Breaking the Trend: How to Avoid Cherry-Picked Signals
arXiv:2504.10914
The paper shows that a simple exponential moving average (EMA) based on a single‑time‑scale mean‑reversion model can capture the performance of trend‑following CTA strategies, arguing that more complex signal baskets risk cherry‑picking and are not optimal.
Abstract
Our empirical results show an impressive fit with the theoretical Sharpe formula of a trend-following strategy depending on the parameter of the signal, which was derived by by Grebenkov and Serror (2014). That empirical fit convinces us that a mean-reversion process with only one time scale is enough to model, in a precise way, the reality of the trend-following mechanism at the average scale of CTAs and as a consequence, using only one simple EMA, appears optimal to capture the trend. As a consequence, using a complex basket of different complex indicators as signal, does not seem to be so rational or optimal and exposes to the risk of cherry-picking.