EMA Deviation and Standard Deviation Thresholds for Trend Following

Summary

This strategy measures the difference between the closing price and an EMA, then calculates the standard deviation of that difference. A factor scales the deviation into a dynamic threshold for entries. In one mode, it buys when the deviation crosses below the negative threshold, aiming to follow a downtrend; in the other, it buys when the deviation crosses above the positive threshold, aiming to follow an uptrend. Both modes are long-only in the provided implementation, and positions close when the deviation crosses zero. The listed defaults are a 200-period EMA and a factor of 1.7.

The document describes a BTC/USDT futures backtest configuration over a stated date range, but gives no performance results. It notes that EMA lag, parameter sensitivity, reversals, and frequent signals in choppy markets can hurt results or raise costs. It recommends testing parameters separately for each mode and considering stop-loss rules and filters. The source’s actual entry and exit logic should be distinguished from broader claims about flexible position management, since no such risk controls are specified in the shown rules.

Key ideas

• The strategy uses the standard deviation of price’s deviation from an EMA to set a changing entry threshold.
• Its two modes enter long on extreme negative or positive deviations, respectively.
• The shown exit rule closes the long position when the deviation crosses zero.
• EMA lag, reversals, and choppy-market signals are identified as risks.
• The document describes a futures backtest setup but reports no outcome or performance statistics.

Tags

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