The Importance of Assuming Appropriate Probability Distributions when Modelling Financial Data with Extremes -A Comparative Study using EVT
This dissertation investigates the implications of using inappropriate distributions when modelling data sets with extreme data. It has been found that in practice it has been assumed that financial data follow a normal and T Distribution even in cases where these assumptions are inappropriate. Su...
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| Format: | Dissertation (University of Nottingham only) |
| Language: | English |
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2006
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| Online Access: | https://eprints.nottingham.ac.uk/20719/ |
| _version_ | 1848792122206978048 |
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| author | Hurley, Tamara Janelle |
| author_facet | Hurley, Tamara Janelle |
| author_sort | Hurley, Tamara Janelle |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | This dissertation investigates the implications of using inappropriate distributions when modelling data sets with extreme data. It has been found that in practice it has been assumed that financial data follow a normal and T Distribution even in cases where these assumptions are inappropriate. Such assumptions when modelling extreme data can lead to gross understatements in risk estimates. The more suitable approach of EVT is introduced as a more prudent approach to model extreme risks. The research was facilitated by models built in EXCEL. Risk estimates derived from a Danish data set of insurance losses under the Normal, T and Generalised Pareto Distribution (EVT) were estimated and compared to determine the degree of error in making wrong distributions assumptions in risk modelling. The dissertation also discusses the usefulness of EVT in the context of regulatory capital charges and explores the limitations of the EVT approach through sensitivity testing.
The Findings of the research highlight that financial institutions are set to incur significant understatements in risk estimates if traditional Normal and T distributions are used as the basis of modelling data with extremes. EVT is considered a necessary complement to existing internal and regulatory risk measurement processes. |
| first_indexed | 2025-11-14T18:39:23Z |
| format | Dissertation (University of Nottingham only) |
| id | nottingham-20719 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T18:39:23Z |
| publishDate | 2006 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-207192018-02-03T01:51:23Z https://eprints.nottingham.ac.uk/20719/ The Importance of Assuming Appropriate Probability Distributions when Modelling Financial Data with Extremes -A Comparative Study using EVT Hurley, Tamara Janelle This dissertation investigates the implications of using inappropriate distributions when modelling data sets with extreme data. It has been found that in practice it has been assumed that financial data follow a normal and T Distribution even in cases where these assumptions are inappropriate. Such assumptions when modelling extreme data can lead to gross understatements in risk estimates. The more suitable approach of EVT is introduced as a more prudent approach to model extreme risks. The research was facilitated by models built in EXCEL. Risk estimates derived from a Danish data set of insurance losses under the Normal, T and Generalised Pareto Distribution (EVT) were estimated and compared to determine the degree of error in making wrong distributions assumptions in risk modelling. The dissertation also discusses the usefulness of EVT in the context of regulatory capital charges and explores the limitations of the EVT approach through sensitivity testing. The Findings of the research highlight that financial institutions are set to incur significant understatements in risk estimates if traditional Normal and T distributions are used as the basis of modelling data with extremes. EVT is considered a necessary complement to existing internal and regulatory risk measurement processes. 2006 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/20719/1/06MBAlixth3.pdf Hurley, Tamara Janelle (2006) The Importance of Assuming Appropriate Probability Distributions when Modelling Financial Data with Extremes -A Comparative Study using EVT. [Dissertation (University of Nottingham only)] (Unpublished) modelling financial data extreme |
| spellingShingle | modelling financial data extreme Hurley, Tamara Janelle The Importance of Assuming Appropriate Probability Distributions when Modelling Financial Data with Extremes -A Comparative Study using EVT |
| title | The Importance of Assuming Appropriate Probability Distributions when Modelling Financial Data with Extremes -A Comparative Study using EVT |
| title_full | The Importance of Assuming Appropriate Probability Distributions when Modelling Financial Data with Extremes -A Comparative Study using EVT |
| title_fullStr | The Importance of Assuming Appropriate Probability Distributions when Modelling Financial Data with Extremes -A Comparative Study using EVT |
| title_full_unstemmed | The Importance of Assuming Appropriate Probability Distributions when Modelling Financial Data with Extremes -A Comparative Study using EVT |
| title_short | The Importance of Assuming Appropriate Probability Distributions when Modelling Financial Data with Extremes -A Comparative Study using EVT |
| title_sort | importance of assuming appropriate probability distributions when modelling financial data with extremes -a comparative study using evt |
| topic | modelling financial data extreme |
| url | https://eprints.nottingham.ac.uk/20719/ |