منابع مشابه
Conditioning Information and Variance Bounds on Pricing Kernels
Gallant, Hansen, and Tauchen (1990) show how to use conditioning information optimally to construct a sharper unconditional variance bound (the GHT bound) on pricing kernels. The literature predominantly resorts to a simple but suboptimal procedure that scales returns with predictive instruments and computes standard bounds using the original and scaled returns. This article provides a formal b...
متن کاملOn Pricing Kernels and Dynamic Portfolios
We investigate the structure of the pricing kernels in a general dynamic investment setting by making use of their duality with the self financing portfolios. We generalize the variance bound on the intertemporal marginal rate of substitution introduced in Hansen and Jagannathan (1991) along two dimensions, first by looking at the variance of the pricing kernels over several trading periods, an...
متن کاملPricing Kernels with Stochastic Skewness and Volatility Risk
Online Appendix In this online appendix, I first provide a brief comparison of the small noise expansion series and the Taylor expansion series. I then use separably Taylor expansion series and the small noise expansion series to derive the pricing kernel in a one-market model with two dates, and the pricing kernel in a two-market model with three dates. I thereafter, investigate whether one ob...
متن کاملConditioning Information and Variance Bounds on Pricing Kernels with Higher-Order Moments: Theory and Evidence
The author develops a strategy for utilizing higher moments and conditioning information efficiently, and hence improves on the variance bounds computed by Hansen and Jagannathan (1991, the HJ bound) and Gallant, Hansen, and Tauchen (1990, the GHT bound). The author’s bound incorporates variance risk premia. It reaches the GHT bound when non-linearities in returns are not priced. The author als...
متن کاملTesting Monotonicity of Pricing Kernels
In this master thesis a mechanism to test mononicity of empirical pricing kernels (EPK) is presented. By testing monotonicity of pricing kernel we can determine whether utility function is concave or not. Strictly decreasing pricing kernel corresponds to concave utility function while non-decreasing EPK means that utility function contains some non-concave regions. Risk averse behavior is usual...
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ژورنال
عنوان ژورنال: Investment Analysts Journal
سال: 2015
ISSN: 1029-3523,2077-0227
DOI: 10.1080/10293523.2014.994437