Volatility-Scaled Price Breakouts with Percentage Exits

Summary

This strategy estimates volatility from the standard deviation of recent logarithmic returns, annualizes that estimate, and scales it back to an expected move for one bar. It places dynamic thresholds above and below the previous close: a close above the upper threshold signals long, while a close below the lower threshold signals short. The accompanying explanation frames this as a Black-Scholes-inspired way to adapt breakout distances to changing volatility, with configurable lookback, chart timeframe, and percentage-based take-profit and stop-loss settings.

The document discusses false breakouts, volatility estimation error, parameter sensitivity, missed moves in persistent trends, and transaction costs. Suggested extensions include volume or momentum confirmation, EWMA or GARCH volatility, ATR-based stops, time filters, and higher-timeframe trend checks. A published backtest configuration names ETH/USDT futures over a short 2025 period, but no results are supplied. The method is a volatility-scaled breakout rule rather than a full option-pricing application; the described use of fixed percentage exits should also be checked against the source, which recalculates exit levels from the current close.

Key ideas

• The strategy estimates volatility from recent log returns and converts it into a one-bar expected price move.
• A close beyond the dynamic upper or lower threshold triggers a long or short entry, respectively.
• Percentage-based stop and target settings are included, though the source calculates their levels from the current close.
• The document identifies false breakouts, volatility forecast error, parameter sensitivity, and trading costs as limitations.
• The ETH/USDT futures backtest configuration is published without performance results.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.