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动态系统性风险测度的多元推断AI 解读

This paper provides statistical inference for marginal expected shortfall (MES) and delta conditional value-at-risk (ΔCoVaR) measures, which are semiparametrically estimated by a two-step procedure in a multivariate GARCH-type framework. We establish the asymptotic properties of corresponding estimators and illustrate how the estimation uncertainty can be decomposed into dynamic univariate marginal and time-varying dependence components. Our methodology reveals good finite…

带人工动态的自组织状态空间模型AI 解读

Abstract We consider the problem of performing parameter and state inference in a state-space model (SSM) parametrized by a static parameter θ. A popular idea to address this problem consists of incorporating θ in the state of the system and allowing its time evolution, modelled as a Markov chain (θt)t≥1. This proxy model defines a so-called self-organizing SSM (SO-SSM) to which one may apply standard particle filters. However, the practical implementation of this idea in a…