Inference for Non-linear Diffusions and Jump-Diffusions: A Monte Carlo EM approach
(2012) 14th International Conference on Automatic Control, Modelling & Simulation (ACMOS '12) p.110-115- Abstract
- We propose a simple, general and computationally efficient algorithm for maximum likelihood estima-
tion (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.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3008444
- author
- Lindström, Erik LU
- organization
- publishing date
- 2012
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Jump-diffusions, Maximum Likelihood estimation, MCEM-algorithm, Resampling, Heston model, Bates model
- host publication
- Recent Researches in Automatic Control and Electronics, Proceedings of the 14th International Conference on Automatic Control, Modelling & Simulation (ACMOS '12)
- editor
- Nola, Vincenzo ; Kadoch, Michel and Zemilak, Alexander
- pages
- 6 pages
- publisher
- WSEAS Press
- conference name
- 14th International Conference on Automatic Control, Modelling & Simulation (ACMOS '12)
- conference dates
- 2012-04-02 - 2012-04-04
- ISBN
- 978-1-61804-080-0
- language
- English
- LU publication?
- yes
- additional info
- The 14th International Conference on Automatic Control, Modelling & Simulation (ACMOS '12) was held in Saint Malo & Mont Saint-Michel, France, April 2-4, 2012 in conjunction with: The 11th International Conference on Microelectronics, Nanoelectronics, Optoelectronics (MINO '12); the 11th International Conference on Telecommunications and Informatics (TELE-INFO '12); the 11th International Conference on Signal Processing (SIP '12); the 2nd International Conference on Environment, Economics, Energy, Devices, Systems, Communications, Computers, Mathematics (EDSCM '13)
- id
- adc4b502-5457-4355-8cf7-ddb6cef82049 (old id 3008444)
- alternative location
- http://www.wseas.us/e-library/conferences/2012/SaintMalo/ACMIN/ACMIN-00.pdf
- date added to LUP
- 2016-04-04 11:10:13
- date last changed
- 2019-03-08 03:24:02
@inproceedings{adc4b502-5457-4355-8cf7-ddb6cef82049, abstract = {{We propose a simple, general and computationally efficient algorithm for maximum likelihood estima-<br/><br> tion (MLE) of parameters in diffusion and jump-diffusion processes. This is conducted within a Monte Carlo<br/><br> EM-algorithm, where the smoothing distribution is computed using resampling. The results are encouraging as<br/><br> we can approximate the MLE well for the models studied when using simulated data. We also obtain reasonable<br/><br> estimates, compared to other papers, when fitting the Heston and Bates model to S&P 500 and VIX data.}}, author = {{Lindström, Erik}}, booktitle = {{Recent Researches in Automatic Control and Electronics, Proceedings of the 14th International Conference on Automatic Control, Modelling & Simulation (ACMOS '12)}}, editor = {{Nola, Vincenzo and Kadoch, Michel and Zemilak, Alexander}}, isbn = {{978-1-61804-080-0}}, keywords = {{Jump-diffusions; Maximum Likelihood estimation; MCEM-algorithm; Resampling; Heston model; Bates model}}, language = {{eng}}, pages = {{110--115}}, publisher = {{WSEAS Press}}, title = {{Inference for Non-linear Diffusions and Jump-Diffusions: A Monte Carlo EM approach}}, url = {{http://www.wseas.us/e-library/conferences/2012/SaintMalo/ACMIN/ACMIN-00.pdf}}, year = {{2012}}, }