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Modelling probabilities of corporate default
This dissertation follows, scrupulously, the probability of default model used by the National University of Singapore Risk Management Institute (NUS-RMI). Any deviations or omissions are noted with reasons related to the scope of this study on modelling probabilities of corporate default of South A...
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| Format: | Thesis |
| Language: | English |
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African Institute of Financial Markets and Risk Management
2020
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| _version_ | 1867613310425235457 |
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| access_status_str | Open Access |
| author | Van Jaarsveldt, Cole |
| author2 | Mahomed, Obeid |
| author_browse | Mahomed, Obeid Van Jaarsveldt, Cole |
| author_facet | Mahomed, Obeid Van Jaarsveldt, Cole |
| author_sort | Van Jaarsveldt, Cole |
| collection | Thesis |
| description | This dissertation follows, scrupulously, the probability of default model used by the National University of Singapore Risk Management Institute (NUS-RMI). Any deviations or omissions are noted with reasons related to the scope of this study on modelling probabilities of corporate default of South African firms. Using our model, we simulate defaults and subsequently, infer parameters using classical statistical frequentist likelihood estimation and one-world-view pseudo-likelihood estimation. We improve the initial estimates from our pseudo-likelihood estimation by using Sequential Monte Carlo techniques and pseudo-Bayesian inference. With these techniques, we significantly improve upon our original parameter estimates. The increase in accuracy is most significant when using few samples which mimics real world data availability |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/31331 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:34:06.076Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | African Institute of Financial Markets and Risk Management |
| publisherStr | African Institute of Financial Markets and Risk Management |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/31331 Modelling probabilities of corporate default Van Jaarsveldt, Cole Mahomed, Obeid Mathematical Finance This dissertation follows, scrupulously, the probability of default model used by the National University of Singapore Risk Management Institute (NUS-RMI). Any deviations or omissions are noted with reasons related to the scope of this study on modelling probabilities of corporate default of South African firms. Using our model, we simulate defaults and subsequently, infer parameters using classical statistical frequentist likelihood estimation and one-world-view pseudo-likelihood estimation. We improve the initial estimates from our pseudo-likelihood estimation by using Sequential Monte Carlo techniques and pseudo-Bayesian inference. With these techniques, we significantly improve upon our original parameter estimates. The increase in accuracy is most significant when using few samples which mimics real world data availability 2020-02-25T12:05:21Z 2020-02-25T12:05:21Z 2019 2020-02-25T08:39:13Z Master Thesis Masters MPhil http://hdl.handle.net/11427/31331 eng application/pdf African Institute of Financial Markets and Risk Management Faculty of Commerce |
| spellingShingle | Mathematical Finance Van Jaarsveldt, Cole Modelling probabilities of corporate default |
| thesis_degree_str | Master's |
| title | Modelling probabilities of corporate default |
| title_full | Modelling probabilities of corporate default |
| title_fullStr | Modelling probabilities of corporate default |
| title_full_unstemmed | Modelling probabilities of corporate default |
| title_short | Modelling probabilities of corporate default |
| title_sort | modelling probabilities of corporate default |
| topic | Mathematical Finance |
| url | http://hdl.handle.net/11427/31331 |
| work_keys_str_mv | AT vanjaarsveldtcole modellingprobabilitiesofcorporatedefault |