Moving Average Crossovers Filtered by Slow-MA Slope

Summary

This strategy combines a fast and slow moving average crossover with a slope filter on the slow average. A bullish crossover signal is considered only when the slow average’s angle exceeds a threshold; the description frames entries around persistent upward movement. It uses percentage-based profit and loss levels, and the implementation also refers to Bollinger Bands for some exits. The narrative additionally describes opening a short after a strong rally, while the code’s entry logic and stop variables make the exact long and short behavior less straightforward.

The document warns that moving averages lag, stops may not protect against abrupt moves, and results depend on parameter choices. It proposes additional trend filters, adaptive periods, trailing stops, and position sizing, but supplies no measured results. The published settings are for BTC/USDT futures over a brief November 2023 interval; no performance statistics are reported, so they do not establish profitability or robustness.

Key ideas

• A bullish fast-over-slow moving average crossover is filtered by the slow average’s slope.
• The strategy uses percentage-based take profit and stop loss settings, with Bollinger Band conditions also present in the implementation.
• Lagging averages and parameter sensitivity can cause late or unreliable signals.
• The brief published futures test settings contain no performance results.

Tags

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