Qualitative Signal Selection Using Trade Quality and Comfort
Summary
This article proposes evaluating social trading signals by inspecting the trades that generated their reported returns, rather than relying only on headline growth, subscriber count, and drawdown. It defines entry quality using maximum adverse excursion relative to the trade result, exit quality using realized result relative to maximum favorable excursion, and combines them into a trade quality measure. A separate comfort measure compares the time spent in profitable and losing territory, using minute bars to classify bars relative to the entry price.
The approach aims to favor providers whose trades capture favorable movement while limiting prolonged exposure to losses. The article describes processing signal histories and quote data with a custom script, then comparing candidates and testing chosen signals at small size. Its evidence is methodological and illustrative; the text provides no independent validation that these metrics predict future performance. Results depend on reliable intratrade price history, and provider selection remains uncertain. It also recommends dividing capital across multiple signals and setting loss limits for each allocation.
Key ideas
- Signal evaluation should examine how reported profits were produced, not just aggregate growth or drawdown.
- Entry quality relates maximum adverse excursion to the realized trade result.
- Exit quality compares realized profit with the maximum favorable excursion during the trade.
- Investor comfort can be approximated by the share of trade lifetime spent in profitable versus losing territory.
- Historical trade metrics do not guarantee future signal performance, so selection should be followed by small-scale testing and risk limits.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.