Assessing the Performance of Value-at-Risk Models in Chinese Stock Market
In this paper, parametric, nonparametric, and semi-parametric models are applied to a hypothetical portfolio - Shanghai Stock Exchange Composite Index to estimate Value-at-Risk in Chinese market. In order to assess the performance of different approaches, the statistic features such as kurtosis, ske...
| Main Author: | |
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| Format: | Dissertation (University of Nottingham only) |
| Language: | English |
| Published: |
2008
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| Online Access: | https://eprints.nottingham.ac.uk/22277/ |
| _version_ | 1848792382717296640 |
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| author | Lin, Lin |
| author_facet | Lin, Lin |
| author_sort | Lin, Lin |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | In this paper, parametric, nonparametric, and semi-parametric models are applied to a hypothetical portfolio - Shanghai Stock Exchange Composite Index to estimate Value-at-Risk in Chinese market. In order to assess the performance of different approaches, the statistic features such as kurtosis, skewness and autocorrelation of daily return have been studied. In addition, this article analyzes the advantages and disadvantages of each model and implements back-tests to check the validation of them. The main finding of this article is that Filtered Historical Simulation proves to be the most appropriate approach to estimate Value-at-Risk in Chinese financial market. |
| first_indexed | 2025-11-14T18:43:31Z |
| format | Dissertation (University of Nottingham only) |
| id | nottingham-22277 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T18:43:31Z |
| publishDate | 2008 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-222772018-03-29T09:51:09Z https://eprints.nottingham.ac.uk/22277/ Assessing the Performance of Value-at-Risk Models in Chinese Stock Market Lin, Lin In this paper, parametric, nonparametric, and semi-parametric models are applied to a hypothetical portfolio - Shanghai Stock Exchange Composite Index to estimate Value-at-Risk in Chinese market. In order to assess the performance of different approaches, the statistic features such as kurtosis, skewness and autocorrelation of daily return have been studied. In addition, this article analyzes the advantages and disadvantages of each model and implements back-tests to check the validation of them. The main finding of this article is that Filtered Historical Simulation proves to be the most appropriate approach to estimate Value-at-Risk in Chinese financial market. 2008 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/22277/1/final1.pdf Lin, Lin (2008) Assessing the Performance of Value-at-Risk Models in Chinese Stock Market. [Dissertation (University of Nottingham only)] (Unpublished) Value-at-Risk parametric model non-parametric model extreme value theory back-tests |
| spellingShingle | Value-at-Risk parametric model non-parametric model extreme value theory back-tests Lin, Lin Assessing the Performance of Value-at-Risk Models in Chinese Stock Market |
| title | Assessing the Performance of Value-at-Risk Models in Chinese Stock Market |
| title_full | Assessing the Performance of Value-at-Risk Models in Chinese Stock Market |
| title_fullStr | Assessing the Performance of Value-at-Risk Models in Chinese Stock Market |
| title_full_unstemmed | Assessing the Performance of Value-at-Risk Models in Chinese Stock Market |
| title_short | Assessing the Performance of Value-at-Risk Models in Chinese Stock Market |
| title_sort | assessing the performance of value-at-risk models in chinese stock market |
| topic | Value-at-Risk parametric model non-parametric model extreme value theory back-tests |
| url | https://eprints.nottingham.ac.uk/22277/ |