ESTIMASI VALUE AT RISK (VaR) UNTUK MODEL EXPONENTIAL GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (EGARCH) DENGAN DISTRIBUSI STUDENT-T
Quantitative risk measurement can be calculated using Value at Risk (VaR) method. Usually, we use VaR with Student-t distribution to estimate the maximum potential loss of leptokurtic data. This VaR Student-t is constant. In this paper, we employ VaR Student-t with EGARCH Student's-t model to e...
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| Main Authors: | , |
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| 格式: | Theses and Dissertations NonPeerReviewed |
| 出版: |
[Yogyakarta] : Universitas Gadjah Mada
2014
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| 主題: | |
| 在線閱讀: | https://repository.ugm.ac.id/133421/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=74084 |
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| 總結: | Quantitative risk measurement can be calculated using Value at Risk (VaR) method. Usually, we use VaR with Student-t distribution to estimate the maximum potential loss of leptokurtic data. This VaR Student-t is constant. In this paper, we employ VaR Student-t with EGARCH Student's-t model to estimate the maximum potential loss of heteroscedasticity and leverage effect data in order to obtain more accurate estimation than VaR Student-t. Backtesting methods used to measure the accuracy of the VaR are the Kupiec test. The Kupiec test stated that VaR Student-t with EGARCH was suitable for estimating the maximum potential loss of the PT WIKAâ��s stock data in December 3rd 2012 to January 31th 2014. This was shown by the results of the next 20 periods VaR forecasts that was capable for covering some forthcoming losses. |
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