A multi-layer, mean-reversion driven risk-on/risk-off strategy that uses many ETF ratios and cross-checks across time windows to decide which long/short basket to trade, with a built-in diversification of signals and a guard against momentum-driven whipsaws.

- The system looks at a wide set of ETFs (including equities, sectors, gold, bonds, oil/gas proxies, utilities, and even volatility-focused funds) to gauge whether investors are taking on more risk or seeking safety. - It creates many signals by comparing how these ETFs perform relative to each other over different recent windows (for example, how fast one asset has risen vs another, or how volatile the market is behaving). - A second layer of risk-testing asks several independent tests to agree before acting. Signals must pass multiple checks across different assets and time frames to be considered robust. This diversifies signals so one noisy gauge doesn’t dominate. - A mean reversion provision sits in front to dampen actions if momentum is strongly pushing in one direction, reducing the chance of being lulled into a quick reversal. - When signals pass, the strategy builds a long/short portfolio using equal-ish weights across the approved signals and rebalances daily. Longs tend to include a mix of growth-oriented or defensive exposure (e.g., certain tech/growth ETFs, gold, utilities) while shorts target what the model sees as weaker or overextended parts of the market. Leveraged ETFs are used in some groups to magnify exposure, increasing both potential returns and risk. - The overall framework is designed to shift with regimes, but its heavy reliance on historical relationships and leverage means risk controls and risk disclosures are essential in live trading.

Back-tested out-of-sample stats show stronger risk-adjusted returns, lower drawdowns, and resilience to regime shifts vs the S&P. A diversified, multi-layer mean-reversion strategy that adapts to risk-on/risk-off dynamics.