The 20th Academic Luncheon of the Digital Technology and Finance

Abstract：

We propose a new approach to construct factors from firm characteristics. In contrast to existing studies, each of our factors comes from the same group of statistically related firm characteristics, making its economic interpretation possible. The number of groups is not chosen ad hocly, but rather determined by data. Applying our method to a set of 94 representative firm characteristics, we find that the factors chosen by our approach is not only easy to interpret economically, but the associated factor model outperforms existing models. We also apply our approach to the recent developed and highly effective IPCA model of Kelly, Pruitt and Su (2019), and find that our factors not only are well linked to the associated economic risks, but also can price assets no worse than the standard IPCA latent factors that are difficult to interpret. 

Speaker Introduction：

Yuxiao Jiao is a Ph.D. candidate in the Department of Finance, School of Economics and Management, Tsinghua University. His research focuses on empirical asset pricing and machine learning. His papers have been accepted by more than ten academic conferences, including the American Finance Association (AFA), the Midwest Finance Association Annual Meeting (MFA), and the Chinese Finance Association Annual Conference. His job-hunting paper was awarded as the "Excellent Paper" by the 2024 Chinese Finance Doctoral Student Graduation Intention Exchange.