Maximum likelihood estimation of the parameters of stochastic differential equations

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The primary objective of this project is to develop efficient algorithms for estimating the parameters of stochastic differential equations (SDEs) by simulated and exact maximum likelihood. The research will draw on both parametric and non-parametric analysis in novel ways to construct estimation procedures that are computationally feasible. These methods will then be applied in the area of finance and used to estimate the parameters of stochastic-volatility models, thus contributing to knowledge in a prominent area of complex systems, namely financial risk. The execution of this collaborative project will deliver quality research training in the topical area of mathematical finance and produce high-calibre postgraduates.