A high-risk, multi-asset, levered-backtest strategy that blends tech/semis bets (via leveraged ETFs) with volatility hedges and USD/commodity/Treasury exposures using RSI and moving-average signals to tilt among baskets and weights. It aims for strong returns but with substantial volatility and drawdown risk.

The strategy runs a backtest over a broad universe of ETFs that represent tech, broad market, semiconductors, volatility, USD/commodities, and Treasuries. It uses two core decision rules for each signal: (1) RSI-based momentum: if a short-term RSI reading on a given ETF is above or below a threshold (e.g., >70 or <30, with day windows like 5, 10, 20, or 30), it triggers a directional tilt or a switch to an alternative ETF (often leveraging or inverse/hedged exposure). (2) Moving-average/price signals: it also uses moving-average comparisons or moving-average-return checks to decide whether the asset should be favored or discarded. Based on these signals, the strategy allocates weights to various baskets (e.g., 55/100 to UVXY-related hedges, or 40/100 to a core group), and in some cases selects from multiple sub-baskets (e.g., “QQQ Pop Bot,” “SMH Pop Bot,” “Bull Market,” “Hedged AAA Popped,” etc.). The exposure often uses leveraged ETFs (e.g., TQQQ for long tech, SPXL for broad market, SOXL/SOXS for semiconductors) and hedges that perform well when volatility or drawdown risk spikes (UVXY, SQQQ). When risk conditions are judged unfavorable (via RSI or price checks against moving averages), the model shifts toward safer assets such as BIL (short-term Treasuries), USDU (USD exposure), or TMF/TMV (long-duration Treasuries with leverage). The structure is highly modular: many mini-systems run in parallel, their signals feed into “group” blocks with explicit weights, and the final allocation is a blend of these groups, tending toward cash-like or defensive assets under risk-off signals and toward aggressive, leveraged tech bets when momentum supports it. In plain terms: the plan tries to ride momentum in favorites like QQQ and semiconductors, but always keeps a set of hedges ready to step in if volatility or risk rises, and it blends many such bets to form a single, diversified but aggressive portfolio. Important caution for a layman: this is a backtest with extreme leverage and many moving parts; real-world results can differ sharply, especially during drawdowns or regime shifts. The approach assumes precise timing, frequent signal evaluation, and execution of multiple leveraged instruments, which carry high risk if market conditions change suddenly.

Out-of-sample, this strategy aims ~36% annual return with ~39% max drawdown vs the S&P’s ~23% return and ~19% drawdown—offering higher upside with active hedges and dynamic allocation to capture trends while guarding risk.