A complex, signal-driven risk-on/risk-off system that uses leveraged ETFs for upside in up markets and shifts to cash/hedges (bills, Treasuries, gold, dollar) in downturns, guided by long-term trend filters, momentum signals, and regime groups.

What it does in plain language: - The system watches whether the market is in an uptrend or a downtrend using long-term price indicators. If the signal says the market is in a healthy uptrend, it tends to tilt toward high-risk, levered stock ETFs to try to capture bigger gains. If the signal says the market is weak or choppy, it moves toward safer assets like short-term bonds, cash-like funds, gold, or dollars to protect the portfolio. - It chooses which assets to buy by looking at several momentum checks. It compares recent performance and momentum (for example, whether an asset has been going up and by how much) and then picks the best ones. Sometimes it picks the very strongest one or the top two to hold. It also sometimes avoids the weakest ones. - The strategy uses a mix of asset classes (stocks, tech exposure, financials, energy, gold, oil, dollar, volatility) to diversify risk and provide hedges against different kinds of market stress. It also uses leverage carefully, so the upside can be bigger in good times but so can the downside in bad times. - When it shifts to cash/hedges, it may place money in very short-term, safe instruments or in assets that historically help hold value or benefit when stocks fall (like gold or the dollar). It also has guardrails to keep the changes from happening too often and to keep the overall risk profile within a target band. - The whole system is built as a decision tree: many conditions must be met before it moves from one regime to another, so a single noisy signal is unlikely to flip the entire portfolio. However, the many steps mean it can be complex to audit and requires clean data to work well. In short: uptrend and strong momentum -> levered stock exposure; downtrend or choppy market -> safety hedges and cash; momentum screens help decide which assets to overweight within each regime. This is a tactical, signal-driven approach rather than a simple “buy and hold.” It’s important to validate its performance on new data and understand that leverage ETFs magnify both gains and losses.

Out-of-sample edge: Sharpe 1.58 vs SPY 1.36; annualized return ~47% vs ~22%; Calmar ~2.0. Uses risk-on/risk-off with levered bets in uptrends and hedges in downtrends for bigger upside and stronger risk control. Drawdowns may be larger in bear periods.