Verified — this backtest ran on Tessen's own engine and data. The inputs can't be faked.
On data it never saw, the agent averaged -3.96bp per trade after costs (win rate 76.5% — irrelevant when losers outweigh winners).
Try: This is an entry-signal problem, not a tuning problem. Change the core idea: different condition, different timeframe, or add a regime filter (e.g. only trade high-volatility periods) — don't just widen stops.
Performance collapses between the training and test periods — the parameters fit historical noise, not a repeatable mechanism.
Try: Simplify: fewer conditions, rounder parameter values (RSI 30, not 28.7), wider regime windows. If a small parameter change kills it, it was never real.
<a href="https://tessen.ai/verify/81c7d920-edc1-4654-9e71-c8b470a3f808"><img src="https://anonimous.net/tessen-api/v1/badge/81c7d920-edc1-4654-9e71-c8b470a3f808.svg" alt="Tessen Grade" /></a>
A Tessen Grade is a historical, out-of-sample statistical measurement — not investment advice, a prediction, or a guarantee of future results. Most strategies fail; a passing grade can stop working as markets change. Trading involves substantial risk of loss. Full risk disclosure