Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/239467 
Year of Publication: 
2021
Citation: 
[Journal:] Journal of Risk and Financial Management [ISSN:] 1911-8074 [Volume:] 14 [Issue:] 2 [Publisher:] MDPI [Place:] Basel [Year:] 2021 [Pages:] 1-19
Publisher: 
MDPI, Basel
Abstract: 
In this paper, we extend the parametric approach of VaR estimation that is based upon the application of two transforms, one for handling skewness and other for kurtosis. These transformations restore normality to data when applied in succession. The transforms are well defined and offer an alternative to VaR models based on the variance-covariance approach. We demonstrate the application of the technique using three pairs of uncorrelated but negatively skewed and fat-tailed stock return distributions, one pair each from recent periods in US and international market, and one from the stressed period of US economic history. Furthermore, we extend the analysis to economic domain by calculating expected shortfalls and risk capital under different estimation methods. For the sake of completion, we compare the estimation results of normal and transformation methods to non-parametric historical simulation.
Subjects: 
back-testing
expected shortfall
GARCH (1,1)
John and Draper transform
manly transform
normal distribution
risk capital
value-at-risk
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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