Scaling Positions as Price Deviates from a Moving Average

Summary

This mean-reversion approach measures price against a moving average and divides deviations into bands. It scales into a position as price moves farther below the average, using larger unit amounts at deeper levels, then sells in corresponding stages as price rises above the average. The source implements these rules for long positions and staged exits; although the prose describes shorting prices above the average, the supplied active orders do not establish short positions. The configurable inputs include the average length, deviation increment, and unit size at each level.

The published backtest settings specify BTC/USDT futures on Binance over roughly a year, using daily bars with an hourly base period, but no performance results are included. Repeated buying into a continuing decline can build substantial exposure, and the document acknowledges that persistent trends may prevent a return to the average. It also flags parameter choice and transaction costs as important limitations. Its suggested mitigations include filters, volatility-aware sizing, and careful testing.

Key ideas

• The strategy defines successive price bands using percentage deviations from a moving average.
• It adds larger long orders at deeper downside bands and stages sales as price rises through upside bands.
• The supplied active order logic describes long accumulation and reduction, despite prose that also discusses short entries.
• Persistent trends can extend exposure before mean reversion occurs, while trading frequency and costs affect results.
• The published backtest configuration does not include performance statistics.

Tags

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