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A reduced rank regression approach to tests of asset pricing

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  • Michele Costa
  • Attilio Gardini
  • Paolo Paruolo

Abstract

Both the Arbitrage Pricing Theory (APT) and the Capital Asset Pricing Model (CAPM) place restrictions of the cross sectional variation of conditional expectations of asset returns and of macro-indicators. The authors show that these restrictions imposed on the reference statistical models lead to special cases of the reduced rank regression model. The maximum likelihood problem is solved by canonical correlation analysis. Likelihood ratio tests about the number of factors underlying stock returns are straightforward to calculate, thus allowing to discriminate between competing financial theories. Moreover LR tests on the relevance of each macroeconomic indicator within a chosen model can be implemented. Some of the tests are illustrated by an application to Italian stock market data. Copyright 1997 by Blackwell Publishing Ltd
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  • Michele Costa & Attilio Gardini & Paolo Paruolo, 1992. "A reduced rank regression approach to tests of asset pricing," Quaderni di Dipartimento 5, Department of Statistics, University of Bologna.
    • Handle: RePEc:bot:quadip:wpaper:48
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    Cited by:

    1. W. M. Tang & K. F. C. Yiu & H. Wong, 2020. "Subset Selection Using Frequency Decomposition with Applications," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 195-220, March.
    2. Francisco J. Goerlich-Gisbert, 1999. "Shocks agregados versus shocks sectoriales. Un análisis factorial dinámico," Investigaciones Economicas, Fundación SEPI, vol. 23(1), pages 27-53, January.
    3. Peter Hansen, 2002. "Generalized Reduced Rank Regression," Working Papers 2002-02, Brown University, Department of Economics.
    4. Scott Gilbert & Petr Zemčík, 2005. "Testing for Latent Factors in Models with Autocorrelation and Heteroskedasticity of Unknown Form," Southern Economic Journal, John Wiley & Sons, vol. 72(1), pages 236-252, July.

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