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Nfa For Factor Number Determination In Apt

Author

Listed:
  • KAI-CHUN CHIU

    (Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, P.R. China)

  • LEI XU

    (Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, P.R. China)

Abstract

In the context of quantitative analysis of the arbitrage pricing theory (APT) model, conventional factor analytic approaches such as maximum likelihood factor analysis (MLFA) cannot provide satisfactory answers to two important questions. The first one concerns the correct identification of factor number while the second one is related to the rotation indeterminacy of factor loadings. In the literature, MLFA followed by likelihood ratio (LR) test and the analysis of eigenvalues of sample covariance matrix were two popular approaches used to determine the appropriate number of factors. However, it was shown empirically that both of them suffered from different kinds of biases. We find the recently developed non-gaussian factor analysis (NFA) model by Xu [24] provides a new perspective for the determination of the appropriate factor numberkin APT, with promising empirical results demonstrated.

Suggested Citation

  • Kai-Chun Chiu & Lei Xu, 2004. "Nfa For Factor Number Determination In Apt," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 7(03), pages 253-267.
    • Handle: RePEc:wsi:ijtafx:v:07:y:2004:i:03:n:s021902490400244x
    DOI: 10.1142/S021902490400244X
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