Extreme Risk In Resource Indices And The Generalized Logistic Distribution

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Chun-Kai Huang
Venelle Pather
Jahvaid Hammujuddy
Knowledge Chinhamu


Extreme Value, Generalized Logistic Distribution, Value-at-Risk, Expected Shortfall, Resource Indices


The resource sector accounts for a substantial proportion of market capitalization on the US and South African stock exchanges. Hence, severe movements in related stock prices can drastically affect the risk profile of the entire market. Extreme value theory provides a basis for evaluating and forecasting such sporadic occurrences. In this article, we compare performances of classical extreme value models against the recently suggested generalized logistic distribution, for estimating value-at-risk and expected shortfall in resource indices. Our results suggest a significant difference in risk behavior between the two markets and the generalized logistic distribution does not always outperform classical models, as previous work may have suggested.


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