Extreme risk in resource indices and the generalized logistic distribution

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 forec...

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Main Authors: Huang, Chun-Kai, Pather, V., Hammujuddy, J., Chinhamu, K.
Format: Journal Article
Published: 2017
Online Access:http://hdl.handle.net/20.500.11937/68019
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author Huang, Chun-Kai
Pather, V.
Hammujuddy, J.
Chinhamu, K.
author_facet Huang, Chun-Kai
Pather, V.
Hammujuddy, J.
Chinhamu, K.
author_sort Huang, Chun-Kai
building Curtin Institutional Repository
collection Online Access
description 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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spelling curtin-20.500.11937-680192018-09-21T00:25:21Z Extreme risk in resource indices and the generalized logistic distribution Huang, Chun-Kai Pather, V. Hammujuddy, J. Chinhamu, K. 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. 2017 Journal Article http://hdl.handle.net/20.500.11937/68019 10.19030/jabr.v33i2.9899 http://creativecommons.org/licenses/by/4.0/ fulltext
spellingShingle Huang, Chun-Kai
Pather, V.
Hammujuddy, J.
Chinhamu, K.
Extreme risk in resource indices and the generalized logistic distribution
title Extreme risk in resource indices and the generalized logistic distribution
title_full Extreme risk in resource indices and the generalized logistic distribution
title_fullStr Extreme risk in resource indices and the generalized logistic distribution
title_full_unstemmed Extreme risk in resource indices and the generalized logistic distribution
title_short Extreme risk in resource indices and the generalized logistic distribution
title_sort extreme risk in resource indices and the generalized logistic distribution
url http://hdl.handle.net/20.500.11937/68019