volatility

To generate trading signals from historical volatility percentile rankings, feed OHLCV data into the engine to compute HV over a configurable window and rank it within a lookback period, producing long, short, or neutral positions based on mean-reversion regimes.

Historical volatility percentile ranks current HV against a lookback period to identify low- and high-volatility regimes, generating mean-reversion signals that time entries and exits when volatility extremes are likely to revert.

Yes, you can apply historical volatility signals across multiple assets by feeding OHLCV data into the engine, which calculates HV and generates per-asset signals using configurable thresholds for low and high volatility regimes.

You need to configure hv_window for HV calculation, lookback for percentile ranking, low_pct and high_pct for regime thresholds, and annualize to adjust volatility scaling when generating trading signals from OHLCV data.

Provide OHLCV data as input to the engine, then set the hv_window and lookback parameters to calculate historical volatility and rank its percentile, which outputs mean-reversion trading signals across your selected assets.

Historical volatility percentile signals rely on mean-reversion regimes and may not perform well during trending markets, as the strategy assumes volatility extremes will revert rather than persist across the configured lookback window.