard deviation are not new, the Crypto VIX integrates these methods into a unique framework designed specifically for digital assets.
- Tailored Methodology : Unlike generic volatility indicators, the Crypto VIX is adapted to the unique characteristics of cryptocurrencies, providing a more precise measure of price fluctuations that reflects the inherent volatility of digital markets.
- Enhanced Insights : By focusing on cryptocurrency-specific price behavior and incorporating advanced statistical techniques, the Crypto VIX offers insights that traditional volatility indicators might miss. This makes it a valuable tool for traders navigating the complex and fast-moving cryptocurrency landscape.
- Innovative Application : The Crypto VIX combines established financial metrics in a novel way, offering a fresh perspective on market volatility and contributing to more effective risk management and trading strategies in the cryptocurrency space.
Summary
The Crypto Volatility Index (VIX) is a specialized tool for measuring cryptocurrency market volatility. By utilizing advanced statistical methods such as logarithmic returns and standard deviation, it provides a detailed measure of price fluctuations. While not entirely original in its use of these methods, the Crypto VIX stands out through its tailored application to the unique characteristics of the cryptocurrency market. Traders can use the Crypto VIX to gauge market risk, adjust their strategies, and make informed trading decisions, supported by practical examples, best practices, and clear visual aids.
EGARCH Volatility Estimator
EGARCH Volatility Estimator (EVE)
Overview:
The EGARCH Volatility Estimator (EVE) is a Pine Script indicator designed to quantify market volatility using the Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) model. This model captures both symmetric and asymmetric volatility dynamics and provides a robust tool for analyzing market risk and trends.
Key Features:
Core EGARCH Formula:
ln(σ t 2 )=ω+α(∣ϵ t−1 ∣+γ⋅ϵ t−1 )+β⋅ln(σ t−1 2 )
ω (Omega): Captures long-term baseline volatility.
α (Alpha): Measures sensitivity to recent shocks.
γ (Gamma): Incorporates asymmetric effects (e.g., higher volatility during market drops).
β (Beta): Reflects the persistence of historical volatility.
The formula computes log-volatility, which is then converted to actual volatility for interpretation.
Standardized Returns:
The script calculates daily log-returns and standardizes them to measure deviations from expected price changes.
Percentile-Based Volatility Analysis:
Tracks the percentile rank of current volatility over a historical lookback period.
Highlights high, medium, or low volatility zones using dynamic background colors.
Dynamic Normalization:
Maps volatility into a normalized range ( ) for better visual interpretation.
Uses color gradients (green to red) to reflect changing volatility levels.
SMA Integration:
Adds a Simple Moving Average (SMA) of either EGARCH volatility or its percentile for trend analysis.
Interactive Display:
Displays current volatility and its percentile rank in a table for quick reference.
Includes high (75%) and low (25%) volatility threshold lines for actionable insights.
Applications:
Market Risk Assessment: Evaluate current and historical volatility to assess market risk levels.
Quantitative Strategy Development: Incorporate volatility dynamics into trading strategies, particularly for options or risk-managed portfolios.
Trend and Momentum Analysis: Use normalized or smoothed volatility trends to identify potential reversals or breakouts.
Asymmetric Volatility Detection: Highlight periods where downside or upside volatility dominates.
Visualization Enhancements:
Dynamic colors and thresholds make it intuitive to interpret market conditions.
Percentile views provide relative volatility context for historical comparison.
This indicator is a versatile tool for traders and analysts seeking deeper insights into market behavior, particularly in volatility-driven trading strategies.
Historical VolatilityHistorical Volatility Indicator with Custom Trading Sessions
Overview
This indicator calculates **annualized Historical Volatility (HV)** using logarithmic returns and standard deviation. Unlike standard HV indicators, this version allows you to **customize trading sessions and holidays** for different markets, ensuring accurate volatility calculations for options pricing and risk management.
