A highly diversified, rules-based, daily-rebalanced multi-asset strategy that uses momentum and mean-reversion signals across stocks, bonds, commodities, and hedges to seek growth while controlling risk. It’s complex and unfolds through many nested rules and ETF selections (e.g., SPY, QQQ, SHV, UVXY, GLD, DBC, TLT, TMF, XLE, XLK, XLP, etc.), with hedging via inverse/volatility ETFs and a cash-allocation framework across blocks. Suited for sophisticated investors who can tolerate daily turnover and rigorous testing.

What it tries to do in plain English: - It divides a big pool of investing ideas into several buckets (stocks, bonds, commodities, energy, gold, and hedged or inverse ideas). - Each bucket holds a set of ETFs that stand in for that kind of asset (for example SPY or QQQ for broad stocks, TLT or TMF for longer-term bonds, GLD for gold, DBC for broad commodities, UVXY for volatility hedges, and SH/PSQ for hedged or inverse stock exposures). - Every day, it asks a long series of questions (rules) to decide which ETFs to own within each bucket. The questions are signals about momentum and trend: • Is the asset’s price recently going up strongly (momentum)? • Is it overbought or oversold (a simple RSI idea, which gives a gauge of how hot or tired a move is)? • How has it performed over different time windows (short, medium, long)? • Is there evidence that the asset is likely to revert toward a typical level (mean-reversion)? - If the signals look favorable, that bucket gets funded with its share of the total cash; if signals look risky, the strategy may hedge or reduce exposure using inverse or volatility-related ETFs (for example PSQ, SH, UVXY, SVXY). - Weights are assigned at multiple levels, with some blocks aiming for equal cash allocation while others tilt toward the strongest signals. The approach is highly systematic and rule-based, not speculative guesswork. It’s designed to ride rallies while trying to protect against sharp downturns, using a broad mix of equities, fixed income, commodities, and hedges. Important note: RSI and moving-average concepts are used as inputs, but the exact thresholds and nested decisions are very intricate, meaning the system rewards disciplined testing and regime awareness rather than casual adjustments.

Out-of-sample: risk-adjusted edge vs S&P. Sharpe ~1.31 vs ~1.11; return ~20.07% vs ~19.82%; max drawdown ~8.7% vs ~18.8%; Beta ~0.60; Calmar ~2.30—steady gains with downside protection.