CAJ | 학술논문

本文利用我国随机分析与计算领域的国际领先成果，结合有关风险与不确定性的哲学一经济学经典理论，创建了新的概率统计分布模型——随机极限正态分布。进而，在此基础上提出了审慎性风险监管指标R-VaR和R-ES。论文旨在为解决长久困扰金融监管界与实业界的厚尾风险建模测度问题提供开拓性的理论与实证支持。
본문이용아국수궤분석여계산영역적국제령선성과，결합유관풍험여불학정성적철학일경제학경전이론，창건료신적개솔통계분포모형——수궤겁한정태분포。진이，재차기출상제출료심신성풍험감관지표R-VaR화R-ES。논문지재위해결장구곤우금융감관계여실업계적후미풍험건모측도문제제공개탁성적이론여실증지지。
The paper introduces a new distribution to improve tail risk modelling. We first demonstrate that the fundamental model of risk metrics, like VaR and ES, which leads to their inability to measure risk in a realistic, dynamic economic environment. Then, random limit normal distribution model is proven to be more effective for measuring and managing risk in the real business world. By employing the new distribution, we then propose more prudential risk metrics —— R-VaR and R-ES.