Xuhu Wan

I work at the intersection of economic theory, quantitative finance, and data science. My academic research started in dynamic contracting and now focuses on information design — persuasion, communication, and signaling in dynamic environments. On the empirical side, I work on machine-learning approaches to asset pricing.

Current interests include AI-driven game theory, dynamic contracting under new frictions, and how information disclosure shapes financial markets.

Outside the academy, I maintain two research-driven systematic trading strategies — SFG (defensive multi-asset, risk-parity core) and AGR (ML-driven equity long-only) — as empirical demonstrations of methods studied in my research. Both are backtested over 20 years of historical data and have been live-traded for 2 years.