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Sources of Time Variation in the Covariance Matrix of Interest Rates

Author

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  • Christophe Pérignon

    (Simon Fraser University)

  • Christophe Villa

    (ENSAI, CREST-LSM, and CREM)

Abstract

The main objective of this paper is to study the sources of time variation in the covariance matrix of interest rates. We depart from the traditional standard deviation–correlation decomposition of covariances and investigate whether time variation in the covariance matrix of bond yield changes is caused by time-varying eigenvalues and/or eigenvectors. On the basis of a formal testing procedure, we find that common factors display a clear time-varying volatility over the past three decades. Most notably, we observe that the switches in monetary policy that take place with the appointment of a new Federal Reserve chairman play an important role in characterizing the time variation in the loadings on the common factors that drive interest rates.

Suggested Citation

  • Christophe Pérignon & Christophe Villa, 2006. "Sources of Time Variation in the Covariance Matrix of Interest Rates," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1535-1550, May.
    • Handle: RePEc:ucp:jnlbus:v:79:y:2006:i:3:p:1535-1550
    DOI: 10.1086/500684
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    Cited by:

    1. Dennis Philip & Chihwa Kao & Giovanni Urga, 2007. "Testing for Instability in Factor Structure of Yield Curves," Center for Policy Research Working Papers 96, Center for Policy Research, Maxwell School, Syracuse University.
    2. Hideyuki Takamizawa, 2018. "A term structure model of interest rates with quadratic volatility," Quantitative Finance, Taylor & Francis Journals, vol. 18(7), pages 1173-1198, July.
    3. Perignon, Christophe & Smith, Daniel R., 2007. "Yield-factor volatility models," Journal of Banking & Finance, Elsevier, vol. 31(10), pages 3125-3144, October.
    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. Goyal, Amit & Pérignon, Christophe & Villa, Christophe, 2008. "How common are common return factors across the NYSE and Nasdaq?," Journal of Financial Economics, Elsevier, vol. 90(3), pages 252-271, December.
    6. Craig S. Hakkio & William R. Keeton, 2009. "Financial stress: what is it, how can it be measured, and why does it matter?," Economic Review, Federal Reserve Bank of Kansas City, vol. 94(Q II), pages 5-50.
    7. Liu, Baisen & Xu, Lin & Zheng, Shurong & Tian, Guo-Liang, 2014. "A new test for the proportionality of two large-dimensional covariance matrices," Journal of Multivariate Analysis, Elsevier, vol. 131(C), pages 293-308.
    8. Galluccio, Stefano & Roncoroni, Andrea, 2006. "A new measure of cross-sectional risk and its empirical implications for portfolio risk management," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2387-2408, August.
    9. Dungey, Mardi & McKenzie, Michael & Smith, L. Vanessa, 2009. "Empirical evidence on jumps in the term structure of the US Treasury Market," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 430-445, June.
    10. Juneja, Januj, 2012. "Common factors, principal components analysis, and the term structure of interest rates," International Review of Financial Analysis, Elsevier, vol. 24(C), pages 48-56.
    11. Chihwa Kao & Lorenzo Trapani & Giovanni Urga, 2007. "Modelling and Testing for Structural Changes in Panel Cointegration Models with Common and Idiosyncratic Stochastic Trend," Center for Policy Research Working Papers 92, Center for Policy Research, Maxwell School, Syracuse University.
    12. Perignon, Christophe & Smith, Daniel R. & Villa, Christophe, 2007. "Why common factors in international bond returns are not so common," Journal of International Money and Finance, Elsevier, vol. 26(2), pages 284-304, March.
    13. Takamizawa, Hideyuki & 高見澤, 秀幸, 2015. "Impact of No-arbitrage on Interest Rate Dynamics," Working Paper Series G-1-5, Hitotsubashi University Center for Financial Research.

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