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

Josef Höök, Elisabeth Larsson, Erik Lindström, Lina von Sydow

Research output: Contribution to journalPublished meeting abstractpeer-review

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

Bibliographical 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.

Subject classification (UKÄ)

  • Probability Theory and Statistics


  • RBF
  • Filtering
  • Fokker-Planck equation

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