u/Expert_CBCD

Best win rate of 72.54% on DIA (Strategy 1), Strategy 2 avg return 0.62%, cumulative 126.68%. Blue-chip index shows strongest model prediction reliability among ETFs tested. DIA weekly long signal offers highest confidence for hitting median high. Lower average hurdle (0.95%) means smaller targets; model may be less effective in low-vol regimes.

Win rate 67.78% on GOOG, Strategy 2 avg return 0.66%, cumulative 67.75% but baseline cumulative 541.97% (misleading due to compounding). Single-stock model still shows signal edge, but baseline buy-and-hold dramatically outperformed cumulative model because model trades only 90 weeks vs 539. Use GOOG signal for tactical weekly longs, but acknowledge long-term hold has been superior. Single-stock idiosyncratic risk; baseline comparison flawed due to different trade counts; model may not capture long-term trend.

Win rate 68.28% on IWM, Strategy 2 avg return 0.41%, cumulative 64.63% outperforming baseline (48.44%). Small-cap index underperforms SPY in absolute returns but still shows model signal benefit. Use IWM signal for diversification, but expect lower per-trade returns. Lower win rate on the short side (not shown); small caps more susceptible to regime shifts.

Model win rate 69.13% on QQQ (Strategy 1), avg return 0.68% per trade for Strategy 2, cumulative profit 153.68% vs baseline 187.13%. QQQ’s high realized max profit potential (2.75%) suggests the model captures strong directional weeks. Apply same weekly signal logic to QQQ for tech-heavy portfolio exposure. Higher volatility in QQQ may increase drawdowns; baseline outperformed cumulative but model reduces risk by trading less.

Model achieves 70.18% win rate (SPY) when probability >60%, with average return 0.55% per trade (28.6% annualized) vs baseline 49.72% and 0.14%. The model’s selectivity (signals only 32% of weeks) and >70% accuracy create a systematic weekly long bias on Monday open. Buy SPY on Monday open when model probability >60%; hold to Friday close (Strategy 2) for superior risk/reward. Model may overfit to historical patterns; regime changes (e.g., rising rates, volatility spikes) could invalidate median-based thresholds.

Model on USO shows 69.23% win rate (Strategy 1), avg return 0.98% per trade, cumulative profit 102.80% vs baseline 22.46%. Commodity ETF exhibits strong model performance with massive outperformance over buy-and-hold hurdle strategy. Weekly long signal on USO when probability >60% generates high absolute returns with moderate frequency. Oil volatility is extreme; average hurdle 2.10% means large moves needed; model may overfit to trend periods.