Volatilitybreakout — Indicators and Strategies

RSI-Adaptive T3 + Squeeze Momentum Strategy ✅ Strategy Guide: RSI-Adaptive T3 + Squeeze Momentum Strategy 📌 Overview The RSI-Adaptive T3 + Squeeze Momentum Strategy is a dynamic trend-following strategy based on an RSI-responsive T3 moving average and Squeeze Momentum detection . It adapts in real-time to market volatility to enhance entry precision and optimize risk. ⚠️ This strategy is provided for educational and research purposes only. Past performance does not guarantee future results. 🎯 Strategy Objectives The main objective of this strategy is to catch the early phase of a trend and generate consistent entry signals. Designed to be intuitive and accessible for traders from beginner to advanced levels. ✨ Key Features RSI-Responsive T3: T3 length dynamically adjusts according to RSI values for adaptive trend detection Squeeze Momentum: Combines Bollinger Bands and Keltner Channels to identify trend buildup phases Visual Triggers: Entry signals are generated from T3 crossovers and momentum strength after squeeze release 📊 Trading Rules Long Entry: When T3 crosses upward, momentum is positive, and the squeeze has just been released. Short Entry: When T3 crosses downward, momentum is negative, and the squeeze has just been released. Exit (Reversal): When the opposite condition to the entry is triggered, the position is reversed. 💰 Risk Management Parameters Pair & Timeframe: BTC/USD (30-minute chart) Capital (simulated): $30,00 Order size: `$100` per trade (realistic, low-risk sizing) Commission: 0.02% Slippage: 2 pips Risk per Trade: 5% Number of Trades (backtest period): 181 📊 Performance Overview Symbol: BTC/USD Timeframe: 30-minute chart Date Range: January 1, 2024 – July 3, 2025 Win Rate: 47.8% Profit Factor: 2.01 Net Profit: 173.16 (units not specified) Max Drawdown: 5.77% or 24.91 (0.79%) ⚙️ Indicator Parameters Indicator Name: RSI-Adaptive T3 + Squeeze Momentum RSI Length: 14 T3 Min Length: 5 T3 Max Length: 50 T3 Volume Factor: 0.7 BB Length: 27 (Multiplier: 2.0) KC Length: 20 (Multiplier: 1.5, TrueRange enabled) 🖼 Visual Support T3 slope direction, squeeze status, and momentum bars are visually plotted on the chart, providing high clarity for quick trend analysis and execution. 🔧 Strategy Improvements & Uniqueness Inspired by the RSI Adaptive T3 by ChartPrime and Squeeze Momentum Indicator by LazyBear , this strategy fuses both into a hybrid trend-reversal and momentum breakout detection system . Compared to traditional trend-following methods, it excels at capturing early trend signals with greater sensitivity . ✅ Summary The RSI-Adaptive T3 + Squeeze Momentum Strategy combines momentum detection with volatility-responsive risk management. With a strong balance between visual clarity and practicality, it serves as a powerful tool for traders seeking high repeatability. ⚠️ This strategy is based on historical data and does not guarantee future profits. Always use appropriate risk management when applying it.

Volatility Trend (Zeiierman)█ Overview The Volatility Trend (Zeiierman) is an indicator designed to help traders identify and analyze market trends based on price volatility. By calculating a dynamic trend line and volatility-adjusted bands, the indicator provides visual cues to understand the current market direction, potential reversal points and volatility. █ How It Works The indicator uses a weighted moving average of historical prices to create a responsive trend line that is adjusted for volatility using standard deviation. The indicator sets upper and lower bands at intervals of two standard deviations, acting as markers for potential overbought or oversold conditions. Additionally, by comparing current and previous trend line values, the indicator identifies the trend direction, providing crucial insights for traders. █ How to Use Trend Identification Use the trend line to identify the overall market direction. An upward-sloping line indicates an uptrend, while a downward-sloping line indicates a downtrend. Volatility Assessment Use the distance between the upper and lower bands to gauge market volatility. Wider bands indicate higher volatility, while narrower bands indicate lower volatility. Overbought/Oversold If the price reaches or exceeds the upper or lower bands, it may be in an overbought or oversold condition, respectively. █ Settings Trend Control: Adjusts the sensitivity and smoothness of the trend line. Lower values make the trend more responsive, while higher values make it smoother. Trend Dynamic: Controls how quickly the trend adjusts to price changes. Higher values result in a slower adjustment. Volatility: Consists of two parts - the scaling factor for volatility and the sensitivity for volatility adjustment. Adjusting these settings alters the distance between the trend lines and the price, as well as how sensitive the bands are to changes in volatility. Squeeze Control: Influences the degree to which market squeeze is considered in the calculation, with higher values increasing sensitivity. Enable Scalping Trend: A toggle that, when activated, makes the indicator focus on short-term trends, which is particularly useful for scalping strategies. █ Related scripts with the same calculation philosophy TrendCylinder TrendSphere Predictive Trend and Structure ----------------- 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!

