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Filtering and Parameter Estimation for a Mean Reverting Interest Rate Model

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Abstract

A Hidden Markov Model with mean reverting characteristics is considered as a model for financial time series, particularly interest rates. The optimal filter for the state of the hidden Markov chain is obtained. A number of auxiliary filters are obtained that enable the parameters of the model to be estimated using the EM algorithm. A simulation study demonstrates the feasibility of this approach.

Suggested Citation

  • Robert Elliott & Paul Fischer & Eckhard Platen, 1999. "Filtering and Parameter Estimation for a Mean Reverting Interest Rate Model," Research Paper Series 17, Quantitative Finance Research Centre, University of Technology, Sydney.
  • Handle: RePEc:uts:rpaper:17
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    Cited by:

    1. Christina Erlwein & Rogemar Mamon, 2009. "An online estimation scheme for a Hull–White model with HMM-driven parameters," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(1), pages 87-107, March.
    2. Robert Elliott & Rogemar Mamon, 2002. "An interest rate model with a Markovian mean reverting level," Quantitative Finance, Taylor & Francis Journals, vol. 2(6), pages 454-458.
    3. Radkov, Petar, 2010. "An interest rate model with Markov chain volatility level," MPRA Paper 60179, University Library of Munich, Germany.

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