A deep, regime-driven ruleset that picks and sizes positions in leveraged and hedging ETFs based on RSI, momentum, and moving-average signals across many market modes to chase upside while aiming to limit drawdown.

A big, layered decision tree looks at many ETFs (often levered or inverse or volatility-related). It uses price signals and momentum (RSI and moving averages) over short and long windows to rank and select top ideas. Cash is allocated across modules; each module may choose 1 asset (top pick) or 2, using even weights within that module. Some branches flip into hedges (UVXY, SVXY, SQQQ, TMV, UUP, etc.) when risk indicators warn. The system cycles through market modes (bull, sideways, bear) and adjusts exposures accordingly, using rules to enter/exit positions and to preserve capital during rough patches. Overall, it’s a regime-aware, rule-driven approach that blends momentum, volatility, and risk-off trades across a broad ETF universe.

Out-of-sample: ~72% annualized return vs SPY ~21%; Calmar ≈2.30 signals strong risk-adjusted upside; a regime-aware, hedged ETF strategy seeks big gains while controlling downside versus the S&P 500.