Sequential Tests of the Arbitrage Pricing Theory: A Comparison of Principal Components and Maximum Likelihood Factors




    Search for more papers by this author
    • Department of Business Administration and Economics, College at Brockport, SUNY and School of Management, University at Buffalo, SUNY, respectively. We would like to thank the participants in the Finance Workshops of Indiana University and the University at Buffalo for their comments. This paper was substantially improved by the thoughtful attention of the anonymous referee. Nevertheless, we do not hold anyone but ourselves responsible for the errors that undoubtedly remain.


We examine the cross-sectional pricing equation of the APT using the elements of eigenvectors and the maximum likelihood factor loadings of the covariance matrix of returns as measures of risk. The results indicate that, for data assumed stationary over twenty years, the first vector is a surprisingly good measure of risk when compared with either a one- or a five-factor model or a five-vector model. We conclude that in some circumstances principal components analysis may be preferred to factor analysis.