Odds on Open Hedge Fund Manager Ernie Chan: Use GenAI to Manage Risk, Not Predict Return
Sep 2, 2025
Join Ernest P. Chan, a leading figure in quantitative finance and founder of PredictNow.ai, as he shares his insights on the intersection of AI and trading. He reveals when machine learning models thrive and the pitfalls of data sparsity in financial markets. Discover how generative AI enhances risk management and portfolio optimization. Ernie also discusses alternatives to find alpha, the evolution of his quant strategies, and the vital traits for success in this evolving field. A must-listen for aspiring quants!
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Finance Has A Data Sparsity Problem
- Financial markets suffer severe data sparsity because old historical data no longer reflect today's market structure and interventions.
- This makes direct ML prediction of returns fragile and prone to overfitting without careful handling.
Manage Risk Before Predicting Returns
- Build AI systems for risk management and portfolio optimization rather than directly predicting returns when data are scarce.
- Prefer simpler, more explainable models like regression trees or piecewise-linear models for deployability and interpretability.
Pre-Training And Joint Models Reduce Data Needs
- Generative AI lets you pre-train on vast unrelated data to overcome financial data scarcity via transfer learning.
- Modeling the input distribution P(X) or joint P(X,Y) provides a stronger prior than discriminative-only approaches.
