Exponential Moving Average Crossover Momentum Strategy

Summary

This strategy uses two exponential moving averages to generate trend-following entries. It enters long when the faster average crosses above the slower one and short when it crosses below. The document describes the EMA’s recursive weighting, in which the current price and prior EMA contribute according to a coefficient determined by the averaging period. Its published parameter values are 55 for the average labeled short and 34 for the one labeled long; the code’s cross conditions compare the 34-period average against the 55-period average, so the labels and stated fast/slow ordering are inconsistent.

The document provides a BTC/USDT Binance futures backtest configuration spanning roughly a year, but reports no returns, drawdowns, or other test findings. It cautions that crossovers can create false signals and perform poorly in consolidating markets. Suggested safeguards include testing parameter combinations, adding trend or volume filters, using stop-loss rules, and checking signals across timeframes. The strategy is simple to implement, but its lagging averages and internal period-label discrepancy warrant care when reproducing it.

Key ideas

• The strategy enters long or short when two exponential moving averages cross in opposite directions.
• EMA values blend the current price with the previous EMA using a coefficient tied to the averaging period.
• The published periods are 55 and 34, but the prose labels and code’s crossover ordering do not align cleanly.
• The document provides a BTC/USDT futures test interval but no reported performance results.
• Crossover whipsaws and lag are key limitations; filters and explicit loss controls are suggested.

Tags

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