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Empirical Analyses of Extreme Value Models for the South African Mining Index
Company: South African Journal of Economics
Company Url: Click here to open
Year Of Publication: 2014
Month Of Publication: May
Resource Link: Click here to open
Download Count: 0
View Count: 702
Comment Num: 0
Language: English
Source: article
Who Can Read: Free
Date: 7-20-2014
Publisher: Administrator
Summary
While the classical normality assumption is simple to implement, it is well known to underestimate the leptokurtic behaviour demonstrated in most financial data. After examining properties of the Johannesburg Stock Exchange Mining Index returns, we propose two extreme value models to fit its negative tail with a higher degree of accuracy. The generalised extreme value distribution (GEVD) is fitted using the block maxima approach, while the generalised Pareto distribution (GPD) is fitted using the peaks-over-threshold method. Numerical assessment of value-at-risk (VaR) estimates indicates that both GEVD and GPD increasingly outperform the normal distribution as we move further into the lower tail. In addition, GEVD produces lower estimates relative to that of the historical VaR, and GPD provides slightly more conservative estimates for adequate capitalisation.
Author(s)
Huang, Chun-Kai Sign in to follow this author
Huang, Chun-Sung Sign in to follow this author
Hammujuddy, Jahvaid Sign in to follow this author
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