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Contribution Details
| Type | Master's Thesis |
| Scope | Discipline-based scholarship |
| Title | Empirical analysis of a non-affine stochastic volatility model |
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| Institution | University of Zurich |
| Faculty | Faculty of Business, Economics and Informatics |
| Number of Pages | 56 |
| Date | 2020 |
| Abstract Text | This thesis is about the pricing performance of the Inverse Gamma model of European vanilla options on an equity underlying. Since the Inverse Gamma model is non-affine it has no closed form solution hence an approximation formula is used. A theoretical foundation is built by introducing the basic tools for option pricing and explaining the standard models which are the foundation for all the different extensions. It is demonstrated why the standard Black-Scholes model fails when it comes to pricing options and how to escape these problems. For the problem with the constant volatility assumption of the Black- Scholes model, stochastic volatility models are introduced. Besides the Inverse Gamma model the Heston model is presented too and serves as the benchmark model. The empirical analysis is based on data sets from two different days. A least squared error fitness function is used to calibrate the parameters. The Heston model outperforms the Inverse Gamma model clearly because it turns out that the approximation formula for this empirical analysis is not good enough. By making use of simulation it can be shown that the Inverse Gamma model can be competitive with the Heston model. |
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