Moving Average Trend Crossovers with a Historical Expectancy Panel
Summary
The strategy uses a short and long simple moving average crossover to enter long or short positions as the perceived trend changes. It pairs this trading rule with a chart panel that summarizes historical expectancy by month and year. The stated calculation combines win rate, average winning trade, and average losing trade; a heatmap is intended to make variation across periods easier to inspect. The example uses 14-day and 28-day averages, and the published test settings cover BTC perpetual futures over roughly a year.
The panel is a descriptive view of past trades, not a forecast or evidence of future profitability. The document warns that crossover systems can trade poorly in range-bound markets, where slippage and costs may accumulate, and that parameter choices can change results. It also says the expectancy measure may omit transaction costs and may become less representative after market conditions shift. The strategy description recommends considering cost-aware or rolling calculations, risk controls, and position sizing, but reports no actual performance figures.
Key ideas
- The strategy enters long or short positions when the two simple moving averages cross.
- A historical expectancy panel groups results by month and year for display as a heatmap.
- Expectancy combines win rate with average winning and losing trade amounts.
- Historical expectancy can lose relevance when market conditions change and may omit trading costs.
- Range-bound trading, slippage, and parameter sensitivity are key limitations.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.