Z-Score Based Momentum Zones with Advanced Volatility Channels The indicator "Z-Score Based Momentum Zones with Advanced Volatility Channels" combines various technical analysis components, including volatility, price changes, and volume correction, to calculate Z-Scores and determine momentum zones and provide a visual representation of price movements and volatility based on multi timeframe highest high and lowest low values. Note: THIS IS A IMPROVEMNT OF "Multi Time Frame Composite Bands" INDICATOR OF MINE WITH MORE EMPHASIS ON MOMENTUM ZONES CALULATED BASED ON Z-SCORES Input Options look_back_length: This input specifies the look-back period for calculating intraday volatility. correction It is set to a default value of 5. lookback_period: This input sets the look-back period for calculating relative price change. The default value is 5. zscore_period: This input determines the look-back period for calculating the Z-Score. The default value is 500. avgZscore_length: This input defines the length of the momentum block used in calculations, with a default value of 14. include_vc: This is a boolean input that, if set to true, enables volume correction in the calculations. By default, it is set to false. 1. Volatility Bands (Composite High and Low): Composite High and Low: These are calculated by combining different moving averages of the high prices (high) and low prices (low). Specifically: a_high and a_low are calculated as the average of the highest (ta.highest) and lowest (ta.lowest) high and low prices over various look-back periods (5, 8, 13, 21, 34) to capture short and long-term trends. b_high and b_low are calculated as the simple moving average (SMA) of the high and low prices over different look-back periods (5, 8, 13) to smooth out the trends. high_c and low_c are obtained by averaging a_high with b_high and a_low with b_low respectively. IDV Correction Calulation : In this script the Intraday Volatility (IDV) is calculated as the simple moving average (SMA) of the daily high-low price range divided by the closing price. This measures how much the price fluctuates in a given period. Composite High and Low with Volatility: The final c_high and c_low values are obtained by adjusting high_c and low_c with the calculated intraday volatility (IDV). These values are used to create the "Composite High" and "Composite Low" plots. Composite High and Low with Volatility Correction: The final c_high and c_low values are obtained by adjusting high_c and low_c with the calculated intraday volatility (IDV). These values are used to create the "Composite High" and "Composite Low" plots. 2. Momentum Blocks Based on Z-Score: Relative Price Change (RPC): The Relative Price Change (rpdev) is calculated as the difference between the current high-low-close average (hlc3) and the previous simple moving average (psma_hlc3) of the same quantity. This measures the change in price over time. Additionally, std_hlc3 is calculated as the standard deviation of the hlc3 values over a specified look-back period. The standard deviation quantifies the dispersion or volatility in the price data. The rpdev is then divided by the std_hlc3 to normalize the price change by the volatility. This normalization ensures that the price change is expressed in terms of standard deviations, which is a common practice in quantitative analysis. Essentially, the rpdev represents how many standard deviations the current price is away from the previous moving average. Volume Correction (VC): If the include_vc input is set to true, volume correction is applied by dividing the trading volume by the previous simple moving average of the volume (psma_volume). This accounts for changes in trading activity. Volume Corrected Relative Price Change (VCRPD): The vcrpd is calculated by multiplying the rpdev by the volume correction factor (vc). This incorporates both price changes and volume data. Z-Scores: The Z-scores are calculated by taking the difference between the vcrpd and the mean (mean_vcrpd) and then dividing it by the standard deviation (stddev_vcrpd). Z-scores measure how many standard deviations a value is away from the mean. They help identify whether a value is unusually high or low compared to its historical distribution. Momentum Blocks: The "Momentum Blocks" are essentially derived from the Z-scores (avgZScore). The script assigns different colors to the "Fill Area" based on predefined Z-score ranges. These colored areas represent different momentum zones: Positive Z-scores indicate bullish momentum, and different shades of green are used to fill the area. Negative Z-scores indicate bearish momentum, and different shades of red are used. Z-scores near zero (between -0.25 and 0.25) suggest neutrality, and a yellow color is used.

