A conditional regime switching CAPM

Vendrame, Vasco; Guermat, Cherif; Tucker, Jon

Abstract

© 2017 Elsevier Inc. The standard Capital Asset Pricing Model (CAPM) is simple, intuitive, and grounded in sound economic theory. Yet, almost half a century's worth of empirical testing has so far failed to demonstrate its relevance. One major reason given for the CAPM's empirical failure is that beta is not the sole measure of systematic risk. In other words, the standard CAPM does not hold. Another important explanation is that the CAPM may hold conditionally rather than unconditionally. The standard CAPM fails to explain the cross-section of returns because it ignores the fact that both the risk and the price of risk are time-varying. The search for conditional models has led researchers to either disregard the theory behind the CAPM or to use statistical procedures that are too complex to be replicated by other researchers and practitioners. In this paper we propose a conditional model that is compatible with the standard CAPM while remaining simple and accessible to both researchers and practitioners. Beta and the risk premium are assumed to be time-varying, with the latter being associated with bull and bear states. We find strong support for the conditional CAPM with beta explaining both bull and bear markets. While the bear market ex-post risk premium is negative, the weighted average risk premium is positive and highly significant.

• Journal Article Type: Article
• Acceptance Date: Dec 11, 2017
• Online Publication Date: Dec 12, 2017
• Publication Date: Mar 1, 2018
• Deposit Date: Dec 12, 2017
• Publicly Available Date: Jun 12, 2019
• Journal: International Review of Financial Analysis
• Print ISSN: 1057-5219
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 56
• Pages: 1-11
• DOI: https://doi.org/10.1016/j.irfa.2017.12.001
• Keywords: asset pricing, conditional CAPM, regime-switching, bull market, bear market
• Public URL: https://uwe-repository.worktribe.com/output/856015
• Publisher URL: https://doi.org/10.1016/j.irfa.2017.12.001
• Contract Date: Dec 12, 2017