A Step Towards Demystifying High-Beta Stocks Asset Pricing Puzzles: A New Bootstrap Pricing Error Test for High-Beta Stocks Under Conditional Correlation and Heteroskedasticity

35 Pages Posted: 20 Dec 2017

See all articles by Klaus Grobys

Klaus Grobys

University of Vaasa; University of Jyväskyla

Date Written: December 12, 2017

Abstract

High-beta stocks seem to be an asset pricing mystery involving puzzles that have been intensively discussed in the most recent finance literature (Christoffersen and Simutin, 2017; Moreira and Muir, 2017). This papers derives novel implications for pricing high-beta stocks in the presence of dynamic correlations and conditional heteroskedasticity. First, it establishes that the widely-used asymptotic Gibbons, Ross, Shanken (1989) test statistic fails as an asset pricing test when applied to high-beta stocks because it dramatically overrejects the null hypothesis. Second, it proposes a new bootstrap procedure that considerably lowers the size distortions and that under certain scenarios generates the correct size in line with the stringent criterion for robustness (Bradley, 1978; Serlin, 2000).

Keywords: GRS test, Wald test, dynamic correlation, conditional heteroskedasticity

JEL Classification: C12, C15

Suggested Citation

Grobys, Klaus, A Step Towards Demystifying High-Beta Stocks Asset Pricing Puzzles: A New Bootstrap Pricing Error Test for High-Beta Stocks Under Conditional Correlation and Heteroskedasticity (December 12, 2017). Available at SSRN: https://ssrn.com/abstract=3088410 or http://dx.doi.org/10.2139/ssrn.3088410

Klaus Grobys (Contact Author)

University of Vaasa ( email )

P.O. Box 700
Wolffintie 34
FIN-65101 Vaasa
Finland

University of Jyväskyla ( email )

Jyväskyla
Finland

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