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Sequential Tests of the Arbitrage Pricing Theory: A Comparison of Principal Components and Maximum Likelihood Factors
Author(s) -
SHUKLA RAVI,
TRZCINKA CHARLES
Publication year - 1990
Publication title -
the journal of finance
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 18.151
H-Index - 299
eISSN - 1540-6261
pISSN - 0022-1082
DOI - 10.1111/j.1540-6261.1990.tb03727.x
Subject(s) - principal component analysis , factor analysis , arbitrage pricing theory , covariance matrix , econometrics , mathematics , measure (data warehouse) , eigenvalues and eigenvectors , covariance , arbitrage , principal (computer security) , factor (programming language) , statistics , capital asset pricing model , economics , financial economics , computer science , physics , quantum mechanics , database , programming language , operating system
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.