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Hedging Long-Term Liabilities
[Pricing the Term Structure with Linear Regressions]

Author

Listed:
  • Rogier Quaedvlieg
  • Peter Schotman

Abstract

Pension funds and life insurers face interest rate risk arising from the duration mismatch of their assets and liabilities. With the aim of hedging long-term liabilities, we estimate variations of a Nelson–Siegel model using swap returns with maturities up to 50 years. We consider versions with three and five factors, as well as constant and time-varying factor loadings. We find that we need either five factors or time-varying factor loadings in the three-factor model to accommodate the long end of the yield curve. The resulting factor hedge portfolios perform poorly due to strong multicollinearity of the factor loadings in the long end, and are easily beaten by a robust, near Mean-Squared-Error- optimal, hedging strategy that concentrates its weight on the longest available liquid bond.

Suggested Citation

  • Rogier Quaedvlieg & Peter Schotman, 2022. "Hedging Long-Term Liabilities [Pricing the Term Structure with Linear Regressions]," Journal of Financial Econometrics, Oxford University Press, vol. 20(3), pages 505-538.
  • Handle: RePEc:oup:jfinec:v:20:y:2022:i:3:p:505-538.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbaa027
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    References listed on IDEAS

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    1. F. Blasques & S. J. Koopman & A. Lucas, 2015. "Information-theoretic optimality of observation-driven time series models for continuous responses," Biometrika, Biometrika Trust, vol. 102(2), pages 325-343.
    2. Michael D. Bauer, 2018. "Restrictions on Risk Prices in Dynamic Term Structure Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(2), pages 196-211, April.
    3. Breitung, Jörg & Eickmeier, Sandra, 2011. "Testing for structural breaks in dynamic factor models," Journal of Econometrics, Elsevier, vol. 163(1), pages 71-84, July.
    4. Caio Almeida & Kym Ardison & Daniela Kubudi & Axel Simonsen & José Vicente, 2018. "Forecasting Bond Yields with Segmented Term Structure Models," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 1-33.
    5. Bams, Dennis & Schotman, Peter C., 2003. "Direct estimation of the risk neutral factor dynamics of Gaussian term structure models," Journal of Econometrics, Elsevier, vol. 117(1), pages 179-206, November.
    6. Adrian, Tobias & Crump, Richard K. & Moench, Emanuel, 2013. "Pricing the term structure with linear regressions," Journal of Financial Economics, Elsevier, vol. 110(1), pages 110-138.
    7. Bianchi, Francesco & Mumtaz, Haroon & Surico, Paolo, 2009. "The great moderation of the term structure of UK interest rates," Journal of Monetary Economics, Elsevier, vol. 56(6), pages 856-871, September.
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    More about this item

    Keywords

    factor models; risk management; term structure;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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