Journal of Financial and Quantitative Analysis Vol. 60 No. 3 2025

Factor Model Comparisons with Conditioning Information

Wayne E. Ferson¹; Andrew F. Siegel²; Junbo L. Wang³

¹ University of Southern California, and a Research Associate at the National Bureau of Economic Research · ² University of Washington Foster School of Business Finance and Business Economics and Information Systems and Operations Management · ³ Louisiana State University

Abstract

We develop methods for testing factor models when the weights in portfolios of factors and test assets can vary with lagged information. We derive and evaluate consistent standard errors and finite sample bias adjustments for unconditional maximum squared Sharpe ratios and their differences. Bias adjustment using a second-order approximation performs well. We derive optimal zero-beta rates for models with dynamically trading portfolios. Factor models’ Sharpe ratios are larger but standard test asset portfolios’ maximum Sharpe ratios are larger still when there is dynamic trading. As a result, most of the popular factor models are rejected.

DOI

10.1017/s002210902400005x

Volume

60

Issue

3

Pages

1401-1426

Language

en

Sources

bibtex:phds-export.bib openalex crossref

Cite

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