Evaluating asset pricing models with non-traded factors using the method of maximum-correlated portfolios
Ge Yang,
Ximing Yin and
Robert L. Kimmel
The North American Journal of Economics and Finance, 2023, vol. 68, issue C
Abstract:
This paper examines the performance of several important asset pricing models with non-traded factors. We propose to test the asset pricing models using the method of Maximum-Correlated (MC) Portfolios. This method is particularly useful when evaluating models with non-traded factors, where the models are potentially mis-specified and factors are possibly noisy. The Q-statistics and Sharpe ratios, derived from MC portfolio method, are used as the goodness-of-fit measures. Smaller Q-stats and higher Sharpe ratios indicate better model performance. We find that Campbell (1996) and Jagannathan and Wang (1996) models are among the best models to price the test assets. These results differ significantly from the existing methods which may be biased by noisy factors.
Keywords: Maximum-correlated portfolios; Non-traded factor models; Sharpe ratios (search for similar items in EconPapers)
JEL-codes: C58 G12 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1062940823001031
Full text for ScienceDirect subscribers only
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:eee:ecofin:v:68:y:2023:i:c:s1062940823001031
DOI: 10.1016/j.najef.2023.101980
Access Statistics for this article
The North American Journal of Economics and Finance is currently edited by Hamid Beladi
More articles in The North American Journal of Economics and Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().