Dollars and Jens
Saturday, May 01, 2010
Econometric Errors in Factor Models
A lot of my favorite papers demonstrate common econometric errors by using the econometric techniques to derive results from random data. There's a new example in this month's issue of the Journal of Financial Economics:
It has become standard practice in the cross-sectional asset pricing literature to evaluate models based on how well they explain average returns on size-B/M portfolios, something many models seem to do remarkably well. In this paper, we review and critique the empirical methods used in the literature. We argue that asset pricing tests are often highly misleading, in the sense that apparently strong explanatory power (high cross-sectional R2s and small pricing errors) can provide quite weak support for a model. We offer a number of suggestions for improving empirical tests and evidence that several proposed models do not work as well as originally advertised.
An important law of applied econometrics, especially in a setting in which the correlation structure is poorly understood, is that no matter how many corrections you include in your standard error calculations, your calculated standard errors will be too low.

For the record, Lewellen got his PhD from the program I'm in at the University of Rochester while Shanken was a professor here.


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