Inference for non-linear diffusions and jump-diffusions: a Monte Carlo EM approach

Authors:
Erik Lindström
Affiliations:
Lund University, Centre for Mathematical Sciences, Lund, Sweden
Venue:
ACMIN'12 Proceedings of the 14th international conference on Automatic Control, Modelling & Simulation, and Proceedings of the 11th international conference on Microelectronics, Nanoelectronics, Optoelectronics
Year:
2012

Citing 5
Cited 0

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Abstract

We propose a simple, general and computationally efficient algorithm for maximum likelihood estimation (MLE) of parameters in diffusion and jump-diffusion processes. This is conducted within a Monte Carlo EM-algorithm, where the smoothing distribution is computed using resampling. The results are encouraging as we can approximate the MLE well for the models studied when using simulated data. We also obtain reasonable estimates, compared to other papers, when fitting the Heston and Bates model to S&P 500 and VIX data.