Essays on Asset Pricing and Econometrics

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Essays on Asset Pricing and Econometrics

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Title: Essays on Asset Pricing and Econometrics
Author: Jin, Tao
Citation: Jin, Tao. 2014. Essays on Asset Pricing and Econometrics. Doctoral dissertation, Harvard University.
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Abstract: This dissertation presents three essays on asset pricing and econometrics. The first chapter identifies rare events and long-run risks simultaneously from a rich data set (the Barro-Ursua macroeconomic data set) and evaluates their contributions to asset pricing in a unified framework. The proposed model of rare events and long-run risks is estimated using a Bayesian Markov-chain Monte-Carlo method, and the estimates for the disaster process are closer to the data than those in the previous studies. Major evaluation results in asset pricing include: (1) for the unleveraged annual equity premium, the predicted values are 4.8%, 4.2%, and 1.0%, respectively; (2) for the Sharpe ratio, the values are 0.72, 0.66, and 0.15, respectively.
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:12269843
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