IDEAS home Printed from https://ideas.repec.org/p/fip/fedhwp/wp-00-21.html

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

    Download full text from publisher

    File URL: http://www.chicagofed.org/digital_assets/publications/working_papers/2000/wp2000_21.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Fama, Eugene F. & Gibbons, Michael R., 1984. "A comparison of inflation forecasts," Journal of Monetary Economics, Elsevier, vol. 13(3), pages 327-348, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Geert Bekaert & Seonghoon Cho & Antonio Moreno, 2010. "New Keynesian Macroeconomics and the Term Structure," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(1), pages 33-62, February.
    2. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
    3. Driffill, John & Sola, Martin & Kenc, Turalay & Spagnolo, Fabio, 2004. "On Model Selection and Markov Switching: A Empirical Examination of Term Structure Models with Regime Shifts," CEPR Discussion Papers 4165, C.E.P.R. Discussion Papers.
    4. Suresh M. Sundaresan, 2000. "Continuous‐Time Methods in Finance: A Review and an Assessment," Journal of Finance, American Finance Association, vol. 55(4), pages 1569-1622, August.
    5. Dong Heon Kim, 2004. "Nonlinearity in the Term Structure," Econometric Society 2004 Far Eastern Meetings 440, Econometric Society.
    6. Boero, G. & Torricelli, C., 1996. "A comparative evaluation of alternative models of the term structure of interest rates," European Journal of Operational Research, Elsevier, vol. 93(1), pages 205-223, August.
    7. Dillen, Hans, 1997. "A model of the term structure of interest rates in an open economy with regime shifts1," Journal of International Money and Finance, Elsevier, vol. 16(5), pages 795-819, September.
    8. Gibson, Rajna & Lhabitant, Francois-Serge & Talay, Denis, 2010. "Modeling the Term Structure of Interest Rates: A Review of the Literature," Foundations and Trends(R) in Finance, now publishers, vol. 5(1–2), pages 1-156, December.
    9. D H Kim, 2005. "Nonlinearity in the Term Structure," Centre for Growth and Business Cycle Research Discussion Paper Series 51, Economics, The University of Manchester.
    10. Doshi, Hitesh & Jacobs, Kris & Liu, Rui, 2018. "Macroeconomic determinants of the term structure: Long-run and short-run dynamics," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 99-122.
    11. Patrick Cheridito & Damir Filipovic, 2004. "Market Price of Risk Specifications for Affine Models: Theory and Evidence," Econometric Society 2004 North American Winter Meetings 536, Econometric Society.
    12. Collin-Dufresne, Pierre & Goldstein, Robert S. & Jones, Christopher S., 2009. "Can interest rate volatility be extracted from the cross section of bond yields?," Journal of Financial Economics, Elsevier, vol. 94(1), pages 47-66, October.
    13. Date, P. & Mamon, R. & Wang, I.C., 2007. "Valuation of cash flows under random rates of interest: A linear algebraic approach," Insurance: Mathematics and Economics, Elsevier, vol. 41(1), pages 84-95, July.
    14. Chris Strickland, 1996. "A comparison of diffusion models of the term structure," The European Journal of Finance, Taylor & Francis Journals, vol. 2(1), pages 103-123.
    15. Ang, Andrew & Piazzesi, Monika, 2003. "A no-arbitrage vector autoregression of term structure dynamics with macroeconomic and latent variables," Journal of Monetary Economics, Elsevier, vol. 50(4), pages 745-787, May.
    16. Torben B. Rasmussen, "undated". "Affine Bond Pricing with a Mixture Distribution for Interest Rate Time-Series DynamicsCreation-Date: 20100225," CREATES Research Papers 2010-11, Department of Economics and Business Economics, Aarhus University.
    17. Alain Monfort & Fulvio Pegoraro, 2007. "Switching VARMA Term Structure Models - Extended Version," Working Papers 2007-19, Center for Research in Economics and Statistics.
    18. Duan, Jin-Chuan & Simonato, Jean-Guy, 1999. "Estimating and Testing Exponential-Affine Term Structure Models by Kalman Filter," Review of Quantitative Finance and Accounting, Springer, vol. 13(2), pages 111-135, September.
    19. Ravi Bansal & Hao Zhou, 2002. "Term Structure of Interest Rates with Regime Shifts," Journal of Finance, American Finance Association, vol. 57(5), pages 1997-2043, October.
    20. repec:wyi:journl:002109 is not listed on IDEAS
    21. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.

    More about this item

    Keywords

    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fip:fedhwp:wp-00-21. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Lauren Wiese (email available below). General contact details of provider: https://edirc.repec.org/data/frbchus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.