Testing Beta-Pricing Models Using Large Cross-Sections

Valentina Raponi, Cesare Robotti, Paolo Zaffaroni and Andrew Karolyi

The Review of Financial Studies, 2020, vol. 33, issue 6, 2796-2842

Abstract: We propose a methodology for estimating and testing beta-pricing models when a large number of assets is available for investment but the number of time-series observations is fixed. We first consider the case of correctly specified models with constant risk premia, and then extend our framework to deal with time-varying risk premia, potentially misspecified models, firm characteristics, and unbalanced panels. We show that our large cross-sectional framework poses a serious challenge to common empirical findings regarding the validity of beta-pricing models. In the context of pricing models with Fama-French factors, firm characteristics are found to explain a much larger proportion of variation in estimated expected returns than betas.Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

JEL-codes: C12 C52 G12 (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
http://hdl.handle.net/10.1093/rfs/hhz064 (application/pdf)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:oup:rfinst:v:33:y:2020:i:6:p:2796-2842.

Ordering information: This journal article can be ordered from
https://academic.oup.com/journals

Access Statistics for this article

The Review of Financial Studies is currently edited by Itay Goldstein

More articles in The Review of Financial Studies from Society for Financial Studies Oxford University Press, Journals Department, 2001 Evans Road, Cary, NC 27513 USA.. Contact information at EDIRC.
Bibliographic data for series maintained by Oxford University Press ().