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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.

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Bibliographic Info

Paper provided by Quantitative Finance Research Centre, University of Technology, Sydney in its series Research Paper Series with number 17.

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Date of creation: 01 Aug 1999
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Handle: RePEc:uts:rpaper:17

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Keywords: filtering; hidden Markov models; interest rate models; EM algorithm;

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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 and Applications, Springer, vol. 18(1), pages 87-107, March.

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