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A post-crisis investigation in to the performance of GARCH-based historical & analytical value-at-risk on the FTSE

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Bibliographic Details
Main Author: De Alessi, Alessando
Other Authors: Huang, Chun-Sung
Format: Thesis
Language:English
Published: Division of Actuarial Science 2014
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access_status_str Open Access
author De Alessi, Alessando
author2 Huang, Chun-Sung
author_browse De Alessi, Alessando
Huang, Chun-Sung
author_facet Huang, Chun-Sung
De Alessi, Alessando
author_sort De Alessi, Alessando
collection Thesis
description Includes abstract.
format Thesis
id oai:open.uct.ac.za:11427/10362
institution University of Cape Town (South Africa)
language eng
last_indexed 2026-06-10T12:33:13.838Z
license_str Not specified — see source repository
provenance_str_mv Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository
publishDate 2014
publishDateRange 2014
publishDateSort 2014
publisher Division of Actuarial Science
publisherStr Division of Actuarial Science
record_format dspace
source_str UCTD — University of Cape Town Open Access Repository
spelling oai:open.uct.ac.za:11427/10362 A post-crisis investigation in to the performance of GARCH-based historical & analytical value-at-risk on the FTSE De Alessi, Alessando Huang, Chun-Sung Mathematical Finance Includes abstract. Includes bibliographical references. This paper is an investigation into the performance of GARCH-based VaR models on the South African FTSE/JSE Top 40 Index. Specifically, this paper investigates whether stability has returned to the VaR measure following its poor performance during the latest global financial crisis (2007). GARCH models are used in both an analytic and historical approach for modeling 1%, 2.5% and 5% daily VaR for a three year backtest period (2010-2012). Four distributions are used: the normal, generalised error, t-distribution and the skewed t-distribution. A particular question asked by this paper, is whether the data from the latest financial crisis (2007) should be used in estimating VaR in a post-crisis market. To investigate this, all models are re-estimated using data that has the financial crisis and/or high volatility period removed, then the results across the two data sets are compared. The take away point from this research is that the volatility-clustering mechanism inherent in every GARCH model is capable of producing accurate VaR estimates in a post-downturn/lower-volatility market even when the data on which the model was estimated contains financial downturn/volatile data. There is strong evidence suggesting stability has returned to this measure - however caution remains over using over-simplified models. 2014-12-28T14:52:04Z 2014-12-28T14:52:04Z 2013 Master Thesis Masters MPhil http://hdl.handle.net/11427/10362 eng application/pdf Division of Actuarial Science Faculty of Commerce University of Cape Town
spellingShingle Mathematical Finance
De Alessi, Alessando
A post-crisis investigation in to the performance of GARCH-based historical & analytical value-at-risk on the FTSE
thesis_degree_str Master's
title A post-crisis investigation in to the performance of GARCH-based historical & analytical value-at-risk on the FTSE
title_full A post-crisis investigation in to the performance of GARCH-based historical & analytical value-at-risk on the FTSE
title_fullStr A post-crisis investigation in to the performance of GARCH-based historical & analytical value-at-risk on the FTSE
title_full_unstemmed A post-crisis investigation in to the performance of GARCH-based historical & analytical value-at-risk on the FTSE
title_short A post-crisis investigation in to the performance of GARCH-based historical & analytical value-at-risk on the FTSE
title_sort post crisis investigation in to the performance of garch based historical analytical value at risk on the ftse
topic Mathematical Finance
url http://hdl.handle.net/11427/10362
work_keys_str_mv AT dealessialessando apostcrisisinvestigationintotheperformanceofgarchbasedhistoricalanalyticalvalueatriskontheftse
AT dealessialessando postcrisisinvestigationintotheperformanceofgarchbasedhistoricalanalyticalvalueatriskontheftse