The Term Structures of Coentropy in International Financial Markets
提出一种基于熵的新相关性度量（协同熵），用于评估国际资产定价模型，发现国际随机贴现因子的协同熵可分解为永久和暂时成分的熵相关，并用G-10国家数据验证了长期风险模型能解释各期限的协同依赖结构。
We propose a new entropy-based correlation measure (coentropy) to evaluate the performance of international asset pricing models. Coentropy captures the codependence of two random variables beyond normality. We document that the coentropy of international stochastic discount factors (SDFs) can be decomposed into a series of entropy-based correlations of permanent and transitory components of the SDFs. We employ the cross section of G-10 countries to obtain model-free estimates of all the components of coentropy at various horizons and we show that the generalization of the long-run risk model featuring two predictable components of consumption growth rates, global disasters, and recursive preferences can account for the composition of codependence at all horizons. This paper was accepted by Tomasz Piskorski, finance.