Volatility Compression Breakout The Volatility Compression Breakout indicator is designed to identify periods of low volatility followed by potential breakout opportunities in the market. It aims to capture moments when the price consolidates within a narrow range, indicating a decrease in volatility, and anticipates a subsequent expansion in price movement. This indicator can be applied to any financial instrument and timeframe. When the close price is above both the Keltner Middle line and the Exponential Moving Average (EMA), the bars are colored lime green, indicating a potential bullish market sentiment. When the close price is positioned above the Keltner Middle but below the EMA, or below the Keltner Middle but above the EMA, the bars are colored yellow, signifying a neutral or indecisive market condition. Conversely, when the close price falls below both the Keltner Middle and the EMA, the bars are colored fuchsia, suggesting a potential bearish market sentiment. Additionally, the coloration of the Keltner Middle line and the EMA provides further visual cues for assessing the trend. When the close price is above the Keltner Middle, the line is colored lime green, indicating a bullish trend. Conversely, when the close price is below the Keltner Middle, the line is colored fuchsia, highlighting a bearish trend. Similarly, the EMA line is colored lime green when the close price is above it, representing a bullish trend, and fuchsia when the close price is below it, indicating a bearish trend. Parameters -- Compression Period : This parameter determines the lookback period used to calculate the volatility compression. A larger value will consider a longer historical period for volatility analysis, potentially capturing broader market conditions. Conversely, a smaller value focuses on more recent price action, providing a more responsive signal to current market conditions. -- Compression Multiplier : The compression multiplier is a factor applied to the Average True Range (ATR) to determine the width of the Keltner Channels. Increasing the multiplier expands the width of the channels, allowing for a larger price range before a breakout is triggered. Decreasing the multiplier tightens the channels and requires a narrower price range for a breakout signal. -- EMA Period : This parameter sets the period for the Exponential Moving Average (EMA), which acts as a trend filter. The EMA helps identify the overall market trend and provides additional confirmation for potential breakouts. Adjusting the period allows you to capture shorter or longer-term trends, depending on your trading preferences. How Changing Parameters Can Be Beneficial Modifying the parameters allows you to adapt the indicator to different market conditions and trading styles. Increasing the compression period can help identify broader volatility patterns and major market shifts. On the other hand, decreasing the compression period provides more precise and timely signals for short-term traders. Adjusting the compression multiplier affects the width of the Keltner Channels. Higher multipliers increase the breakout threshold, filtering out smaller price movements and providing more reliable signals during significant market shifts. Lower multipliers make the indicator more sensitive to smaller price ranges, generating more frequent but potentially less reliable signals. The EMA period in the trend filter helps you align your trades with the prevailing market direction. Increasing the EMA period smoothes out the trend, filtering out shorter-term fluctuations and focusing on more sustained moves. Decreasing the EMA period allows for quicker responses to changes in trend, capturing shorter-term price swings. Potential Downsides While the Volatility Compression Breakout indicator can provide valuable insights into potential breakouts, it's important to note that no indicator guarantees accuracy or eliminates risk. False breakouts and whipsaw movements can occur, especially in volatile or choppy market conditions. It is recommended to combine this indicator with other technical analysis tools and consider fundamental factors to validate potential trade opportunities. Making It Work for You To maximize the effectiveness of the Volatility Compression Breakout indicator, consider the following: -- Combine it with other indicators : Use complementary indicators such as trend lines, oscillators, or support and resistance levels to confirm signals and increase the probability of successful trades. -- Practice risk management : Set appropriate stop-loss levels to protect your capital in case of false breakouts or adverse price movements. Consider implementing trailing stops or adjusting stop-loss levels as the trade progresses. -- Validate with price action : Analyze the price action within the compression phase and look for signs of building momentum or weakening trends. Support your decisions by observing candlestick patterns and volume behavior during the breakout. -- Backtest and optimize : Test the indicator's performance across different timeframes and market conditions. Optimize the parameters based on historical data to find the most suitable settings for your trading strategy. Remember, no single indicator can guarantee consistent profitability, and it's essential to use the Volatility Compression Breakout indicator as part of a comprehensive trading plan. Regularly review and adapt your strategy based on market conditions and your trading experience. Monitor the indicator's performance and make necessary adjustments to parameter values if the market dynamics change. By adjusting the parameters and incorporating additional analysis techniques, you can customize the indicator to suit your trading style and preferences. However, it is crucial to exercise caution, conduct thorough analysis, and practice proper risk management to increase the likelihood of successful trades. Remember that no indicator can guarantee profits, and continuous learning and adaptation are key to long-term trading success.

