Shrinking Factor Dimension: A Reduced-Rank Approach

62 Pages Posted: 23 Jul 2018 Last revised: 17 Oct 2019

See all articles by Dashan Huang

Dashan Huang

Singapore Management University - Lee Kong Chian School of Business

Jiaen Li

Washington University in St. Louis

Guofu Zhou

Washington University in St. Louis - John M. Olin Business School; China Academy of Financial Research (CAFR)

Date Written: October 17, 2019

Abstract

We propose a reduced-rank approach to reduce a large number of factors to a few parsimonious ones. It is designed to explain the cross section of stock returns, more suitable than principal component analysis and partial least squares in factor dimension reduction. Out of 70 factor proxies, we find that the best five combinations of them seem adequate. However, they do not improve much for pricing individual stocks, though they outperform the Fama-French (2015) five factors for pricing industry portfolios as expected. Our results suggest that new factors are wanted to reduce the pricing errors at the firm level.

Keywords: reduced rank, PCA, PLS, factors, factor model, cross section

JEL Classification: G1, G11, G12, G17

Suggested Citation

Huang, Dashan and Li, Jiaen and Zhou, Guofu, Shrinking Factor Dimension: A Reduced-Rank Approach (October 17, 2019). Available at SSRN: https://ssrn.com/abstract=3205697 or http://dx.doi.org/10.2139/ssrn.3205697

Dashan Huang

Singapore Management University - Lee Kong Chian School of Business ( email )

50 Stamford Road
Singapore, 178899
Singapore

HOME PAGE: http://dashanhuang.weebly.com/

Jiaen Li

Washington University in St. Louis ( email )

One Brookings Drive
Campus Box 1208
Saint Louis, MO MO 63130-4899
United States

Guofu Zhou (Contact Author)

Washington University in St. Louis - John M. Olin Business School ( email )

Washington University
Campus Box 1133
St. Louis, MO 63130-4899
United States
314-935-6384 (Phone)
314-658-6359 (Fax)

HOME PAGE: http://apps.olin.wustl.edu/faculty/zhou/

China Academy of Financial Research (CAFR)

Shanghai Advanced Institute of Finance
Shanghai P.R.China, 200030
China

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