A complex, rule-driven, momentum-based portfolio that blends leveraged stock bets with volatility hedges and bond/cash allocations. It uses multi-timeframe RSI-like signals and performance metrics to pick a handful of asset candidates from a wide ETF universe, then weights and rebalances them to adapt to changing market risk. It intention is to ride strong trends (in tech/leveraged ETFs) while reducing drawdown risk with hedges and safe assets when volatility spikes. It can incorporate niche ETFs (like KMLM) if they meet the momentum criteria.

- Build a portfolio from a broad universe of ETFs (including leveraged stock bets like TQQQ, SOXL, SPXL and hedges like UVXY, SVXY, VIXM, SQQQ). - The strategy uses layered rules that resemble a decision tree. Each level checks conditions such as momentum signals (a version of RSI over various day counts), relative strength versus a benchmark (often SPY or a bond proxy), and recent performance (cumulative or moving-average returns). It then selects the strongest candidates within a group (top N) and assigns weights to those assets. - There are explicit “Core” exposures and a separate “Safety Town” overlay. The Core aims for growth via leveraged equity exposure when momentum is favorable; Safety Town adds hedges and cash/bonds to reduce risk in uncertain markets. - Hedging logic uses volatility-related ETFs (UVXY, SVXY, VIXM, SQQQ) and anti-beta/factor funds (BTAL) to dampen drawdowns when volatility spikes or when momentum deteriorates. - Rebalancing is driven by the rule windows (days like 5, 10, 21, 30) that determine how often the system reassesses and reallocates. - The whole framework is designed to test multiple market regimes and to adapt by shifting between risk-on (bullish) bets and risk-off (defensive) allocations. The result is a portfolio that is often long several leveraged tech/growth ETFs when the trend is favorable, but that can pivot to hedges and safe assets when signals deteriorate. If you’d like a simpler, layman-friendly outline of a single “mode” (e.g., a pure risk-on mode and a pure risk-off mode) I can extract that as a straightforward two or three-basket plan. Also, if you want to understand a particular ticker’s role (for example, why the model might favor TQQQ vs SQQQ or UVXY in a given stripe of rules), I can walk through that specific decision path with plain-language explanations.

Out-of-sample Sharpe ~1.20 vs S&P ~1.14; annualized return ~62% vs ~19%; Calmar ~2.36 vs ~1.0. Momentum-driven, risk-managed strategy that rides trends with hedges, delivering superior risk-adjusted gains—even with higher drawdowns.