熵风险度量非参数估计的渐近行为

扬州大学本科毕业生论文Asymptotic behavior of nonparametric estimation in entropic risk measureAbstract In recent years,the development of the world's financial economy is faster and faster,and the scale,speed,complexity and dynamics of the financial market are increasing.Therefore,the financial and regulatory institutions pay more and more attention to the risk management ofthe financial market,and the risk management technology is increasingly valued.Therefore,it hasbecome the focus of attention,and the research of risk measurement theory is also of greatsignificance.So far,some domestic and foreign scientists and experts have put forward some riskassessment methods,such as online value at risk method,conditional value at risk method andentropy risk measurement method.Those scholars and experts have provided a very reliabletheoretical support in risk assessment.This paper mainly studies the estimation and asymptoticbehavior of the empirical distribution function of entropy risk measurement.This article can be divided into five chapters,the structure is as follows:The first chapter summing up the backdrop of the research,and analyzes the currentsituation of the concept of internal and extemal risk assessment.The second chapter outlines some common risk assessment methods and key theoreticalelements,as well as the basic concepts of risk assessment and online value,Assume the cost ofthe risk and the associated characteristics.The third chapter summarizes the existing nonparametric estimation methods,includingempirical distribution function method,histogram method and kernel density estimation method.The fourth chapter the empirical distribution function of entropic risk measure is estimatedand its asymptotic behavior is analyzed firstly,and then the kernel density estimation of entropicrisk measure and its asymptotic behavior are obtained.The fifth chapter summarizes the whole article.Key words Risk measure Entropic risk measureNonparametric estimation Empiricaldistribution function