Filtering and Parameter Estimation of Partially Observed Diffusion Processes Using Gaussian RBFs

Research output: Contribution to journalPublished meeting abstract


Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Probability Theory and Statistics


  • RBF, Filtering, Fokker-Planck equation
Original languageEnglish
Journal[Publication information missing]
Publication statusPublished - 2014
Publication categoryResearch
Event2014 SIAM Conference on Financial Mathematics and Engineering - Chicago, Illinois, United States
Duration: 2014 Nov 132014 Nov 15

Bibliographic note

Asset prices can be modeled as stochastic diffusion pro- cesses involving a number of parameters. Based on market observations, these parameters can be estimated. Prices are not uniquely determined due to the ask-bid spread. We model the spread as additive noise, and show that Gaussian radial basis functions (RBFs), leads to a convenient math- ematical representation. Furthermore, substantial parts of the computations can be performed analytically if RBFs are used for approximating transition densities.