Serhiy Kozak (Maryland): When do cross-sectional asset pricing factors span the stochastic discount factor

We are excited to resume the in person seminar series of the Advanced Financial Technologies Laboratory (AFTLab). Please join us for the next AFTLab seminar:

Time: Thursday, May 12, 2022, 5:00pm-6:00pm
Location: Huang 305
Speaker: Serhiy Kozak, University of Maryland

Title: When do cross-sectional asset pricing factors span the stochastic discount factor? 

Abstract:
When expected returns are linear in asset characteristics, the stochastic discount factor (SDF) that prices individual stocks can be represented as a factor model with GLS cross-sectional regression slope factors. Factors constructed heuristically by aggregating individual stocks into characteristics-based factor portfolios using sorting, characteristics-weighting, or OLS cross-sectional regression slopes do not span this SDF unless the covariance matrix of stock returns has a specific structure. These conditions are more likely satisfied when researchers use large numbers of characteristics simultaneously. Methods to hedge unpriced components of heuristic factor returns allow partial relaxation of these conditions. We also show the conditions that must hold for dimension reduction to a number of factors smaller than the number of characteristics to be possible without having to invert a large covariance matrix. Under these conditions, instrumented and projected principal components analysis methods can be implemented as simple PCA on certain portfolio sorts.

Bio:
Serhiy Kozak is an assistant professor of finance at the Robert H. Smith School of Business at the University of Maryland. Prior to that, he was an assistant professor of finance at the University of Michigan, Ross School of Business. His current research focuses on embedding economic and asset pricing restrictions into machine learning methods to study the dynamics of asset prices. Serhiy earned his PhD at the University of Chicago in 2013.