Case studies
Illustrative examples of systematic strategies developed and tested by AI Quant Forge. They are published to show the research process, implementation choices, results and limitations — not because they are our best-performing models and not as investment recommendations.
Each month, the strategy trades a capped, long-only minimum-variance portfolio targeting the cross-sectional mean estimated return. It also…
Daily estimates a constrained Kelly allocation across SPY and GLD, then scales its active deviation from a 100% SPY benchmark to prescribed…
A class-weighted ridge-logistic model estimates the probability of near-term VIX stress and continuously scales a long-only SPY allocation,…
Each month, the strategy fits a multivariate normal tempered-stable model to 12 months of daily ETF returns and allocates capital so centere…
The strategy holds SPY long with exposure scaled from a one-day-ahead binomial Markov-switching multifractal volatility forecast. It targets…
A monthly risk overlay measures persistent rotation in the subdominant correlation eigenspace of a point-in-time large-cap stock universe. W…
The strategy holds a long NEPSE Index exposure scaled to a 12% annualized volatility target using one-day Student-t GARCH or EGARCH forecast…
A point-in-time correlation-network indicator shifts a large-cap equity portfolio into a 75% MBB defensive allocation when systemic co-movem…
Dynamically tilts a U.S. ETF portfolio between growth/technology and defensive/value-income baskets using a continuous macro-stress score bu…
Allocates weekly across 200 liquid US large-cap stocks using a minimum-variance anchor plus covariance-weighted recent-return tilts. The two…
Buys up to 20 liquid US stocks with strong absolute momentum when FEDFUNDS is at or below 1%. Exits positions when momentum weakens, price b…
A long-only US equity strategy enters liquid stocks when completed-week and daily moving-average trends are jointly bullish. Positions are A…