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Financial signal processing: a self calibrating model

Author

Listed:
  • Robert J. Elliott
  • William C. Hunter
  • Barbara M. Jamieson

Abstract

Previous work on multifactor term structure models has proposed that the short rate process is a function of some unobserved diffusion process. We consider a model in which the short rate process is a function of a Markov chain which represents the 'state of the world'. This enables us to obtain explicit expressions for the prices of zero-coupon bonds and other securities. Discretizing our model allows the use of signal processing techniques from Hidden Markov Models. This means we can estimate not only the unobserved Markov chain but also the parameters of the model, so the model is self-calibrating. The estimation procedure is tested on a selection of U.S. Treasury bills and bonds.

Suggested Citation

  • Robert J. Elliott & William C. Hunter & Barbara M. Jamieson, 2000. "Financial signal processing: a self calibrating model," Working Paper Series WP-00-21, Federal Reserve Bank of Chicago.
    • Handle: RePEc:fip:fedhwp:wp-00-21
    as

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    References listed on IDEAS

    as
    1. Hamilton, James D., 1988. "Rational-expectations econometric analysis of changes in regime : An investigation of the term structure of interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 385-423.
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    3. Pearson, Neil D & Sun, Tong-Sheng, 1994. "Exploiting the Conditional Density in Estimating the Term Structure: An Application to the Cox, Ingersoll, and Ross Model," Journal of Finance, American Finance Association, vol. 49(4), pages 1279-1304, September.
    4. Harrison, J. Michael & Kreps, David M., 1979. "Martingales and arbitrage in multiperiod securities markets," Journal of Economic Theory, Elsevier, vol. 20(3), pages 381-408, June.
    5. Gordon Pye, 1966. "A Markov Model of the Term Structure," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 80(1), pages 60-72.
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