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Revisiting the methodology and application of Value-at-Risk
- Date Issued:
- 2012
- Summary:
- The main objective of this thesis is to simulate, evaluate and discuss three standard methodologies of calculating Value-at-Risk (VaR) : Historical simulation, the Variance-covariance method and Monte Carlo simulations. Historical simulation is the most common nonparametric method. The Variance-covariance and Monte Carlo simulations are widely used parametric methods. This thesis defines the three aforementioned VaR methodologies, and uses each to calculate 1-day VaR for a hypothetical portfolio through MATLAB simulations. The evaluation of the results shows that historical simulation yields the most reliable 1-day VaR for the hypothetical portfolio under extreme market conditions. Finally, this paper concludes with a suggestion for further studies : a heavy-tail distribution should be used in order to imporve the accuracy of the results for the two parametric methods used in this study.
Title: | Revisiting the methodology and application of Value-at-Risk. |
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Name(s): |
Chung, Kyong. Charles E. Schmidt College of Science Department of Mathematical Sciences |
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Type of Resource: | text | |
Genre: | Electronic Thesis Or Dissertation | |
Date Issued: | 2012 | |
Publisher: | Florida Atlantic University | |
Physical Form: | electronic | |
Extent: | viii, 44 p. : ill. (some col.) | |
Language(s): | English | |
Summary: | The main objective of this thesis is to simulate, evaluate and discuss three standard methodologies of calculating Value-at-Risk (VaR) : Historical simulation, the Variance-covariance method and Monte Carlo simulations. Historical simulation is the most common nonparametric method. The Variance-covariance and Monte Carlo simulations are widely used parametric methods. This thesis defines the three aforementioned VaR methodologies, and uses each to calculate 1-day VaR for a hypothetical portfolio through MATLAB simulations. The evaluation of the results shows that historical simulation yields the most reliable 1-day VaR for the hypothetical portfolio under extreme market conditions. Finally, this paper concludes with a suggestion for further studies : a heavy-tail distribution should be used in order to imporve the accuracy of the results for the two parametric methods used in this study. | |
Identifier: | 827936095 (oclc), 3358328 (digitool), FADT3358328 (IID), fau:4013 (fedora) | |
Note(s): |
by Kyong Chung. Thesis (M.S.)--Florida Atlantic University, 2012. Includes bibliography. Mode of access: World Wide Web. System requirements: Adobe Reader. |
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Subject(s): |
Valuation -- Econometric models Prices -- Econometric models Financial risk management Mathematical optimization Finance -- Mathematical models |
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Persistent Link to This Record: | http://purl.flvc.org/FAU/3358328 | |
Use and Reproduction: | http://rightsstatements.org/vocab/InC/1.0/ | |
Host Institution: | FAU |