No abstract

No abstract

No abstract

No abstract

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.