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Global term structure modelling using principal component analysis

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  • Arcady Novosyolov
  • Daniel Satchkov

Abstract

Principal component analysis (PCA) is a technique commonly applied to the interest rate markets to describe yield curve dynamics in a parsimonious manner. Despite an increase in global investing and the growing interconnectedness of the international markets, PCA has not been widely applied to decomposing joint structure of global yield curves. Our objective is to describe the joint structure with a model that can potentially be used for scenario analysis and for estimating the risk of interest rate-sensitive portfolios. In this study, we examine three variations of the PCA technique to decompose global yield curve and interest rate implied volatility structure. We conclude that global yield curve structure can be described with 15–20 factors, whereas implied volatility structure requires at least 20 global factors. The procedure that we identify as preferable is a two-step PCA, with local curves decomposed in the first step and combined local PCs decomposed into a joint structure (PCA of PCs) in the second step. This procedure has a key advantage in that it makes any scenario analysis more meaningful by keeping local PCA factors, which have important economic interpretations as shift, twist and butterfly moves of the yield curve.

Suggested Citation

  • 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.
  • Handle: RePEc:pal:assmgt:v:9:y:2008:i:1:d:10.1057_jam.2008.3
    DOI: 10.1057/jam.2008.3
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    Citations

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    Cited by:

    1. Ling-Ni Boon & Florian Ielpo, 2016. "An anatomy of global risk premiums," Journal of Asset Management, Palgrave Macmillan, vol. 17(4), pages 229-243, July.
    2. 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.
    3. Fendel, Ralf & Neumann, Christian, 2021. "Tail risk in the European sovereign bond market during the financial crises: Detecting the influence of the European Central Bank," Global Finance Journal, Elsevier, vol. 50(C).
    4. 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.

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