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A generalization of the Kalman filter to models with infinite variance

Author

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  • Le Breton, Alain
  • Musiela, Marek

Abstract

The problem of optimal linear estimation for continuous time processes is investigated. The signal and observation processes are solutions of a linear system. The optimal filter is given by recursive equations which reduce to the classical Kalman-Bucy equations when the system is driven by independent white noises. The filter is defined by a left innovations process. Solutions to the prediction and smoothing problems are obtained. The assumptions concerning the errors allow to consider models with infinite variance.

Suggested Citation

  • Le Breton, Alain & Musiela, Marek, 1993. "A generalization of the Kalman filter to models with infinite variance," Stochastic Processes and their Applications, Elsevier, vol. 47(1), pages 75-94, August.
    • Handle: RePEc:eee:spapps:v:47:y:1993:i:1:p:75-94
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