A dense, rule-based, daily-rebalanced multi-asset strategy that blends equities, sector tilts, gold and gold proxies, volatility hedges, and bonds. It uses momentum, RSI, and moving-average signals across multiple time frames, plus cross-asset comparisons, to tilt between risk-on exposure and crash/defensive hedges. Base cash-like protection (BIL) anchors the portfolio while crash-catching blocks seek hedges (UVXY, SPXS, SVIX, etc.) when stress signals appear. In short: aim for equity upside with layered risk controls and hedging that can shift aggressively with market conditions.

- It starts with cash-like protection: a base allocation that uses short-term Treasuries (BIL) as a cash proxy to cushion volatility. This base can be adjusted as signals evolve. - It then layers hedges and alternative assets (e.g., GLD, BTAL, BITO, SPMO) to capture or hedge specific risk factors (gold exposure, market-neutral/anti-beta, Bitcoin ETF, and a volatility-hedge tilt). - A set of signals labeled as sector tilts (e.g., XLP Colab Signals and XLU Colab Signals) evaluate which sectors or stock groups look relatively stronger, using momentum and return metrics over different windows. - The “Crash Catcher” and related CAOS/EQT/EM/BND blocks are designed to identify rising market stress and tilt toward hedges (e.g., UVXY, SPXS, SVIX, SZK, etc.) or to re-enter risk exposure as conditions improve. These blocks use momentum and trend checks across a mix of ETFs and levered products, and they often apply bottom-filtering or top-filtering to select a small subset of assets with the strongest signals. - There are multiple cross-asset comparisons (e.g., SPY vs GLD; SPY vs EEM; SPY vs TLT) that compare momentum, cumulative returns, and price relationships to decide whether to emphasize equity exposure, gold, or bonds. - A number of “Pick Bottom” style groups attempt to identify favorable long-side or hedged positions by focusing on the strongest moves among levered equity proxies (SPXL, TQQQ, TECL, SOXL) after filtering by RSI and moving-average metrics. - The model uses a large array of windows (short to long) for RSI, moving-average returns, cumulative returns, and moving-average price checks to create a mosaic of rules. The weights are expressed as percentages (denominators of 100) within subgroups and are then blended into the final daily allocation. - The overall architecture is described as an asset-class label (EQUITIES) with daily rebalance, suggesting the tool is intended for a dynamic, fast-moving allocation rather than a static buy-and-hold. - In practice, you’d expect the system to shift between heavy equity exposure, sector/defensive tilts (XLP, XLU, GLD-based hedges), and hedge/convertible-like bets (VIX-related ETFs, SPXS, UVXY, SVIX), with occasional shifts into cash or bond proxies (BIL, VTIP, TLT, TMF/TMV) depending on the signals. - Important caveats: the strategy relies on many interdependent conditions that can be highly sensitive to parameter choices and market regime; it may produce frequent turnover and requires robust risk controls to avoid unintended concentration in a few hedges or levered bets.

Out-of-sample, this strategy offers superior risk-adjusted returns and tighter risk controls vs SPY: Sharpe ~2.10 vs ~1.91, Calmar ~3.49, max drawdown ~3.11% vs ~5.07%, beta ~0.16, with positive alpha and hedging.