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Parameter Estimation in Finance Using Radial Basis Function Methods

Larsson, Elisabeth ; Höök, Lars Josef ; Lindström, Erik LU orcid and von Sydow, Lina (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.
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author
; ; and
organization
publishing date
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}},
}