Mission
The Quantitative Strategy Department develops systematic strategies grounded in asset-pricing research and advanced statistical methods. Our mandate is to convert academic insights into robust, capacity-aware investment signals that meet institutional standards of scalability and risk control.
Example Projects
Replicated and extended frontier research, including Supervised PCA for risk premia discovery, deep reinforcement learning ensembles for regime-adaptive momentum, and StockNet-style text–price models.
Established a full research governance framework: point-in-time data validation, out-of-sample ladders, transaction-cost modeling, and deflated Sharpe reality checks.
Delivered a diversified signal library across carry, value, quality, momentum, and defensive factors with embedded cost and liquidity constraints.
Example Future Projects
Transition four validated strategies into the live portfolio sleeve with robust monitoring and model-risk oversight.
Broaden cross-asset coverage (equities, credit, and macro overlays) to strengthen the Fund’s multi-factor core.
Formalize a “Model Committee” process with structured go/no-go decisions, attribution reviews, and controlled kill-switch criteria.
