A deep, regime-aware, multi-asset portfolio built from covariances via Markowitz optimization, then adjusted by a dense set of momentum/mean-reversion rules to rotate among stocks, bonds, commodities, and hedges (including short exposures) for risk-controlled growth.

In plain terms, the system first studies how a large group of assets tend to move together (their correlations) and converts that into a covariance framework. It then uses a classic portfolio-optimization method to pick an initial mix of assets that aims for the best expected return for a given amount of risk. Next, a detailed web of conditional rules (the blocks) governs how that mix shifts from day to day. If market signals show broad strength, it tilts toward equities and commodities; if signals indicate risk or turning conditions, it moves into safer assets like short-duration bonds or cash proxies, and it may even take short positions to reduce exposure to a market drop. The rules draw on indicators like moving averages, momentum tests, and relative strength comparisons between different assets (for example, SPY vs QQQ vs XLK) with various look-back periods (often 8–200 days). There are specialized themes (e.g., bear-market modes, alt-asset momentum, and hedged editions) that further guide allocation and risk controls. The result is a dynamic, diversified, long/short portfolio that spans stocks, bonds, commodities, precious metals, and hedges, all sized by an optimization framework but steered by regime-based rules.

Regime-aware, multi-asset strategy rotates across stocks, bonds, and hedges for risk-controlled growth. Out-of-sample Sharpe 1.22 vs S&P 1.10; drawdown 8.2% vs 18.8%; Calmar 1.93. Higher risk-adjusted returns with less downside than the S&P.