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Identifying Term Structure Volatility from the LIBOR-Swap Curve

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  • Samuel Thompson

Abstract

This paper proposes a new family of specification tests and applies them to affine term structure models of the London Interbank Offered Rate (LIBOR)-swap curve. Contrary to Dai and Singleton (2000), the tests show that when standard estimation techniques are used, affine models do a poor job of forecasting volatility at the short end of the term structure. Improving the volatility forecast does not require different models; rather, it requires a different estimation technique. The paper distinguishes between two econometric procedures for identifying volatility. The 'cross-sectional' approach backs out volatility from a cross section of bond yields, and the 'time-series' approach imputes volatility from time-series variation in yields. For an affine model, the volatility implied by the time-series procedure passes the specification tests, while the cross-sectionally identified volatility does not. This is surprising, since under correct specification, the 'cross-sectional' approach is maximum likelihood. One explanation is that affine models are slightly misspecified; another is that bond yields do not span volatility, as in Collin-Dufresne and Goldstein (2002). , Oxford University Press.

Suggested Citation

  • Samuel Thompson, 2008. "Identifying Term Structure Volatility from the LIBOR-Swap Curve," Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 819-854, April.
  • Handle: RePEc:oup:rfinst:v:21:y:2008:i:2:p:819-854
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    File URL: http://hdl.handle.net/10.1093/rfs/hhm082
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    Cited by:

    1. Almeida, Caio & Graveline, Jeremy J. & Joslin, Scott, 2011. "Do interest rate options contain information about excess returns?," Journal of Econometrics, Elsevier, vol. 164(1), pages 35-44, September.
    2. Christensen, Jens H.E. & Lopez, Jose A. & Rudebusch, Glenn D., 2015. "A probability-based stress test of Federal Reserve assets and income," Journal of Monetary Economics, Elsevier, vol. 73(C), pages 26-43.
    3. repec:hal:journl:peer-00796745 is not listed on IDEAS
    4. 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.
    5. Corradi, Valentina & Swanson, Norman R., 2011. "Predictive density construction and accuracy testing with multiple possibly misspecified diffusion models," Journal of Econometrics, Elsevier, vol. 161(2), pages 304-324, April.
    6. Cheridito, Patrick & Filipovic, Damir & Kimmel, Robert L., 2006. "Affine Term Structure Models," Working Paper Series 2007-2, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    7. Aït-Sahalia, Yacine & Kimmel, Robert L., 2010. "Estimating affine multifactor term structure models using closed-form likelihood expansions," Journal of Financial Economics, Elsevier, vol. 98(1), pages 113-144, October.
    8. Cai, Lili & Swanson, Norman R., 2011. "In- and out-of-sample specification analysis of spot rate models: Further evidence for the period 1982-2008," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 743-764, September.
    9. Peter Christoffersen & Christian Dorion & Kris Jacobs & Lotfi Karoui, 2014. "Nonlinear Kalman Filtering in Affine Term Structure Models," Management Science, INFORMS, vol. 60(9), pages 2248-2268, September.
    10. Aït-Sahalia, Yacine & Fan, Jianqing & Peng, Heng, 2009. "Nonparametric Transition-Based Tests for Jump Diffusions," Journal of the American Statistical Association, American Statistical Association, vol. 104(487), pages 1102-1116.
    11. Diep Duong & Norman Swanson, 2013. "Density and Conditional Distribution Based Specification Analysis," Departmental Working Papers 201312, Rutgers University, Department of Economics.
    12. Fuchun Li, 2015. "Testing for the Diffusion Matrix in a Continuous-Time Markov Process Model with Applications to the Term Structure of Interest Rates," Staff Working Papers 15-17, Bank of Canada.

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