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Bayesian extensions to Diebold-Li term structure model

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Author Info

  • Laurini, Márcio Poletti
  • Hotta, Luiz Koodi

Abstract

This paper proposes a statistical model to adjust, interpolate, and forecast the term structure of interest rates. The model is based on the extensions for the term structure model of interest rates proposed by Diebold and Li (2006), through a Bayesian estimation using Markov Chain Monte Carlo (MCMC). The proposed extensions involve the use of a more flexible parametric form for the yield curve, allowing all the parameters to vary in time using a structure of latent factors, and the addition of a stochastic volatility structure to control the presence of conditional heteroskedasticity observed in the interest rates. The Bayesian estimation enables the exact distribution of the estimators in finite samples, and as a by-product, the estimation enables obtaining the distribution of forecasts of the term structure of interest rates. Unlike some econometric models of term structure, the methodology developed does not require a pre-interpolation of the yield curve. The model is fitted to the daily data of the term structure of interest rates implicit in SWAP DI-PRÉ contracts traded in the Mercantile and Futures Exchange (BM&F) in Brazil. The results are compared with the other models in terms of fitting and forecasts.

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Bibliographic Info

Article provided by Elsevier in its journal International Review of Financial Analysis.

Volume (Year): 19 (2010)
Issue (Month): 5 (December)
Pages: 342-350

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Handle: RePEc:eee:finana:v:19:y:2010:i:5:p:342-350

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Web page: http://www.elsevier.com/locate/inca/620166

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Keywords: Term structure Bayesian inference Markov Chain Monte Carlo;

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References

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  1. Diebold, Francis X. & Li, Canlin & Yue, Vivian Z., 2007. "Global yield curve dynamics and interactions: A dynamic Nelson-Siegel approach," CFS Working Paper Series 2008/27, Center for Financial Studies (CFS).
  2. Diebold, Francis X. & Li, Canlin, 2003. "Forecasting the term structure of government bond yields," CFS Working Paper Series 2004/09, Center for Financial Studies (CFS).
  3. 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.
  4. Oliver B. Linton & Enno Mammen & J. Nielsen & Carsten Tanggaard, 2000. "Yield Curve Estimation by Kernel Smoothing Methods," Econometric Society World Congress 2000 Contributed Papers 0235, Econometric Society.
  5. Darrell Duffie & Rui Kan, 1996. "A Yield-Factor Model Of Interest Rates," Mathematical Finance, Wiley Blackwell, vol. 6(4), pages 379-406.
  6. Brennan, Michael J. & Schwartz, Eduardo S., 1979. "A continuous time approach to the pricing of bonds," Journal of Banking & Finance, Elsevier, vol. 3(2), pages 133-155, July.
  7. McCulloch, J Huston, 1971. "Measuring the Term Structure of Interest Rates," The Journal of Business, University of Chicago Press, vol. 44(1), pages 19-31, January.
  8. Shea, Gary S., 1984. "Pitfalls in Smoothing Interest Rate Term Structure Data: Equilibrium Models and Spline Approximations," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 19(03), pages 253-269, September.
  9. Hull, John & White, Alan, 1990. "Pricing Interest-Rate-Derivative Securities," Review of Financial Studies, Society for Financial Studies, vol. 3(4), pages 573-92.
  10. Heath, David & Jarrow, Robert & Morton, Andrew, 1992. "Bond Pricing and the Term Structure of Interest Rates: A New Methodology for Contingent Claims Valuation," Econometrica, Econometric Society, vol. 60(1), pages 77-105, January.
  11. Michael J. Brennan and Eduardo S. Schwartz., 1979. "A Continuous-Time Approach to the Pricing of Bonds," Research Program in Finance Working Papers 85, University of California at Berkeley.
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Cited by:
  1. Márcio Poletti Laurini, 2014. "Dynamic functional data analysis with non-parametric state space models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(1), pages 142-163, January.

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