Ross Recovery and the Contemporaneous Pricing Kernel

2021 ◽  
Author(s):  
Marie-Hélène Gagnon ◽  
Gabriel Power ◽  
Dominique Toupin
Keyword(s):  
Pricing Kernel

The payoff and implied pricing kernel in REITs

2008 ◽  
Vol 40 (21) ◽  
pp. 2775-2783
Author(s):  
Hsiao-Tang Hsu
Keyword(s):  
Pricing Kernel

scholarly journals Estimates of foreign exchange risk premia: a pricing kernel approach

2007 ◽  
Vol 35 (3) ◽  
pp. 475-495 ◽  
Author(s):  
Lorenzo Cappiello ◽  
Nikolaos Panigirtzoglou
Keyword(s):  
Foreign Exchange ◽  
Risk Premia ◽  
Pricing Kernel ◽  
Foreign Exchange Risk ◽  
Exchange Risk ◽  
Kernel Approach

A Bayesian Estimate of the Pricing Kernel

2016 ◽  
Author(s):  
Chiara Legnazzi ◽  
Giovanni Barone-Adesi ◽  
Antonietta Mira
Keyword(s):  
Bayesian Estimate ◽  
Pricing Kernel

scholarly journals Forecasting The Pricing Kernel of IBNR Claims Development In Property-Casualty Insurance

2021 ◽  
Author(s):  
Godfrey Cadogan
Keyword(s):  
Pricing Kernel ◽  
Property Casualty

Forecasting The Pricing Kernel of IBNR Claims Development In Property-Casualty Insurance

scholarly journals Forecasting The Pricing Kernel of IBNR Claims Development In Property-Casualty Insurance

2021 ◽  
Author(s):  
Godfrey Cadogan
Keyword(s):  
Pricing Kernel ◽  
Property Casualty

Forecasting The Pricing Kernel of IBNR Claims Development In Property-Casualty Insurance

scholarly journals Relative Entropy and Minimum-Variance Pricing Kernel in Asset Pricing Model Evaluation

Entropy ◽  
2020 ◽  
Vol 22 (7) ◽  
pp. 721
Author(s):  
Javier Rojo-Suárez ◽  
Ana Belén Alonso-Conde
Keyword(s):  
Asset Pricing ◽  
Relative Entropy ◽  
Explanatory Power ◽  
Minimum Variance ◽  
Pricing Models ◽  
Pricing Kernel ◽  
Cross Sectional ◽  
Testing Procedures ◽  
Asset Pricing Models ◽  
Leibler Divergence

Recent literature shows that many testing procedures used to evaluate asset pricing models result in spurious rejection probabilities. Model misspecification, the strong factor structure of test assets, or skewed test statistics largely explain this. In this paper we use the relative entropy of pricing kernels to provide an alternative framework for testing asset pricing models. Building on the fact that the law of one price guarantees the existence of a valid pricing kernel, we study the relationship between the mean-variance efficiency of a model’s factor-mimicking portfolio, as measured by the cross-sectional generalized least squares (GLS) R 2 statistic, and the relative entropy of the pricing kernel, as determined by the Kullback–Leibler divergence. In this regard, we suggest an entropy-based decomposition that accurately captures the divergence between the factor-mimicking portfolio and the minimum-variance pricing kernel resulting from the Hansen-Jagannathan bound. Our results show that, although GLS R 2 statistics and relative entropy are strongly correlated, the relative entropy approach allows us to explicitly decompose the explanatory power of the model into two components, namely, the relative entropy of the pricing kernel and that corresponding to its correlation with asset returns. This makes the relative entropy a versatile tool for designing robust tests in asset pricing.

ELW pricing kernel and empirical risk aversion

2014 ◽  
Vol 21 (5) ◽  
pp. 372-376 ◽  
Author(s):  
Jun Sik Kim ◽  
Hyeyoen Kim ◽  
Doojin Ryu
Keyword(s):  
Risk Aversion ◽  
Pricing Kernel ◽  
Empirical Risk
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