A complex, rule-based, momentum-driven fund surfer that selects one asset at a time from a wide menu (leveraged stock ETFs, hedges, volatility products, and some bond funds). It uses RSI and price-mersistence checks to pick an all-in position, with hedges in place to blunt risk when signals weaken. High-risk, high-reward approach designed to ride trends across regimes rather than a steady, diversified allocation.

Think of this as a smart switchboard for a single investment. It looks across many possible bets (a mix of stock market ETFs, leveraged bets, inverse bets to profit on declines, volatility products, and some bond funds). It then runs several mini-tests to see which asset looks strongest (or weakest, in some sub-strategies) based on simple, familiar ideas: - Momentum and strength: is the asset’s price movement strong over a short window? This is checked with a measure called RSI (roughly, “is this going up with energy or is it running out of steam” over a given number of days). - Price momentum relative to recent performance: is the asset above its recent trend or price level? - Short-term performance over a few days: is the asset’s return over the last 1–5 days good or bad, and is its drawdown (how much it has fallen) within a small acceptable range? - Relative strength against other assets: the system may rank several assets and pick the one with the strongest momentum or the “least bad” momentum depending on the sub-strategy. - Risk controls: some rules look at volatility signals (via VIX-related products like VXX/UVXY) or bond/treasury signals (TLT/SHY/TMF/TMV) to decide whether to hedge or to switch to a safer exposure if risk indicators are elevated. - All-in decision: when a rule passes, the system typically allocates 100% of the capital to the chosen asset (weight 100/100). - No automatic regular rebalancing: the system only changes when a new signal triggers; otherwise it stays in cash or the current position. In plain terms, the engine scans many possible bets, uses momentum-like signals to rank them, and then jumps fully into the asset that the rules say looks best right now, with hedges ready to kick in if risk rises. It is designed to adapt to different market regimes—strong uptrends in tech/growth via TQQQ/UPRO-enabled bets, downturns hedged by SQQQ or volatility products, and safety via treasury/bond exposure when risk spikes. The inclusion of “Bottom” and “Top” selections with different RSI windows merely reflects slightly different time horizons and momentum interpretations within the same framework. For someone new to the tickers: - TQQQ/UPRO are 3x leveraged bets on the broad tech/large-cap growth indices (QQQ/SPY) meaning they magnify moves up or down. - SQQQ is the inverse 3x bet on QQQ, used as a hedge. - VXX/UVXY are volatility bets that tend to rise when markets get choppy or drop. - VXX and UVXY are used sparingly as hedges, not as core long-term holdings. - SPY is the S&P 500 ETF (broad market). - QQQ tracks large-cap tech (Nasdaq 100). - TMF/TMV are 3x levered bets on long-term Treasuries; SHY is on short-term Treasuries. - TLT tracks long Treasuries. The exact thresholds (RSI windows, moving-average comparisons, max-drawdown windows) are specific to the model and are tuned to generate buy/sell decisions, but the overarching idea is: go long leverage when momentum looks strong in a given asset, and hedge or rotate to safer assets when signals warn of risk. This is not a simple strategy and carries significant risk, including large drawdowns if market conditions deteriorate.

Out-of-sample edge: annualized return ~78.7% vs 23.2% S&P, Sharpe ~1.51 vs 1.40, Calmar ~1.54. Higher upside with momentum-driven, all-in bets plus hedges. Note: higher drawdown (~51%) means aggressive risk tolerance.