Does Smooth Ambiguity Matter for Asset Pricing?

A. Gallant, Mohammad Jahan-Parvar and Hening Liu

No 1221, International Finance Discussion Papers from Board of Governors of the Federal Reserve System (U.S.)

Abstract: We use the Bayesian method introduced by Gallant and McCulloch (2009) to estimate consumption-based asset pricing models featuring smooth ambiguity preferences. We rely on semi-nonparametric estimation of a flexible auxiliary model in our structural estimation. Based on the market and aggregate consumption data, our estimation provides statistical support for asset pricing models with smooth ambiguity. Statistical model comparison shows that models with ambiguity, learning and time-varying volatility are preferred to the long-run risk model. We analyze asset pricing implications of the estimated models.

Keywords: Ambiguity; Bayesian estimation; equity premiums; Markov-switching; long-run risks (search for similar items in EconPapers)
JEL-codes: C61 D81 G11 G12 (search for similar items in EconPapers)
Pages: 83 pages
Date: 2018-01
New Economics Papers: this item is included in nep-rmg and nep-upt
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.federalreserve.gov/econres/ifdp/files/ifdp1221.pdf (application/pdf)

Related works:
Journal Article: Does Smooth Ambiguity Matter for Asset Pricing? (2019)
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:fip:fedgif:1221

DOI: 10.17016/IFDP.2018.1221

Access Statistics for this paper

More papers in International Finance Discussion Papers from Board of Governors of the Federal Reserve System (U.S.) Contact information at EDIRC.
Bibliographic data for series maintained by Ryan Wolfslayer ; Keisha Fournillier ().