Abstract

http://ssrn.com/abstract=2380144
 


 



A Performance Comparison of Large-n Factor Estimators


Zhuo Chen


Tsinghua University - PBC School of Finance

Gregory Connor


London School of Economics & Political Science (LSE) - Department of Accounting and Finance

Robert A. Korajczyk


Northwestern University - Kellogg School of Management

November 10, 2014


Abstract:     
We evaluate the performance of various methods for estimating factor returns in an approximate factor model when the cross-sectional sample can be large relative to the time-series sample. We find that 1) most estimators perform well, even when they do not accommodate the form of heteroskedasticity present in the data; 2) for the sample sizes considered here, accommodating heteroskedasticity does not deteriorate performance much when simple forms of heteroskedasticity are present; 3) estimators that handle missing data by substituting fitted returns from the factor model converge to the true factors more slowly than the other estimators.

Number of Pages in PDF File: 31

Keywords: Factor Model, Asymptotic Principal Components, Large-Scale Factor Model

JEL Classification: G1, G12, C15, C23

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Date posted: January 18, 2014 ; Last revised: November 11, 2014

Suggested Citation

Chen, Zhuo and Connor, Gregory and Korajczyk, Robert A., A Performance Comparison of Large-n Factor Estimators (November 10, 2014). Available at SSRN: http://ssrn.com/abstract=2380144 or http://dx.doi.org/10.2139/ssrn.2380144

Contact Information

Zhuo Chen
Tsinghua University - PBC School of Finance ( email )
43 Chengfu Road
Beijing, 100083
China
Gregory Connor
London School of Economics & Political Science (LSE) - Department of Accounting and Finance ( email )
Houghton Street
London WC2A 2AE
United Kingdom
+44 702 955-6407 (Phone)
+44 702 955-7420 (Fax)
Robert A. Korajczyk (Contact Author)
Northwestern University - Kellogg School of Management ( email )
2001 Sheridan Road
Evanston, IL 60208
United States
847-491-8336 (Phone)
847-491-5719 (Fax)
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