Risk Management based on GARCH and Non-parametric stochastic volatility models and some cases of Generalized Hyperbolic distribution
The paper is devoted to the modern methods of Value-at-Risk calculation using different cases of Generalized Hyperbolic distribution and models for predicting volatility. In our research we use GARCH-M and Non-parametric volatility models and compare Value-at-Risk calculation depending on the distri...
| Main Authors: | , |
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| Format: | Others |
| Language: | English |
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Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE)
2008
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| Subjects: | |
| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-2201 |
| Summary: | The paper is devoted to the modern methods of Value-at-Risk calculation using different cases of Generalized Hyperbolic distribution and models for predicting volatility. In our research we use GARCH-M and Non-parametric volatility models and compare Value-at-Risk calculation depending on the distribution that is used. In the case of Non-parametric model corresponding windows are proved by the Cross Validation method. Furthermore in our work we consider adaption of the method to intraday data using ACD and UHF-GARCH models. The project involves also application of the developed methods to real financial data and comparable analysis of the obtained results. |
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