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Factor Models of Stock Returns: GARCH Errors versus Time - Varying Betas

Phoebe Koundouri (), Nikolaos Kourogenis (), Nikitas Pittis () and Panagiotis Samartzis
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Nikitas Pittis: University of Piraeus, Greece

No 1409, DEOS Working Papers from Athens University of Economics and Business

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.

Keywords: autoregressive beta; stock returns; single factor model; conditional heteroscedasticity; in-sample performance; out-of-sample performance (search for similar items in EconPapers)
JEL-codes: C22 G10 G11 G12 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ets and nep-ger
Date: 2014-09-17
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Related works:
Journal Article: Factor Models of Stock Returns: GARCH Errors versus Time‐Varying Betas (2016) Downloads
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