A complex, rule-driven, multi-asset rotation strategy that uses momentum and volatility signals to pick a small set of ETFs (including levered and hedged funds) across stocks, bonds, and commodities. It aims to ride trends, hedge against volatility, and dynamically allocate to the strongest segments rather than sticking to a single asset class.

It divides money into big groups (like Tech vs Utilities, Bonds, Commodities) and then, using a lot of rules, chooses a small set of funds to own. Each fund is picked only if a mix of signals says it’s likely to rise: recent price trends, how strong the asset has been recently, and how its price compares to its moving averages. Signals include RSI (measures recent price strength), moving-average momentum (which assets have performed best lately), and price vs. longer-term averages. If conditions look favorable for a group, the strategy tends to pick up to 3 funds from that group—often using leveraged or inverse ETFs to magnify moves or hedge risk. If signals show risk is rising (volatility spikes, momentum fades), hedges and safer assets are considered. The system uses lots of nested “if/then” checks to decide which assets to own and how much weight to give them, with no fixed calendar rebalancing; changes occur as the decision rules trigger. In short: it tries to ride the strongest, most favorable market segments while ducking for cover when risk climbs, across a broad mix of stocks, bonds, commodities, and volatility hedges.

Out-of-sample, this dynamic, rule-based multi-asset rotation rides the strongest trends while hedging risk. It targets ~46% annualized return vs ~21% for the S&P, with superior risk-adjusted metrics (Sharpe ~1.45, Calmar ~2.11).