Robust Inference for Consumption‐Based Asset Pricing

Frank Kleibergen and Zhaoguo Zhan

Journal of Finance, 2020, vol. 75, issue 1, 507-550

Abstract: The reliability of traditional asset pricing tests depends on: (i) the correlations between asset returns and factors; (ii) the time series sample size T compared to the number of assets N. For macro‐risk factors, like consumption growth, (i) and (ii) are often such that traditional tests cannot be trusted. We extend the Gibbons‐Ross‐Shanken statistic to test identification of risk premia and construct their 95% confidence sets. These sets are wide or unbounded when T and N are close, but show that average returns are not fully spanned by betas when T exceeds N considerably. Our findings indicate when meaningful empirical inference is feasible.

Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (33)

Downloads: (external link)
https://doi.org/10.1111/jofi.12855

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:bla:jfinan:v:75:y:2020:i:1:p:507-550

Ordering information: This journal article can be ordered from
http://www.afajof.org/membership/join.asp

Access Statistics for this article

More articles in Journal of Finance from American Finance Association Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().