Feb 1, 2018 12:30pm to 2:00pm
1011 Evans Hall
Happening As Scheduled
This papers deals with the approximation of latent statistical factors with sparse and easy-to-interpret proximate factors. Latent factors in a large-dimensional factor model can be estimated by principal component analysis, but are usually hard to interpret. By shrinking the factor weights, we obtain proximate factors that are easier to interpret. We show that proximate factors consisting of...
Speaker: Markus Pelger, Stanford (Speaker - Featured)