A daily, rule-based, all-star momentum/rotation system that scans a broad ETF and stock universe, builds regime-based baskets (Bull, Bear, Defense, etc.), ranks top assets with multiple momentum and volatility tests, and holds a small, equal-weighted portfolio while hedging risk. It uses leveraged/volatility plays for strategy intensity and includes risk controls to shift into defensive assets when needed.

- What it does in plain terms: Every day, it looks across a very large family of ETFs (and some stocks) to decide which few should be bought for the next day. The goal is to own assets that have shown strong recent performance and favorable price trends, while avoiding or hedging against assets that look risky or overextended. - How it decides: It uses a nested set of tests (a decision tree). First, it sorts assets using different metrics (such as how much an asset has gained recently, how strong its price trend looks using moving averages, and how volatile it is). It then picks the top performers from various “baskets” or groups (for example, a Tech/Biotech-focused group, a Bear market group that uses inverse/ leveraged instruments, or a Defense group with bonds/gold/cash proxies). Each group selects a small number of best assets based on multi-window momentum signals. - What it buys: The system tends to hold a few assets at a time (often 3), with equal-weighting across them. The asset universe includes widely-known names (SPY, QQQ, IWM, XLK, AMZN, AAPL, NVDA, MSFT) and a broad array of ETFs (e.g., TQQQ, SOXL, UVXY, SQQQ, UPRO, SPXL, TECL, TMF, SHY, IEF, GLD, UUP, etc.). - How it adapts: It has “regime buckets” (Bull, Bear, Defense, and other thematic groups). Depending on current signals (price action, volatility, momentum, drawdown, etc.), it selects which bucket to trade and which assets to carry. This is the rotation aspect: you’re not always in the same set of assets; you tilt toward different baskets as conditions change. - How risk is managed: The structure includes checks like max drawdown (e.g., comparing the strategy’s drawdown to a benchmark like SPY), volatility measures (standard deviation), and price/momentum crossovers relative to long-term indicators. When risk signals worsen, the code shifts toward defensive assets (bonds, gold, cash proxies, or market hedges like SHY, IEF, UUP, GLD) to protect capital. - What “daily rebalance” means: Every trading day the system recomputes its signals and updates the basket; positions are adjusted to fit the current top picks and weights. - Why so many tickers and groups: The aim is to capture a broad set of drivers (tech leadership, biotech, emerging markets, energy, leveraged bets, hedges) and to be able to perform cross-asset rotation that’s responsive to different market regimes. The nesting (Group -> Subgroup -> Sort by X -> Filter by Y) is how the model blends many signals into a coherent, rule-based portfolio.

Out-of-sample shows ~45% annualized return vs SPY’s ~22%, with Calmar ≈1 and disciplined risk controls. Daily, rule-based rotation targets momentum leaders and hedges—delivering higher growth with managed volatility; note drawdowns can spike in stress.