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The sum of two independent polynomially-modified hyperbolic secant random variables with application in computational finance
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作者 a.a.l.zadeh Hojatollah Zakerzadeh Hamzeh Torabi 《International Journal of Modeling, Simulation, and Scientific Computing》 EI 2021年第4期201-214,共14页
In this paper,by reshaping the hyperbolic secant distribution using Hermite polynomial,we devise a polynomially-modified hyperbolic secant distribution which is more flexible than secant distribution to capture the s... In this paper,by reshaping the hyperbolic secant distribution using Hermite polynomial,we devise a polynomially-modified hyperbolic secant distribution which is more flexible than secant distribution to capture the skewness,heavy-tailedness and kurtosis of data.As a portfolio possibly consists of multiple assets,the distribution of the sum of independent polynomially-modified hyperbolic secant random variables is derived.In exceptional cases,we evaluate risk measures such as value at risk and expected shortfall(ES)for the sum of two independent polynomially-modified hyperbolic secant random variables.Finally,using real datasets from four international computers stocks,such as Adobe Systems,Microsoft,Nvidia and Symantec Corporations,the effectiveness of the proposed model is shown by the goodness of Gram–Charlier-like expansion of hyperbolic secant law,for performance of value at risk and ES estimation,both in and out of the sample period. 展开更多
关键词 Expected shortfall Gram–Charlier-like expansions heavy tailed distributions value at risk
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