An International Perspective on Risk Management Quality
提出一种评估风险管理模型质量的新方法，通过检验未预期极端风险与海外极端风险的独立性，发现跨国风险传导的证据，并讨论如何将国际依赖性纳入模型以改进风险预测。
Abstract This paper introduces an alternative method for assessing the quality of risk management models. Specifically, using the forecast efficiency notion that forecast errors should be independent of a pertinent information set, we consider the extent to which unanticipated downside risk (extreme risk) is independent of overseas extreme risk. This is achieved using a bootstrap version of the non‐causality test recently introduced by Hong et al . ( ), data covering 45 international equity markets, and by measuring extreme risk via a class of risk management models recently introduced by Xiao and Koenker ( ). In doing this, we find significant evidence of transmission (causality) across national borders. Moreover, we discuss how risk managers in developed and emerging markets can parsimoniously incorporate such information (international dependency) into their risk management models to produce measures of downside risk that have more desirable ex post properties (viz. forecast efficiency properties).