Agostino Capponi to Deliver Keynote on AI Limits and Market Nonstationarity at Fordham Quant 2026
QuantVision 2026: Fordham’s Quantitative Conference
Agostino Capponi is a professor of financial technology and analytics at Columbia University and the director of the Center for Digital Finance and Technologies. His research sits at the intersection of fintech artificial intelligence in finance market microstructure economic and financial networks and portfolio management with a strong focus on how modern data driven methods behave in real world financial markets.
In two months Professor Capponi will deliver a keynote address at the Fordham Quant 2026 Conference. His talk titled When More Data Hurts Navigating the Nonstationarity Complexity Tradeoff in Return Prediction will examine a critical and timely problem in quantitative finance. As datasets grow larger and models become more complex predictive performance does not always improve. In financial markets changing regimes structural breaks and feedback effects can cause sophisticated models to fail precisely when they appear most powerful.
His keynote will explore why nonstationarity fundamentally alters the data versus complexity tradeoff how excessive model flexibility can amplify noise and instability and what this means for return prediction portfolio construction and AI driven investment systems. The talk is expected to resonate strongly with quantitative researchers portfolio managers and data scientists working at the frontier of machine learning and finance.
Professor Capponi’s upcoming keynote reflects his broader work on building robust financial models that acknowledge market dynamics rather than assuming static statistical relationships. The session will be one of the highlights of Fordham Quant 2026.
QuantVision 2026: Fordham’s Quantitative Conference
