Volatility-Normalized Trend Following with Hull Average and Risk Sizing

Summary

This trend-following system builds a cumulative series from price changes scaled by recent variability, then compares that normalized series with a Hull moving average. Crossovers open long positions and crossunders open short positions, with an opposite signal closing the existing direction. Position size is adjusted using recent return volatility and a target annualized volatility, subject to a leverage cap. A hard stop is placed using a multiple of average true range measured around entry.

The document outlines configurable lookbacks, long and short switches, compounding, and stop settings. Its published test setup uses daily BTC/USDT futures data for roughly a year, but no performance statistics are supplied, so its claims about signal quality or risk control are not empirically established here. The method can lag at reversals, volatility-based sizing can limit exposure during volatile moves, and tight stops may be hit by price swings. The implementation also depends on its volatility estimates and annualization assumptions; alternative averages, stop methods, and directional variants would need out-of-sample evaluation.

Key ideas

• Signals come from crossovers between a cumulative volatility-normalized price series and its Hull moving average.
• An opposite crossover closes the current directional position and can initiate the other side.
• Position size targets annualized volatility and is constrained by a maximum leverage setting.
• A configurable multiple of average true range determines a hard stop from entry.
• The published daily BTC/USDT futures setup provides no reported performance results.

Tags

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