A complex, multi-model, out-of-sample momentum and regime-rotation portfolio that blends many signals across a broad asset universe (stocks, sectors, bonds, volatility hedges, and leveraged/alternative ETFs) to select a small set of assets and weights. It uses RSI, moving averages, and relative strength, with KMLM as a dynamic diversifier, aiming for diversified growth with risk controls rather than a simple buy-and-hold approach.

- The strategy runs many small decision blocks (groups). Each block looks at a pool of assets and asks: is this asset exhibiting strength or favorable momentum on a certain time frame? If yes, it allocates weight to that asset within its block. - Signals rely on common momentum and trend ideas (relative strength, RSI, moving-average comparisons, and price-theory checks). Windows vary by rule (for example, RSI over 10–40 days; moving-average relationships over 20, 60, 180, or 200 days). - The universe includes popular stocks/ETFs (eg, SPY for the S&P, QQQ for tech-heavy Nasdaq), sector/credit/less-known ETFs, leverage/inverse vehicles (eg, TQQQ, UPRO, SOXL, UVXY), and hedges (eg, Zeros like BIL for short-term cash proxies; TLT and long-duration bonds as bond hedges). - One asset often dominates a block (select-n 1 or 2) and may be given a large weight (e.g., 100% within that block), while other blocks contribute smaller weights. Some blocks explicitly target top- or bottom- performing assets across windows or sorts. - A separate “KMLM switcher” sub-system uses the KMLM (Managed Futures) ETF as a filter in certain rotation decisions, adding a trend-following/diversification component that shifts exposure when KMLM signals align with other momentum cues. - The blocks also include hedging/risk-control themes, such as defensive sleeves (bond-like assets, short-term Treasuries) and “50/50” style groups that mix long/short momentum to damp risk while preserving upside opportunities. - Rebalancing: the root notes “rebalance: none,” suggesting the cadence is determined by the rule signals rather than a calendar schedule. The overall plan is designed to stay diversified and dynamically adjust exposure as rules fire. - The strategy uses an out-of-sample framework for at least three months—meaning the signals must have worked on data not used to design them, helping avoid curve-fitting and over-optimistic backtests. This improves robustness across market regimes. - In practice, you should expect a portfolio that can hold long positions in strong momentum assets, hedges against downturns, and selective use of more aggressive, levered instruments during favorable regimes. The combination aims to pursue upside with risk controls, but it also introduces significant complexity and some levered risk due to leveraged ETFs and volatility instruments. - Important caveat for a layperson: many assets used are not just plain stocks, but include leveraged ETFs (which magnify moves and risk), inverse/short ETFs (betting against a market), and volatility-based products (which behave very differently in rising vs. falling markets). The strategy is designed to switch among dozens of assets depending on a large set of signals, not to “buy the market” in a single straightforward way.

Out-of-sample momentum/regime strategy targets ~38% annualized return vs SPY’s ~18%, backed by diversified assets and dynamic hedging. Higher drawdowns exist, but it offers stronger growth potential and cross-asset resilience.