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Value at risk and extreme value theory : application to the Johannesburg Securities Exchange

dc.contributor.authorWilliams, R.en_ZA
dc.contributor.authorVan Heerden, J. D.en_ZA
dc.contributor.authorConradie, W. J.en_ZA
dc.date.accessioned2019-10-02T13:55:09Z
dc.date.available2019-10-02T13:55:09Z
dc.date.issued2018
dc.identifier.citationWilliams, R., Van Heerden, J. D. & Conradie, W. J. 2018. Value at risk and extreme value theory : application to the Johannesburg Securities Exchange. Journal for Studies in Economics and Econometrics, 42(1):87-114
dc.identifier.issn0379-6205 (print)
dc.identifier.urihttp://hdl.handle.net/10019.1/106568
dc.descriptionCITATION: Williams, R., Van Heerden, J. D. & Conradie, W. J. 2018. Value at risk and extreme value theory : application to the Johannesburg Securities Exchange. Journal for Studies in Economics and Econometrics, 42(1):87-114.
dc.descriptionThe original publication is available at https://journals.co.za
dc.description.abstractValue at Risk (VaR) has been established as one of the most important and commonly used financial risk management tools. Nevertheless, the attractive features and wide-spread use of VaR could not help to avoid a number of financial crises and its severe impact on economies globally, the latest being the 2008 financial crisis. In isolation, VaR has, in the past, mostly focused on events that occur with a 1% or 5% probability. This is a popular reason offered for its failure of ‘predicting’ the financial crises, as the latter are viewed as ‘extreme’ events and can therefore not be classified as events with a 1% or 5% probability of happening. The use of Extreme Value Theory (EVT) in calculating VaR is a relatively new approach and attempts to expand on the traditional VaR-only approach to include potential extreme events. This approach has provided good results in developed markets and in this article we investigate if the same holds true in the more volatile South African equity space. We examine and compare the application of seven VaR and VaR-EVT models on the FTSE/JSE Total Return All Share Index. Our results suggest that the Filtered Historical Simulation VaR method is the best all-round model. It is, however, worthwhile to employ EVT in the form of the conditional Generalized Pareto Distribution (GPD) model when calculating very extreme quantiles such as the 0.1% quantile. Our results further highlight the importance of filtering the data in order to account for the conditional heteroskedasticity of the financial time series.en_ZA
dc.description.urihttps://journals.co.za/content/journal/10520/EJC-e7d0e34a7?fromSearch=true
dc.format.extent28 pages ; illustrations
dc.language.isoen_ZAen_ZA
dc.publisherBureau for Economic Research
dc.subjectJohannesburg Stock Exchange -- Risk assessmenten_ZA
dc.subjectValue at risken_ZA
dc.subjectValue investingen_ZA
dc.subjectExtreme value theoryen_ZA
dc.subjectValue -- Economic aspectsen_ZA
dc.titleValue at risk and extreme value theory : application to the Johannesburg Securities Exchangeen_ZA
dc.typeArticleen_ZA
dc.description.versionPublisher's version
dc.rights.holderBureau for Economic Research


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