Parameter Estimation in Finance Using Radial Basis Function Methods
(2016) SIAM Conference on Financial Mathematics and Engineering- Abstract
- Given time series market observations for a price process, the parameters in an assumed underlying model can be determined through maximum likelihood estimation. Transition probability densities need to be estimated between each pair of data points. We show that Gaussian radial basis function approximation of the Fokker-Planck equations for the densities leads to a convenient mathematical representation. We present numerical results for one and two factor interest rate models.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/20b10b59-d68b-463a-b802-2425f5696b80
- author
- Larsson, Elisabeth ; Höök, Lars Josef ; Lindström, Erik LU and von Sydow, Lina
- organization
- publishing date
- 2016-11-19
- type
- Contribution to conference
- publication status
- published
- subject
- conference name
- SIAM Conference on Financial Mathematics and Engineering
- conference dates
- 2016-11-17 - 2016-11-19
- language
- English
- LU publication?
- yes
- id
- 20b10b59-d68b-463a-b802-2425f5696b80
- date added to LUP
- 2016-08-24 14:23:50
- date last changed
- 2019-03-08 03:24:03
@misc{20b10b59-d68b-463a-b802-2425f5696b80, abstract = {{Given time series market observations for a price process, the parameters in an assumed underlying model can be determined through maximum likelihood estimation. Transition probability densities need to be estimated between each pair of data points. We show that Gaussian radial basis function approximation of the Fokker-Planck equations for the densities leads to a convenient mathematical representation. We present numerical results for one and two factor interest rate models.}}, author = {{Larsson, Elisabeth and Höök, Lars Josef and Lindström, Erik and von Sydow, Lina}}, language = {{eng}}, month = {{11}}, title = {{Parameter Estimation in Finance Using Radial Basis Function Methods}}, year = {{2016}}, }