Teaching Economics to the Machines | School of Management and Economics

Topic:	Teaching Economics to the Machines
Time&Date:	10:30 am -12:00 pm, June 26, 2025 (Thursday)
Venue	Room D804, Teaching Complex D Building
Speaker:	Hui Chen Massachusetts Institute of Technology
Abstract:	Structural models in economics often suffer from a poor fit with the data and demonstrate suboptimal forecasting performances. Machine learning models, in contrast, offer rich flexibility but are prone to overfitting and struggle to generalize beyond the confines of training data. We propose a transfer learning framework that incorporates economic restrictions from a structural model into a machine learning model. Specifically, we first construct a neural network representation of the structural model by training on the synthetic data generated by the structural model and then fine-tune the network using empirical data. When applied to option pricing, the transfer learning model significantly outperforms the structural model, a conventional deep neural network, and several alternative approaches for bringing in economic restrictions. The out-performance is more significant i) when the sample size of empirical data is small, ii) when market conditions change relative to the training data, or iii) when the degree of structural model misspecification is likely to be low.
Biography:	Hui Chen is the Nomura Professor of Finance at the MIT Sloan School of Management. His research focuses on asset pricing and its connections with corporate finance. Chen is particularly interested in the interactions between the macro economy and term structure, credit risk, and corporate financing or investment decisions. His recent research projects include application of business cycle models to explain corporate financing behavior and corporate bond pricing, as well as analysis of the effects of incomplete markets on entrepreneurial financing and investments. Chen holds a BA in economics and finance from Zhongshan University, an MS in mathematics from the University of Michigan, and a PhD in finance from the University of Chicago.