<p>This dissertation explores issues regarding the short-lived temporal variation of the equity risk premium. In the past decade, the equity risk premium puzzle is resolved by many competing consumption-based asset pricing models. However, before \cite{btz:vrp:rfs}, the return predictability as an outcome of such models has limited empirical support in the short-run. Nowadays, there has been a consensus of the literature that the short-run equity return's predictability is intimately linked with the variance risk premium---the difference between options-implied and actual realized variation measures.</p><p>In this work, I continue to argue the importance of the short-lived components in the equity risk premium. Specifically, I first provide simulation evidence of the strong return predictability based on the variance risk premium in the U.S. aggregate market, and document new empirical findings in the international setting. Then I attempt to use a structural macro-finance model to guide through the predictability estimation with much more efficiency gain. Finally I decompose the equity risk premium into two short-lived parts --- tail risk and diffusive risk --- and propose a semi-parametric estimation method for each part. The results are arranged in the following order.</p><p>Chapter 1 of the dissertation is co-authored with Tim Bollerslev, James Marrone and Hao Zhou. In this chapter, we demonstrate that statistical finite sample biases cannot ``explain'' this apparent predictability in U.S. market based on variance risk premium. Further corroborating the existing evidence of the U.S., we show that country specific regressions for France, Germany, Japan, Switzerland, the Netherlands, Belgium and the U.K. result in quite similar patterns. Defining a ``global'' variance risk premium, we uncover even stronger predictability and almost identical cross-country patterns through the use of panel regressions. </p><p>Chapter 2 of the dissertation is co-authored with Tim Bollerslev and Hao Zhou. In this chapter, we examine the joint predictability of return and cash flow within a present value framework, by imposing the implications from a long-run risk model that allow for both time-varying volatility and volatility uncertainty. We provide new evidences that the expected return variation and the variance risk premium positively forecast both short-horizon returns \textit{and} dividend growth rates. We also confirm that dividend yield positively forecasts long-horizon returns, but that it does not help in forecasting dividend growth rates. Our equilibrium-based ``structural'' factor GARCH model permits much more accurate inference than %the reduced form VAR and</p><p>univariate regression procedures traditionally employed in the literature. The model also allows for the direct estimation of the underlying economic mechanisms, including a new volatility leverage effect, the persistence of the latent long-run growth component and the two latent volatility factors, as well as the contemporaneous impacts of the underlying ``structural'' shocks.</p><p>In Chapter 3 of the dissertation, I develop a new semi-parametric estimation method based on an extended ICAPM dynamic model incorporating jump tails. The model allows for time-varying, asymmetric jump size distributions and a self-exciting jump intensity process while avoiding commonly used but restrictive affine assumptions on the relationship between jump intensity and volatility. The estimated model implies that the average annual jump risk premium is 6.75\%. The model-implied jump risk premium also has strong explanatory power for short-to-medium run aggregate market returns. Empirically, I present new estimates of the model based equity risk premia of so-called "Small-Big", "Value-Growth" and "Winners-Losers" portfolios. Further, I find that they are all time-varying and all crashed in the 2008 financial crisis. Additionally, both the jump and volatility components of equity risk premia are especially important for the "Winners-Losers" portfolio.</p> / Dissertation
| Identifer | oai:union.ndltd.org:DUKE/oai:dukespace.lib.duke.edu:10161/8712 |
| Date | January 2014 |
| Creators | Xu, Lai |
| Contributors | Bollerslev, Tim |
| Source Sets | Duke University |
| Detected Language | English |
| Type | Dissertation |
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