Key Features
✅ Custom Trading Sessions - Define multiple trading sessions per day with precise start/end times
✅ Multiple Markets Support - Pre-configured for US, Russian, European, and crypto markets
✅ Clearing Periods Handling - Account for intraday clearing breaks
✅ Flexible Calendar - Set trading days per year for different countries
✅ All Timeframes - Works correctly on intraday, daily, weekly, and monthly charts
✅ Info Table - Optional display showing calculation parameters
How It Works
The indicator uses the classical volatility formula:
σ_annual = σ_period × √(periods per year)
Where:
- σ_period = Standard deviation of logarithmic returns over the specified period
- Periods per year = Calculated based on actual trading time (not calendar time)
Calculation Method
1. Computes log returns: ln(close / close )
2. Calculates standard deviation over the lookback period
3. Annualizes using the square root rule with accurate period count
4. Displays as percentage
Settings
Calculation
- Period (default: 10) - Lookback period for volatility calculation
Trading Schedule
- Trading Days Per Year (default: 252) - Number of actual trading days
- USA: 252
- Russia: 247-250
- Europe: 250-253
- Crypto (24/7): 365
- Trading Sessions - Define trading hours in format: `hh:mm:ss-hh:mm:ss, hh:mm:ss-hh:mm:ss`
Display
- Show Info Table - Shows calculation parameters in real-time
Market Presets
United States (NYSE/NASDAQ)
Trading Sessions: 09:30:00-16:00:00
Trading Days Per Year: 252
Trading Minutes Per Day: 390
Russia (MOEX)
Trading Sessions: 10:00:00-14:00:00, 14:05:00-18:40:00
Trading Days Per Year: 248
Trading Minutes Per Day: 515
Europe (LSE)
Trading Sessions: 08:00:00-16:30:00
Trading Days Per Year: 252
Trading Minutes Per Day: 510
Germany (XETRA)
Trading Sessions: 09:00:00-17:30:00
Trading Days Per Year: 252
Trading Minutes Per Day: 510
Cryptocurrency (24/7)
Trading Sessions: 00:00:00-23:59:59
Trading Days Per Year: 365
Trading Minutes Per Day: 1440
Use Cases
Options Trading
- Compare HV vs IV - Historical volatility compared to implied volatility helps identify mispriced options
- Volatility mean reversion - Identify when volatility is unusually high or low
- Straddle/strangle selection - Choose optimal strikes based on historical movement
Risk Management
- Position sizing - Adjust position size based on current volatility
- Stop-loss placement - Set stops based on expected price movement
- Portfolio volatility - Monitor individual asset volatility contribution
Market Analysis
- Regime identification - Detect transitions between low and high volatility environments
- Cross-market comparison - Compare volatility across different assets and markets
Why Accurate Trading Hours Matter
Standard HV indicators assume 24-hour trading or use simplified day counts, leading to significant errors in annualized volatility:
- 5-minute chart error : Can be off by 50%+ if using wrong period count
- Options pricing impact : Even 2-3% HV error affects option values substantially
- Intraday vs overnight : Correctly excludes non-trading periods
This indicator ensures your HV calculations match the methodology used in professional options pricing models.
Technical Notes
- Uses actual trading minutes, not calendar days
- Handles multiple clearing periods within a single trading day
- Properly scales volatility across all timeframes
- Logarithmic returns for more accurate volatility measurement
- Compatible with Pine Script v6
Author Notes: This indicator was designed specifically for options traders who need precise volatility measurements across different global markets. The customizable trading sessions ensure your HV calculations align with actual market hours and industry-standard options pricing models.
USDT.D Volatility TrackerUSDT.D Volatility Tracker
Description:
This script is designed to track the volatility of USDT.D (US Dollar in cryptocurrency) on the TradingView platform. It uses a moving average and deviation from it to generate buy and sell signals, helping traders visualize changes in volatility and make informed decisions.
Input Parameters:
maPeriod: The period of the moving average (default 120). This parameter allows users to adjust the length of the period used to calculate the moving average.
devThreshold: The deviation threshold (default 0.6). This parameter defines the level of deviation that will trigger buy or sell signals.
Data Request:
The script requests closing data for USDT.D using the request.security function, allowing it to retrieve up-to-date data on the selected timeframe.
Moving Average and Deviation Calculation:
An exponential moving average (EMA) is used to calculate the deviation from the moving average, enabling the identification of current volatility.
Deviation Line Display:
The deviation rate line is displayed on the chart, allowing users to visually track changes in volatility.
Signal Generation:
If the deviation exceeds the set threshold (devThreshold), a buy signal is generated (green background).
If the deviation falls below the negative threshold (-devThreshold), a sell signal is generated (red background).
Visual Signals:
Buy signals are displayed on the chart as green triangles, while sell signals are displayed as red triangles. This helps traders quickly identify potential entry and exit points.
Range-Weighted Volatility (Comparable)I wrote an indicator to measure volatility inside a range. It’s extremely useful for choosing a trading pair for grid strategies, because it lets you quickly, easily, and fairly identify which asset is the volatility leader. It measures volatility “fairly” relative to the asset’s trading range, not just by absolute price changes.
