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.
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…
The strategy holds up to 20 liquid US stocks with positive multi-horizon time-series momentum and bullish moving-average trends, but only wh…
The strategy holds liquid US large-cap stocks only when completed-week and daily moving-average trends are simultaneously bullish. Positions…
Each close, the strategy buys liquid stocks with persistent positive overnight returns and shorts stocks with weak overnight behavior after…
Ranks top-500 US stocks within sectors on quality and risk-adjusted momentum, then buys high-quality winners and shorts low-quality laggards…
Long-only regime-adaptive relative momentum strategy on the 100 most actively traded U.S. stocks. When SPY is in a positive, low-volatility…
Long-only weekly time-series momentum strategy on the 50 largest US stocks, selecting names with positive multi-horizon momentum, a 200-day…