Adaptive Zero-Lag EMA Signals Using Dominant-Cycle Estimation
Summary
The strategy adapts its smoothing period using a cosine instantaneous-frequency method intended to estimate the dominant market cycle. It then calculates an exponential average and searches a range of gain values for one that minimizes the current absolute error between the input price and an error-corrected EMA. Crossovers between the corrected value and the ordinary EMA generate long or short entries when the error percentage exceeds a threshold. Inputs include the source price, period, adaptivity, gain limit, threshold, and stated stop and target point values.
The document describes the calculation and publishes settings for a BTC/USDT futures backtest, but gives no performance results. The introductory explanation mentions position sizing and protective exits, yet the supplied source ends after entry rules and does not implement those exits or sizing. The backtest covers only a short period, so it cannot establish how the adaptive signal behaves across market regimes.
Key ideas
- A cosine frequency estimate is used to adjust the average period to an estimated dominant cycle.
- The method searches gain values to reduce the absolute difference between price and an error-corrected EMA.
- Crossovers trigger directional entries only when the error percentage exceeds a threshold.
- The source shown does not implement the stop, target, or position-sizing features described in its overview.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.