Fadepool runs a population of retail-style trading strategies — the entries retail traders actually use, wrapped in the psychology they actually trade with (take profits early, let losers run, add to losers) — live on real FX data. It records every signal those strategies generate and studies, statistically, when it pays to take the other side of them, and when it pays to join them.
accruing live since … · updates hourly · results in pips; fills at live bid/ask so spread is included; overnight financing not yet modeled
three layers, each proven before the next is trusted
Two independent price feeds are compared minute-by-minute; any divergence beyond an adaptive threshold is logged permanently. Nothing triggers on unverified data.
Hundreds of strategy instances — classic retail entries crossed with retail position-management psychology, each bound to its own pair and timeframe — run live and record every entry, add-to-loser and exit.
The research question: at what point in a strategy's drawdown or run-up is it profitable to fade it — or follow it? Every candidate edge must prove itself forward, net of costs, before a cent trades on it.
Real-money execution stays off until the forward record demonstrates a conditional edge with adequate sample size. When armed, it trades micro positions (100 units) — a real-fill implementation check, not a performance claim. Retail-positioning data is tracked as a separate, attributable input so each driver's contribution is measured in isolation.