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Term Structure Models Can Predict Interest Rate Volatility. But How?

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  • Hideyuki Takamizawa

Abstract

This paper attempts to predict the volatility of interest rates through dynamic term structure models. For this attempt, the models are improved, based on the three-factor Gaussian model, to have level-dependent volatilities supported by data. The empirical results show that the predictive power of the proposed models is higher than that of the affine models. Compared with time-series models, it is low for the four-week forecasting horizon but can be comparable for middle to long term rates by extending the horizon up to 32 weeks. The combination of these two different types of forecasts can lead to higher predictive power.

Suggested Citation

  • Hideyuki Takamizawa, 2010. "Term Structure Models Can Predict Interest Rate Volatility. But How?," Tsukuba Economics Working Papers 2010-008, Faculty of Humanities and Social Sciences, University of Tsukuba.
  • Handle: RePEc:tsu:tewpjp:2010-008
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    File URL: https://pepp.hass.tsukuba.ac.jp/RePEc/2010-008.pdf
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    1. 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.
    2. Pierre Collin‐Dufresne & Robert S. Goldstein & Christopher S. Jones, 2008. "Identification of Maximal Affine Term Structure Models," Journal of Finance, American Finance Association, vol. 63(2), pages 743-795, April.
    3. Ait-Sahalia, Yacine, 1996. "Testing Continuous-Time Models of the Spot Interest Rate," Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 385-426.
    4. Pierre Collin‐Dufresne & Robert S. Goldstein, 2002. "Do Bonds Span the Fixed Income Markets? Theory and Evidence for Unspanned Stochastic Volatility," Journal of Finance, American Finance Association, vol. 57(4), pages 1685-1730, August.
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    Cited by:

    1. Hideyuki Takamizawa, 2015. "Predicting Interest Rate Volatility Using Information on the Yield Curve," International Review of Finance, International Review of Finance Ltd., vol. 15(3), pages 347-386, September.

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