Hybrid Breakout | VCP-Inspired TrendTrend Squeeze Breakout
Trend Squeeze Breakout is a trend-following momentum strategy designed to identify stocks in strong established uptrends that are consolidating into relatively tight trading ranges before attempting a breakout.
The strategy combines a simplified Minervini-style trend template, volatility contraction, volume confirmation, and stop-entry breakout execution. It is designed primarily for swing trading and is intended to participate in strong upward price expansions while filtering out many breakouts occurring in weak or declining trends.
Strategy Explanation
The strategy follows a simple sequence:
Identify a strong uptrend
A long setup requires:
Price above the 50-period SMA
50 SMA above the 150 SMA
150 SMA above the 200 SMA
200 SMA rising
200 SMA continuing to rise over the selected lookback period
50 SMA not declining
This establishes that the stock is already in a structurally bullish environment before considering an entry.
Identify a volatility contraction
The strategy looks for periods where recent price movement has become unusually tight.
It evaluates both:
Recent high-low range
Recent closing-price range
The high-low range is also compared with its historical percentile over the selected lookback period. This allows the strategy to identify relatively quiet consolidation periods rather than relying on a fixed volatility threshold alone.
Confirm volume
When the volume filter is enabled, breakout volume must exceed the moving-average volume baseline by the selected multiplier.
The default requirement is:
Volume > 20-period average volume × 1.2
This is intended to provide additional confirmation that the breakout is supported by meaningful participation.
Enter on a breakout
When the trend, contraction, and volume conditions are satisfied, the strategy places a stop-entry order above the recent high.
The default breakout lookback is 3 bars, allowing the strategy to attempt to enter as price moves through the recent consolidation high rather than simply buying while the stock remains inside the range.
Manage the position
Positions use tiered profit-taking:
25% closed at +10%
50% closed at +20%
Remaining position closed at +30%
Default stop loss at -8%
This allows the strategy to realize some profits during the initial move while maintaining exposure to larger momentum extensions.
Features
Trend Filter — 50/150/200 SMA bullish alignment
Long-Term Trend Confirmation — Requires the 200 SMA to be rising
Volatility Squeeze Detection — Identifies unusually tight recent ranges
Range Percentile Filter — Compares current volatility with historical volatility
Close-Range Filter — Detects tight price consolidation
Volume Confirmation — Optional volume expansion requirement
Stop-Entry Breakout — Enters only when price breaks the recent high
Tiered Profit Taking — Three configurable profit targets
Percentage-Based Stop Loss — Adjustable downside protection
Date Filter — Allows users to restrict backtests to a specific period
Configurable Parameters — Trend, volatility, volume, breakout, and risk settings can all be adjusted
Tips for Use
Use on liquid stocks
The strategy is generally better suited to liquid stocks and ETFs with sufficient trading volume. Extremely illiquid securities can produce unrealistic backtest results because of spreads and execution differences.
Start with daily charts
The strategy is particularly suited to identifying multi-day or multi-week momentum breakouts. Daily charts are a good starting point when evaluating the strategy.
Avoid optimizing every parameter
The many adjustable parameters make it possible to overfit the strategy to a particular stock or historical period. Test parameter changes across multiple securities and different market environments rather than optimizing exclusively for one chart.
Treat the volume filter as confirmation, not a guarantee
High volume can strengthen a breakout signal, but it does not guarantee that the breakout will succeed.
Test across different market conditions
Trend-following breakout systems typically perform differently during strong bull markets, corrections, sideways markets, and high-volatility periods. Evaluate results across multiple market regimes before relying on the strategy.
Pay attention to execution
The strategy uses stop-entry orders above recent highs. In live trading, gaps, slippage, spreads, and intrabar price movement can cause actual execution prices to differ from backtested results.
Important Note
This strategy is inspired by trend-template and volatility-contraction concepts, but it is not a complete implementation of a textbook VCP. It uses a simplified statistical contraction model rather than explicitly identifying multiple successive contractions, contraction depths, and their associated volume characteristics.
Backtest results are hypothetical and do not guarantee future performance. Always consider commissions, slippage, liquidity, position sizing, and market conditions when evaluating a strategy.
Recommended starting configuration: Daily timeframe, liquid stocks, default trend filter, volume confirmation enabled, and the default tiered risk-management settings.
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Toby Crabel's HisVolAs in Linda Raschke's Street smarts..... . This indicator shows the signals of Toby Crabel's Historical Volatility 6/100 strategy. The strategy assumes, that volatility contraction measured by two measures would give better results.
There is one other script that is a strategy , but it assumes that the signal requires both inside bar and narrowest range, what is not as in Linda Raschke's.
The strategy and what does the script do:
1) measures short-term unannualized volatility (by default six), long term uannualized volatility (by default 100), and measures the ratio of short volatility / long volatility.
2) checks if the current bar is an inside bar or has narrowest range out of last X bar (by default 4), or both,
3) puts an etiquette if short volatility / long volatility is equal to or smaller than 0,5 AND the day is inside bar, has narrowest range, or both.
Next day both buy-stop and sell-stop should be set. Buy-stop at the high and sell-stop at the low of the bar with etiquette.
This is by no means any financial advice, nor the historical results guarantee future gain.
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Volatility with Power VariationVolatility Analysis using Power Variation
The "Volatility with Power Variation" indicator is designed to measure market volatility. It focuses on providing traders with a clear understanding of how much the market is moving and how this movement changes over time.. This indicator helps in identifying potential periods of market expansion or contraction, based on volatility.
What the indicator does:
This indicator analyzes volatility which refers to the degree of variation in the returns of a financial instrument over time. It's an important measure to understand how much the price and returns of a asset fluctuates. High volatility means large price swings, meanwhile low volatility indicates smaller and consolidating movements. Realized (Historical) Volatility refers to volatility based on past price data.
Power Variation
Power Variation is an extension of the traditional methods used to calculate realized volatility. Instead of simply summing up squared returns (as done in calculating variance), Power Variation raises the magnitude of returns to a power p . This allows the indicator to capture different types of market behavior depending on the chosen value of p .
When P = 2, the Power variation behaves like a traditional variance measure. Lower values of p (e.g., p=1) make the indicator more sensitive to smaller price changes, meanwhile higher values make it more responsive to large jumps, but smaller price moves wont affect the measure that much or won't most likely.
Bipower Variation
Bipower variation is another method used to analyze the changes in price. It specifically isolates the continuous part of price movements from the jumps, which can help by understanding whether volatility is coming from regular market activity or from sharp, sudden moves.
How to Use the Indicator.
Understand Realized and Historical Volatility. Volatility after periods of low volatility you can eventually expect a expansion or an increase in volatility. Conversely, after periods of high volatility, the market often contracts and volatility decreases. If the variation plot is really low and you start seeing it increasing, shown by the standard deviation channels and moving average and you see it trending and increasing then that means you can expect for volatility to increase which means more price moves and expansions. Also if the scaling seems messed up, then use the logarithmic chart scale.
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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
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes! Indicator
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Volatility patterns / Flowly Indicators- 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.
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