Linear Regression Slope for Market Regime Trading

Summary

This strategy uses the change in closing price over a lookback period as a simple linear regression slope proxy to classify conditions as bullish or bearish. Its published defaults are a 20-bar slope length, a 50-bar simple moving average, and a slope threshold of 0.1. A slope above the threshold prompts a long entry, while a slope below its negative prompts a short entry. Positions are closed when price crosses the moving average.

The document frames slope as an objective way to summarize trend direction and strength, while noting that the calculation can lag. It warns that choppy markets can produce repeated signals and transaction costs, and that results depend on the slope, threshold, and moving-average settings. The provided BTC/USDT spot backtest configuration gives a date range and timeframe but no reported results. The source calculation is a change divided by lookback length rather than a fitted regression coefficient, and its exit rule closes positions at either direction of moving-average cross; these implementation details limit how literally the broader claims should be interpreted.

Key ideas

• The strategy classifies market direction using the average price change over a configurable lookback as a slope proxy.
• A positive threshold crossing prompts a long entry, and a negative threshold crossing prompts a short entry.
• Price crossing the simple moving average in either direction closes positions.
• The method can lag and may generate frequent signals in choppy markets.
• The published settings include a BTC/USDT spot backtest configuration but no performance results.

Tags

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