For example: if an asset trades in a 50–100 range and over a week it moves many, many times between 52 and 98, then it’s highly volatile. But if another asset trades in a 50–1000 range and makes the same 52–98 moves, its volatility is actually low — because the “weight” of that movement relative to the full range is small. The indicator accounts for this “movement weight” relative to the range, then sums these weights into a single number. That number makes it easy to judge whether an asset is suitable for a grid strategy.
That’s exactly what grids need: not just high volatility, but high volatility within a narrow range.
Settings: the Window (bars) field defines how many bars are used to calculate volatility. On a 5-minute chart, one week is 2016 bars (2460/57). By default, the script calculates over 30 days on 5-minute charts. The script also allows you to set a second symbol for comparison, so you can see both results on the same chart.
Написал индикатор для определения волатильности в диапазоне, очень-очень полезно для выбора торговой пары на гриде, позволяет легко и быстро и честно определить лидера по волатильности, при этом определяет ее "честно", относительно торгового диапазона, а не просто изменения цены.
Например если актив торгуется в диапазоне 50-100 и за неделю много-много раз сходил 52-98, то это очень волатильный актив, и в то же время если актив торгуется в диапазоне 50-1000 и сходил так же 52-98, то это будет низко волатильный актив, т.е. учитывается "вес" движения относительно диапазона и данные "веса" суммируются в одну единую цифру по которой и можно оценивать насколько актив подходит под грид стратегию.
А ведь именно это для гридов и нужно, не просто высокая волатильность, а именно высокая волатильность в узком диапазоне.
Касательно настроек , в поле Windows (bars) задается количество баров по которым скрипт будет считать волатильность, на 5-ти минутки неделя это 2016 (24*60/5*7), стандартно скрипт считает за 30 дней на 5-ти минутки. + в самом скрипте можно указать вторую пару для сравнения чтоб на одном графике увидеть результат.
BTC Volatility ForecastThe "BTC Volatility Forecast" indicator is designed to help traders anticipate Bitcoin (BTC) price volatility by analyzing historical daily price ranges and projecting future fluctuations. Inspired by advanced volatility forecasting studies, it calculates an approximate realized variance using the squared difference between each day’s high and low prices. By applying a simple linear regression model over the past five days of variance data (customizable via the "Lag Period" input), the indicator provides a forecast for the next day’s volatility. This makes it a valuable tool for BTC traders looking to gauge potential market turbulence and adjust their strategies accordingly.
On the chart, the indicator displays two lines: a blue solid line representing the current realized variance and an orange line showing the forecasted volatility for the upcoming day. Traders can set a "Volatility Threshold" to trigger alerts when the forecast exceeds a specified level, aiding in risk management or trade planning. A debug label on the last bar also shows the exact current and forecasted values for quick reference. While this version uses daily data for simplicity, it captures the essence of volatility prediction and can be a starting point for understanding BTC market dynamics—perfect for both novice and experienced traders on TradingView.
QSL Rolling Annualized VolatilityThis script calculates the rolling annualized volatility of an asset, helping traders measure how much its returns fluctuate over time. It uses logarithmic daily returns and computes the standard deviation over a custom lookback period (default: 252 trading days = 1 year) to capture historical volatility. The result is scaled to an annualized figure by multiplying by √252, making it comparable across different timeframes.
🔹 Key Features:
Customizable Lookback Period: Set in days to fit different trading strategies.
Annualized Output: Expresses volatility in yearly terms for consistency with financial models.
Rolling Calculation: Continuously updates to reflect recent market conditions.
Clear Visualization: Plots volatility as a time-series indicator and displays the latest value with a label.
This tool is ideal for risk management, position sizing, and strategy optimization in quantitative trading. 🚀
Positive Volatility and Volume GaugeThis is my first published script. It is a real volatility gauge that allows the user to see the real volatility of a given candle on the 15-min time frame. It also has the SMA of real volatility and volume available.
It provides the user to identify high volatility points that can lead to reversals back to the mid-point of said high volatility.
You can change the threshold of the signal line. For the 15-min time frame, I suggest that the 1.5-2.5 threshold be used for the best view.
Good luck and let me know if you have any questions or suggestions. I'm always open to learning.
Thank you!
fake volume (normalized volatility)fake volume is not volume.
This is open source. check it my source.
there is no 'volume'
but look at that indicator, it really looks like volume.
- how is it possible?
i tried to calculate volatility. and this is it.
usually volatility = volume. so this is not a supprise.
