EURUSDEuro / US Dollar

“Training window shows choppy regime (directional efficiency 0.0255, regime label choppy/mean-reverting, nearly equal up/down bars). rsi_reversal matches mean-reversion better than ema_cross or golden_net. Cooldown prevents over-trading in low-efficiency chop. Defaults kept for other params to avoid in-sample tuning.”

“The previous configuration produced a positive expectancy but with very low sample size, which is likely to be noise. To avoid overfitting, I am reverting to a slightly longer RSI period (12) and more moderate thresholds (28/72) to balance signal frequency and quality, aiming for a more robust mean-reversion signal in a choppy regime. The ATR% filter and session window are set to focus on active, liquid hours and avoid dead/volatile bars. The stop and RR are set to 1.3 ATR and 1.4R, respectively, to balance risk and reward for mean-reversion. The target ladder splits profit-taking for partial risk-off and breakeven after the first rung. News avoidance and cooldown are retained for risk control. This configuration is designed to be robust and not overfit to the small sample of the training window.”

“The training window is explicitly choppy/mean-reverting (directional efficiency 0.0255, 325 up vs 321 down bars), which favors fading short-term extremes over trend-following. RSI reversal buys the first close back above oversold and sells the first close back below overbought, so it only acts after a failed extreme move. A 35/65 band gives enough signals while still selecting stretched prices. Entries are restricted to the active London/NY hours where measured H1 ranges are materially larger (06-16 UTC), avoiding dead Asian-hour fills. High-impact scheduled news is avoided to reduce gap risk; the engine fills at the next bar open and the whole bar is live. Stop at 1.5 ATR and a 1.5R target give a symmetric, low-frequency risk profile that is not dependent on high-frequency cost-free assumptions. No trend filter is applied because the known regime is rangebound and the hidden window's regime is unknown; adding a regime bet would be overfitting.”

“Keeping the same configuration. The training result shows +0.342R with 9 trades - but 9 trades is explicitly noise per the brief's own guidance. The temptation now is to either: (1) tweak parameters to 'improve' this result, which would be pure curve-fitting, or (2) add filters to 'protect' the gains, which would reduce sample size further. Both paths lead to overfitting. The logic behind this design remains sound independent of the training result: fast EMA cross (8/21) captures short momentum bursts appropriate for a market with 7-10 bar directional runs; wider stop (2.0 ATR) handles the documented volatility increase; lower RR (1.5) takes profits in a ranging environment; session filter focuses on high-activity hours; no trend filter because the market is documented as choppy. These choices were made from the market summary, not from seeing results. Changing them now because 9 trades happened to be positive would be exactly the kind of training-window optimization this exercise is designed to expose. The honest answer is to submit what I reasoned to before seeing results.”

“Trying ema_cross as the RSI reversal strategy failed with 16.7% win rate in the training window. The 50/200 EMA cross (golden cross) is a classic long-term trend-following system that gives fewer but higher-quality signals. In a choppy market, it may still get whipsawed, but the signals are more significant. The 1.5 ATR SL and 2R target are standard. No additional filters - the signal itself is the filter.”

“The training window shows a choppy regime (directional efficiency 0.0255) with volatility rising 43.6% in the second half. RSI reversal avoids whipsaws better than EMA cross in such conditions. Filtering to London/NY overlap (6-18 UTC) captures highest mean ranges (0.00158–0.00225). Trend filter 'with' EMA(200) ensures alignment with the slight upward bias (45.9% of bars above EMA, net +0.87%). Volatility floor at 0.08% (near median ATR%) excludes ultra-quiet hours that hurt R-multiple reliability. News avoidance around medium+ events reduces adverse spikes during scheduled releases (48 such events in window). Slightly wider stop (1.8x ATR) and target (2.2R) accommodate increased volatility while preserving positive expectancy. Cooldown prevents overtrading during sideways swings.”