Volatility patterns / quantifytools - Overview Volatility patterns detect various forms of indecisive price action, on a larger scale as a compressed range and on a smaller scale as indecision candles. Indecisive and volatility suppressing price action can be thought of as a spring being pressed down. The more suppression, the more tension is built and eventually released as a spike or series of spikes in volatility. Each volatility pattern is assigned an influence period, during which average and peak relative volatility is recorded and stored to volatility metrics. - Patterns The following scenarios are qualified as indecision candles: inside candles, indecision engulfing candles and volatility shifts. By default, each indecision candle is considered a valid pattern only when another indecision candle has taken place within 3 periods, e.g. prior inside candle + indecision engulfing candle = valid volatility pattern. This measurement is taken to filter noise by looking for multiple hints of pending volatility, rather than just one. Level of tolerated noise can be changed via input menu by using sensitivity setting, by default set to 2. Sensitivity at 1: Any single indecision candle is considered a valid pattern Sensitivity at 2: 2 indecision candles within 3 bars is considered a valid pattern Sensitivity at 3: 2 indecision candles within 2 bars (consecutive) is considered a valid pattern The following scenarios are qualified as range patterns: series of lower highs/higher lows and series of low volatility pivots. A pivot is defined by highest/lowest point in price, by default within 2 periods back and 2 periods forward. When 4 pivots with qualities mentioned above are found, a box indicating compressed range will appear. Both required pivots and pivot definition can be adjusted via input menu. - Influence time and metrics By default, influence time for each volatility pattern is set to 6 candles, a period for which spike(s) in volatility is expected. For each influence period, average relative volatility (volatility relative to volatility SMA 20) and peak relative volatility is recorded and stored to volatility metrics. All metrics used in calculations are visible in "Data Window "tab. Average and peak volatility during influence period will vary depending on chart, timeframe and chosen settings. Tweaking the settings might result in an improvement and is worth experimenting with. - Visuals By default, indecision candles are visualized as yellow lines and range patterns as orange boxes. Influence time periods are respectively visualized as colored candle borders, applied as long as influence time period is active. All colors are fully customizable via input menu. - Practical guide Volatility patterns depict moments of equal strength from both bulls and bears. While this equilibrium is in place, price is stagnant and compresses until either side initiates volatility, releasing the built up tension. On top of hedging and playing the volatility using volatility based instruments, some other methods can be applied to take advantage of the somewhat tricky areas of indecision. Example #1: Trading volatility Volatility is not a bad thing from a trading perspective, but can actually be fertile ground for executing trade setups. Trading volatility influence periods from higher timeframes on lower timeframes gives greater resolution to work with and opportunities to take advantage of the wild swings created. Example #2: Finding bias for patterns Points of confluence where it anyway makes sense to favor one side over the other can be used for establishing bias for indecisive price action as well. At face value, it makes sense to expect bearish reactions at range highs and bullish reactions at range low, for which volatility patterns can provide a catalyst. Example #3: Betting on initiation direction Betting on direction of the first volatile move can easily go against you, but if risk/reward is able to compensate for the poor win rate, it's a valid idea to consider and explore.

SuperBollingerTrend (Expo)█ Overview The SuperBollingerTrend indicator is a combination of two popular technical analysis tools, Bollinger Bands, and SuperTrend. By fusing these two indicators, SuperBollingerTrend aims to provide traders with a more comprehensive view of the market, accounting for both volatility and trend direction. By combining trend identification with volatility analysis, the SuperBollingerTrend indicator provides traders with valuable insights into potential trend changes. It recognizes that high volatility levels often accompany stronger price momentum, which can result in the formation of new trends or the continuation of existing ones. █ How Volatility Impacts Trends Volatility can impact trends by expanding or contracting them, triggering trend reversals, leading to breakouts, and influencing risk management decisions. Traders need to analyze and monitor volatility levels in conjunction with trend analysis to gain a comprehensive understanding of market dynamics. █ How to use Trend Reversals: High volatility can result in more dramatic price fluctuations, which may lead to sharp trend reversals. For example, a sudden increase in volatility can cause a bullish trend to transition into a bearish one, or vice versa, as traders react to significant price swings. Volatility Breakouts: Volatility can trigger breakouts in trends. Breakouts occur when the price breaks through a significant support or resistance level, indicating a potential shift in the trend. Higher volatility levels can increase the likelihood of breakouts, as they indicate stronger market momentum and increased buying or selling pressure. This indicator triggers when the volatility increases, and if the price is near a key level when the indicator alerts, it might trigger a great trend. █ Features Peak Signal Move The indicator calculates the peak price move for each ZigZag and displays it under each signal. This highlights how much the market moved between the signals. Average ZigZag Move All price moves between two signals are stored, and the average or the median is calculated and displayed in a table. This gives traders a great idea of how much the market moves on average between two signals. Take Profit The Take Profit line is placed at the average or the median price move and gives traders a great idea of what they can expect in average profit from the latest signals. ----------------- 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!

[TH] Volatility Breakout Volatility Breakout Strategy for TradingHook. This strategy is not for backtesting but for forward-testing starting when added to chart. It can make and send a formatted message string for buy and sell order using alert.