Does Smooth Ambiguity Matter for Asset Pricing?

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 cons...

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Bibliographic Details
Main Authors: Jahan-Parvar, M.R (Author), Liu, H. (Author), Ronald Gallant, A. (Author)
Format: Article
Language:English
Published: Oxford University Press 2019
Online Access:View Fulltext in Publisher
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008 220511s2019 CNT 000 0 und d
020 |a 08939454 (ISSN) 
245 1 0 |a Does Smooth Ambiguity Matter for Asset Pricing? 
260 0 |b Oxford University Press  |c 2019 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1093/rfs/hhy118 
520 3 |a 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 also analyze asset pricing implications of the estimated models. Received April 12, 2016; editorial decision September 11, 2018 by Editor Stijn Van Nieuwerburgh. 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. © 2018 Published by Oxford University Press on behalf of The Society for Financial society (2018). 
700 1 |a Jahan-Parvar, M.R.  |e author 
700 1 |a Liu, H.  |e author 
700 1 |a Ronald Gallant, A.  |e author 
773 |t Review of Financial Studies