A dense, daily-rebalanced, rule-based system that blends leveraged equity ETFs with hedges and bonds. It uses RSI and price-trend signals to pick a small slate of assets, then weights them; it includes bear-market hedges and regime-shift modules, and even test portfolios (like a no-shorts version) to study outcomes. In plain terms: it tries to ride strong market momentum with leveraged bets, while hedging risk with volatility and bond positions, all guided by a large set of nested rules.

- The system runs each day, rebalancing the selected Portfolios (e.g., Port 36 and Port 37) based on a long, nested set of decision rules. - Each rule tree starts at a high level (grouping assets into scenarios like bullish trends, bearish signals, or defensive bear-market hedges) and drills down to pick one asset (or a very small set) from a group. - Signals come from momentum and trend indicators (notably RSI-like readings, price relative to short-term and long-term moving averages, and price versus a 200-day trend). When a condition is met (for example, an asset’s RSI is in a particular range and its price is above/below a moving average), the engine may select that asset, or pass to an alternate choice. - “Top” or “bottom” selections pick the best/worst candidate within a group, and weights determine how much of the capital to allocate to each chosen asset (e.g., 100/100 or 50/100). - The design intentionally includes hedging paths. If indicators signal risk (e.g., overbought conditions, rising volatility, or sideways markets), the system can shift into hedges like UVXY (volatility), SQQQ (short QQQ), or VIX-related ETFs, or into bond/cash-like assets (BIL, SHY, BND) to reduce drawdowns. - Several named sub-portfolios and groupings (e.g., “Beta Baller,” “Seth’s Simplified Portfolio,” “Bear Market Sideways Protection”) serve as modules that apply different rule sets, which then feed into a final allocation. - The framework occasionally includes test/alternative configurations (e.g., “KMLM Switcher Testfolio – No Shorts”) to study how the results change when certain asset groups or positions are excluded. - Tick-by-tick, the system references tickers as proxies for asset classes (e.g., UVXY for volatility exposure, TQQQ for leveraged tech, QQQ as a base, SOXL/TECL as semis/tech megatrends, SQQQ as inverse exposure, BND/SHY/UUP etc. for bonds and diversification). - The approach is dynamic and can adapt to different market regimes, but it is data- and parameter-heavy, intended to automate a lot of decision logic that a human might otherwise apply in a discretionary way.

Dynamic, rule-based momentum strategy with hedges and bonds. Out-of-sample: ~11.1% annualized return with solid risk-adjusted profile (Calmar ~0.90) and diversification beyond SPY via regime-aware hedging and selective leverage.