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Modelowanie krzywej dochodowości dla Polski z wykorzystaniem metody Nelsona-Siegla

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  • Kostyra, Tomasz P.

Abstract

Yield curve modelling is an essential task for the governance of the modern economy and in particular for financial market participants, and hence it is an extensively researched topic. This paper presents yield curve modelling using the Nelson-Siegel approach for Poland, which was recently recognised as a developed country. Yield curve studies available for Poland are quite scarce and were conducted when Poland was still classified as a developing country. Therefore, it is worthwhile to examine the yield curve construction after three decades of economic transition. This study offers a model which, with certain assumptions, derives zero-coupon yield curves from the market prices of Treasury bonds. The simplifying assumptions reduce model development time, while delivering yield curves of higher accuracy than those commercially available.

Suggested Citation

  • Kostyra, Tomasz P., . "Modelowanie krzywej dochodowości dla Polski z wykorzystaniem metody Nelsona-Siegla," Gospodarka Narodowa-The Polish Journal of Economics, Szkoła Główna Handlowa w Warszawie / SGH Warsaw School of Economics, vol. 2022(2).
    • Handle: RePEc:ags:polgne:359261
    DOI: 10.22004/ag.econ.359261
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    References listed on IDEAS

    as
    1. Nymand-Andersen, Per, 2018. "Yield curve modelling and a conceptual framework for estimating yield curves: evidence from the European Central Bank’s yield curves," Statistics Paper Series 27, European Central Bank.
    2. Tomasz Piotr Kostyra & Michał Rubaszek, 2020. "Forecasting the Yield Curve for Poland," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 5(2), pages 103-117, December.
    3. Jozef Glova, 2010. "Matrix Theory Application in the Bootstrapping Method for the Term Structure of Interest Rates," Economic Analysis, Institute of Economic Sciences, vol. 43(1-2), pages 44-49.
    4. Michał Rubaszek, 2016. "Forecasting the Yield Curve With Macroeconomic Variables," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 1(1), pages 1-21, June.
    5. 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.
    6. Diebold, Francis X. & Li, Canlin, 2006. "Forecasting the term structure of government bond yields," Journal of Econometrics, Elsevier, vol. 130(2), pages 337-364, February.
    7. Annaert, Jan & Claes, Anouk G.P. & De Ceuster, Marc J.K. & Zhang, Hairui, 2013. "Estimating the spot rate curve using the Nelson–Siegel model," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 482-496.
    8. Diebold, Francis X. & Rudebusch, Glenn D. & Borag[caron]an Aruoba, S., 2006. "The macroeconomy and the yield curve: a dynamic latent factor approach," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 309-338.
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