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Estimating the implied distribution of the future short term interest rate using the Longstaff-Schwartz model

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  • Hördahl, Peter

Abstract

This paper proposes the use of the two-factor term-structure model of Longstaff and Schwartz (1992a, LS) to estimate the risk-neutral density (RND) of the future short-term interest rate. The resulting RND can be interpreted as the market's estimate of the density of the future short-term interest rate. As such, it provides a useful financial indicator of the perceived uncertainty of future developments in the short-term interest rate. The LS approach used in this paper provides an alternative to option-based estimation procedures, which may be useful in situations here options markets are not sufficiently developed to allow estimation of the implied distribution from observed option prices. A simulation-based comparison of these two approaches reveals that the differences in the results are relatively small in magnitude, at least for short forecast horizons. Furthermore, the LS model is quite successful in capturing the asymmetries of the true distribution. It is therefore concluded that the LS model can be useful for estimating the distribution of future interest rates, when the purpose is to provide a general measure of the market' s perceived uncertainty, for example as an indictor for monetary policy purposes. JEL Classification: C15, E43, E47, G12

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Bibliographic Info

Paper provided by European Central Bank in its series Working Paper Series with number 0016.

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Date of creation: Mar 2000
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Handle: RePEc:ecb:ecbwps:20000016

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  1. Ait-Sahalia, Yacine, 1996. "Nonparametric Pricing of Interest Rate Derivative Securities," Econometrica, Econometric Society, vol. 64(3), pages 527-60, May.
  2. Soderlind, P & Svensson, L-E-O, 1996. "New Techniques to Extract Market Expectations from Financial Instruments," Papers 621, Stockholm - International Economic Studies.
  3. Dahlquist, Magnus & Svensson, Lars E O, 1996. " Estimating the Term Structure of Interest Rates for Monetary Policy Analysis," Scandinavian Journal of Economics, Wiley Blackwell, vol. 98(2), pages 163-83, June.
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  5. Cox, John C & Ingersoll, Jonathan E, Jr & Ross, Stephen A, 1985. "A Theory of the Term Structure of Interest Rates," Econometrica, Econometric Society, vol. 53(2), pages 385-407, March.
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  7. Koedijk, C.G. & Nissen, F. & Schotman, P.C. & Wolff, C.C.P., 1997. "The dynamics of short-term interest rate volatility reconsidered," Open Access publications from Tilburg University urn:nbn:nl:ui:12-3108628, Tilburg University.
  8. Francis X. Diebold & Todd A. Gunther & Anthony S. Tay, 1997. "Evaluating Density Forecasts," Center for Financial Institutions Working Papers 97-37, Wharton School Center for Financial Institutions, University of Pennsylvania.
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  11. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
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  13. Brenner, Robin J. & Harjes, Richard H. & Kroner, Kenneth F., 1996. "Another Look at Models of the Short-Term Interest Rate," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 31(01), pages 85-107, March.
  14. Chan, K C, et al, 1992. " An Empirical Comparison of Alternative Models of the Short-Term Interest Rate," Journal of Finance, American Finance Association, vol. 47(3), pages 1209-27, July.
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Cited by:
  1. Vähämaa, Sami, 2004. "Option-implied asymmetries in bond market expectations around monetary policy actions of the ECB," Working Paper Series 0315, European Central Bank.
  2. Leo Krippner, 2003. "Modelling the Yield Curve with Orthonormalised Laguerre Polynomials: A Consistent Cross-Sectional and Inter-Temporal Approach," Working Papers in Economics 03/02, University of Waikato, Department of Economics.

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