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Empirical analysis of term structure shifts

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  • Joel R. Barber

    (Florida International University)

Abstract

Principal component analysis and factor analysis of term structure movements shows that between 80 and 90% of term structure shifts can be explained by a uniform shift that is roughly parallel. In contrast, our analysis of term structure data from 1986 to 2016 reveals that only 57% of the shifts have been uniform. Twist- and butterfly-type shifts accounted for 28 and 10%, respectively, of all shifts. Remarkably, these frequency results are roughly the same for uniform and twist shifts determined on a daily, weekly, and monthly basis over the entire sample and over three subperiods. Based on historical data, an investor should expect a uniform shift in the term structure about 57% and a twist 28% of the time.

Suggested Citation

  • Joel R. Barber, 2021. "Empirical analysis of term structure shifts," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 45(2), pages 360-371, April.
  • Handle: RePEc:spr:jecfin:v:45:y:2021:i:2:d:10.1007_s12197-020-09521-9
    DOI: 10.1007/s12197-020-09521-9
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    References listed on IDEAS

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    1. Emrah Ahi & Vedat Akgiray & Emrah Sener, 2018. "Robust term structure estimation in developed and emerging markets," Annals of Operations Research, Springer, vol. 260(1), pages 23-49, January.
    2. Frederick R. Macaulay, 1938. "Some Theoretical Problems Suggested by the Movements of Interest Rates, Bond Yields and Stock Prices in the United States since 1856," NBER Books, National Bureau of Economic Research, Inc, number maca38-1, July.
    3. Joel Barber & Mark Copper, 2012. "Principal component analysis of yield curve movements," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 36(3), pages 750-765, July.
    4. Lars E.O. Svensson, 1994. "Estimating and Interpreting Forward Interest Rates: Sweden 1992 - 1994," NBER Working Papers 4871, National Bureau of Economic Research, Inc.
    5. 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.
    6. Fisher, Lawrence & Weil, Roman L, 1971. "Coping with the Risk of Interest-Rate Fluctuations: Returns to Bondholders from Naive and Optimal Strategies," The Journal of Business, University of Chicago Press, vol. 44(4), pages 408-431, October.
    7. Svensson, Lars E O, 1994. "Estimating and Interpreting Forward Interest Rates: Sweden 1992-4," CEPR Discussion Papers 1051, C.E.P.R. Discussion Papers.
    8. Michael D. Bauer & James D. Hamilton, 2018. "Robust Bond Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 31(2), pages 399-448.
    9. Arcady Novosyolov & Daniel Satchkov, 2008. "Global term structure modelling using principal component analysis," Journal of Asset Management, Palgrave Macmillan, vol. 9(1), pages 49-60, May.
    10. Nelson, Charles R & Siegel, Andrew F, 1987. "Parsimonious Modeling of Yield Curves," The Journal of Business, University of Chicago Press, vol. 60(4), pages 473-489, October.
    11. Johan Hagenbjörk & Jörgen Blomvall, 2019. "Simulation and evaluation of the distribution of interest rate risk," Computational Management Science, Springer, vol. 16(1), pages 297-327, February.
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    More about this item

    Keywords

    Term structure shift; Spot rates; Principal component analysis;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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