A Performance Comparison of Large-n Factor Estimators
Tsinghua University - PBC School of Finance
London School of Economics & Political Science (LSE) - Department of Accounting and Finance
Robert A. Korajczyk
Northwestern University - Kellogg School of Management
November 10, 2014
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
Date posted: January 18, 2014 ; Last revised: November 11, 2014
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