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Factor models of stock returns: GARCH errors versus time-varying betas

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  • Koundouri, Phoebe
  • Kourogenis, Nikolaos
  • Pittis, Nikitas
  • Samartzis, Panagiotis

Abstract

This paper investigates the implications of time-varying betas in factor models for stock returns. It is shown that a single-factor model (SFMT) with autoregressive betas and homoscedastic errors (SFMT-AR) is capable of reproducing the most important stylized facts of stock returns. An empirical study on the major US stock market sectors shows that SFMT-AR outperforms, in terms of in-sample and out-of-sample performance, SFMT with constant betas and conditionally heteroscedastic (GARCH) errors, as well as two multivariate GARCH-type models.

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  • Koundouri, Phoebe & Kourogenis, Nikolaos & Pittis, Nikitas & Samartzis, Panagiotis, 2016. "Factor models of stock returns: GARCH errors versus time-varying betas," LSE Research Online Documents on Economics 65548, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:65548
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    2. Blasques, F. & Francq, Christian & Laurent, Sébastien, 2024. "Autoregressive conditional betas," Journal of Econometrics, Elsevier, vol. 238(2).

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    More about this item

    Keywords

    autoregressive beta; stock returns; single factor model; conditional heteroscedasticity; in-sample performance; out-of-sample performance;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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