- how is it helpful? (how can we use this?)
compare with real volume. sometime it make difference.
if "fake volume" is high, but real volme is not high,
and that means the price may not peak( nor bottom )
also it doesnt have influence.
you can use this indicator for something like score, index. that doesnt have volume.
ex: SPX, KOSPI
======================================
가짜볼륨은 볼륨이 아닙니다.
소스코드를 보면 알겠지만 볼륨을 사용하지 않았습니다.
하지만 굉장히 볼륨처럼 보입니다.
- 어째서 이게 가능한가?
저는 시장변동률을 수치화 하려고 했고 그걸 가시화했을 뿐 입니다.
일반적으로 시장변동률은 거래량과 같이 움직입니다.
그러니 딱히 놀라운 현상은 아닙니다.
- 이것을 어떻게 쓰나요? 어떤 도움이 되나요?
가끔 볼륨이랑 가짜볼륨이 다를 수가 있습니다.
만약 볼륨이 가짜볼륨보다 작다면, 그 지점은 중요 고점이나 저점이 아니겠지요.
(사실 이런 기법들을 연구하면서 만들어진 저의 지표 shock detector가 따로 있습니다.)
볼륨이 없는 인덱스나 점수 계열을 보실 때에 볼륨 대신에 아쉬운대로 이걸 사용해볼 수도 있겠습니다.
Historical Volatility RatioThis script is a way to plot the ratio of short-term and long-term volatility. If the ratio is below 50% for a short/long term HV, we know that the market has the potential to make a large move as the volatility reverts back to its mean.
Credit to Dave Landry for this idea. Seems to be a nice predictor after looking at many breakouts after a pullback.
Defaults to 6-period and 100-period HV.
Currency Volatility Index (CVI)This Currency Volatility Index (CVI) indicator aggregates the realized volatility of the eight “major” FX pairs into a single, tradable series—much like an FX-version of the VIX. Here’s what it does step by step:
Inputs & Settings
• Volatility Length (default 20 days): the lookback over which daily log-returns’ standard deviation is computed.
• Data Timeframe (default Daily): the resolution at which price data is fetched for each pair.
• Smoothing Length (default 5): the period of a simple moving average applied to the raw, averaged volatility (in %).
Pair-by-Pair Volatility Calculation
For each hard-coded symbol (EURUSD, GBPUSD, USDJPY, USDCHF, AUDUSD, USDCAD, NZDUSD, EURGBP):
Pull the series of daily closes.
Compute the series of log-returns: ln(today’s close / yesterday’s close).
Calculate the standard deviation of those log-returns over your lookback.
Annualize it (×√252) to convert daily volatility into an annualized figure.
Aggregation
The eight annualized volatilities are averaged (equal weights).
The resulting number is then multiplied by 100 to express it as a percentage.
Smoothing & Plotting
A simple moving average over the aggregated volatility smooths out spikes.
The smoothed CVI (%) is plotted as a standalone line below price charts.
Visualization Aids
A small table in the top-right corner shows each pair’s current volatility in percent.
A dynamic label on the final bar prints the latest CVI value directly on the chart.
Why use it?
Gives a one-stop measure of overall FX market turbulence.
Helps you compare “quiet” vs. “volatile” regimes across currencies.
Dynamic Volatility Heatmap (ATR)How the Script Works
Dynamic Thresholds:
atrLow and atrHigh are calculated as percentiles (20% and 80% by default) of ATR values over the last double the ATR period (28 days if ATR is 14).
This creates thresholds that adapt to recent market conditions.
Background Heatmap:
Green: ATR is below the low threshold, indicating calm markets (options are cheap).
Red: ATR is above the high threshold, signaling elevated volatility (options are expensive).
Yellow: ATR is within the normal range, showing neutral market conditions.
Overlay Lines:
]Dynamic lines for atrLow and atrHigh help visualize thresholds on the chart.
Interpretation for Trading
Green Zone (Low ATR):
Interpretation: The market is calm, and options are likely underpriced.
Trade Setup: Favor buying options (e.g., long straddles or long calls/puts) to profit from potential volatility increases.
Red Zone (High ATR):
Interpretation: The market is volatile, and options are likely overpriced.
Trade Setup: Favor selling options (e.g., credit spreads or iron condors) to benefit from volatility decay.
Yellow Zone (Neutral ATR):
Interpretation: Volatility is within typical levels, offering no strong signal.
Trade Setup: Combine with other indicators, such as gamma levels or Bollinger Bands, for confirmation.
