Implicit numerical methods such as the stochastic theta-method offer a practical way to approximate solutions of stochastic differential equations. The method involves a parameter, θ, which is freely chosen. In this thesis, we investigate strong convergence and linear stability, both mean-square and asymptotic, arising from the implementation of the theta-method when applied to ordinary stochastic differential equations incoroporating jumps. Such models are used in several disciplines; in particular, we note their use as models for various financial quantities such as asset prices, interest rates and volatility.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:501657 |
| Date | January 2008 |
| Creators | Chalmers, Graeme D. |
| Publisher | University of Strathclyde |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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