Exchangeability, extreme returns and Value-at-Risk forecasts
In this paper, we propose a new approach to extreme value modelling for the forecasting of Value-at-Risk (VaR). In particular, the block maxima and the peaks-over-threshold methods are generalised to exchangeable random sequences. This caters for the dependencies, such as serial autocorrelation, of...
| Main Authors: | , , |
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| Format: | Journal Article |
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Elsevier BV * North-Holland
2017
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| Online Access: | http://hdl.handle.net/20.500.11937/67319 |
| _version_ | 1848761534691409920 |
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| author | Huang, Chun-Kai North, D. Zewotir, T. |
| author_facet | Huang, Chun-Kai North, D. Zewotir, T. |
| author_sort | Huang, Chun-Kai |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | In this paper, we propose a new approach to extreme value modelling for the forecasting of Value-at-Risk (VaR). In particular, the block maxima and the peaks-over-threshold methods are generalised to exchangeable random sequences. This caters for the dependencies, such as serial autocorrelation, of financial returns observed empirically. In addition, this approach allows for parameter variations within each VaR estimation window. Empirical prior distributions of the extreme value parameters are attained by using resampling procedures. We compare the results of our VaR forecasts to that of the unconditional extreme value theory (EVT) approach and the conditional GARCH-EVT model for robust conclusions. |
| first_indexed | 2025-11-14T10:33:12Z |
| format | Journal Article |
| id | curtin-20.500.11937-67319 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:33:12Z |
| publishDate | 2017 |
| publisher | Elsevier BV * North-Holland |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-673192018-09-21T00:31:09Z Exchangeability, extreme returns and Value-at-Risk forecasts Huang, Chun-Kai North, D. Zewotir, T. In this paper, we propose a new approach to extreme value modelling for the forecasting of Value-at-Risk (VaR). In particular, the block maxima and the peaks-over-threshold methods are generalised to exchangeable random sequences. This caters for the dependencies, such as serial autocorrelation, of financial returns observed empirically. In addition, this approach allows for parameter variations within each VaR estimation window. Empirical prior distributions of the extreme value parameters are attained by using resampling procedures. We compare the results of our VaR forecasts to that of the unconditional extreme value theory (EVT) approach and the conditional GARCH-EVT model for robust conclusions. 2017 Journal Article http://hdl.handle.net/20.500.11937/67319 10.1016/j.physa.2017.02.080 Elsevier BV * North-Holland restricted |
| spellingShingle | Huang, Chun-Kai North, D. Zewotir, T. Exchangeability, extreme returns and Value-at-Risk forecasts |
| title | Exchangeability, extreme returns and Value-at-Risk forecasts |
| title_full | Exchangeability, extreme returns and Value-at-Risk forecasts |
| title_fullStr | Exchangeability, extreme returns and Value-at-Risk forecasts |
| title_full_unstemmed | Exchangeability, extreme returns and Value-at-Risk forecasts |
| title_short | Exchangeability, extreme returns and Value-at-Risk forecasts |
| title_sort | exchangeability, extreme returns and value-at-risk forecasts |
| url | http://hdl.handle.net/20.500.11937/67319 |