5. Enhancing with Other Indicators
Combine with Bollinger Bands:
Overlay Bollinger Bands to identify price extremes and align them with volatility heatmap signals.
Weighted VolatilityIntroducing the "Weighted Volatility" indicator, a powerful tool that incorporates the PeacefulIndicators library to measure the price volatility and volume in the market. This indicator is designed to help you detect potential opportunities and enhance your trading analysis.
The Weighted Volatility indicator offers the following features:
Adjustable input parameters, allowing you to modify the source (close by default) and the length parameter to suit your trading style and preferences.
A visually clear display, with the Weighted Volatility line in blue and a horizontal line at zero, making it easy to interpret the indicator's signals.
The core functionality of the Weighted Volatility indicator is powered by the weighted_volatility_oscillator function from the PeacefulIndicators library, ensuring accurate and reliable results.
To start using the Weighted Volatility indicator in your trading analysis, simply add the script to your chart and customize the input parameters as needed. We hope this script, built upon the PeacefulIndicators library, proves to be a valuable addition to your trading strategy.
[A618] Historical Volatility Bands
Historical Volatility Bands
To be used over 5 mins for best results
HVB is a standard deviation measure for Historical Volatility Percentile,
It helps you figure out the next level of Support and Resistances
> If the HVB width is narrow, its an indication for a Trending market day
> Price crossing the highest green band line symbolises a nice upmove
> Price crossing the lowest red band line symbolises a nice downmove
> Green and Red lines are levels of Support and Resistances with respect to Historical Volatility
Credits
Historical Volatility Percentile calculation part : @cheatcountry
Link to cheatcountry idea
Hope this Helps!
High Volatility and Big Price Change ScannerThis Pine Script scans for high volatility and significant price changes on the chart. It uses Average True Range (ATR) to measure volatility and calculates the percentage change in price over a specified lookback period. When both conditions—high volatility (ATR above a threshold) and a significant price change (greater than the set percentage threshold)—are met, a signal is plotted below the bar. Additionally, an alert condition is included for notifications when these conditions are satisfied.
This script is useful for identifying stocks with large price movements and increased volatility, which may indicate potential trading opportunities.
Volatility %This indicator compares the average range of candles over a long period with the average range of a short period (which can be defined according to whether the strategy is more long-term or short-term), thus allowing the measurement of the asset's volatility or the strength of the movement. It was also created to be used on the 1D time frame with Swing Trading.
This indicator does not aim to predict the direction or strength of the next movement, but seeks to indicate whether the asset's value is moving more or less than the average. Based on the principle of alternation, after a large movement, there will likely be a short movement, and after a short movement, there will likely be a long one. Therefore, phases with less movement can be a good time to position oneself, and if volatility starts to decrease and the target has not been reached, closing the position can be considered.
This indicator also comes with three bands of percentage volatility averages altered by a multiplier, allowing for a dynamic reading of how volatile the market is. These should be adapted according to the asset.
This indicator is not meant to be used alone but as an auxiliary indicator.
Local VolatilityThe traditional calculation of volatility involves computing the standard deviation of returns,
which is based on the mean return. However, when the asset price exhibits a trending behavior,
the mean return could be significantly different from zero, and changing the length of the time
window used for the calculation could result in artificially high volatility values. This is because
more returns would be further away from the mean, leading to a larger sum of squared deviations.
To address this issue, our Local Volatility measure computes the standard deviation of the
differences between consecutive asset prices, rather than their returns. This provides a measure of
how much the price changes from one tick to the next, irrespective of the overall trend.
~ arxiv.org
MAX4 Ord. Volatility Market ScannerScan volatility of for NEW 15 coin listed on binance futures , print result in label ordered form higher or lower volatility Use it in combination with MAX2 Ord. Volatility Market and MAX1 Ord. Volatility Market Scanner to have all binance futures coin scan
MAX3 Ord. Volatility Market ScannerScan volatility of for last 29 coin on binance futures, print result in label ordered form higher or lower volatility Use it in combination with MAX2 Ord. Volatility Market and MAX1 Ord. Volatility Market Scanner to have all binance futures coin scan
MAX2 Ord. Volatility Market ScannerScan volatility of 40 pair, print result in label ordered form higher or lower volatility
Use it in combination with MAX1 Ord. Volatility Market Scanner for have 80 coin scan
MAX1 Ord. Volatility Market ScannerScan volatility of 40 pair, print result in label ordered form higher or lower volatility
Use it in combination with MAX2 Ord. Volatility Market Scanner for have 80 coin scan
