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Yield Curve Modelling with the Nelson-Siegel Method for Poland

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  • Tomasz P. Kostyra

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

  • Tomasz P. Kostyra, 2022. "Yield Curve Modelling with the Nelson-Siegel Method for Poland," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 2, pages 44-56.
    • Handle: RePEc:sgh:gosnar:y:2022:i:2:p:44-56
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    References listed on IDEAS

    as
    1. Lars E.O. Svensson, 1994. "Estimating and Interpreting Forward Interest Rates: Sweden 1992 - 1994," NBER Working Papers 4871, National Bureau of Economic Research, Inc.
    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. Ibanez, Francisco, 2015. "Calibrating the Dynamic Nelson-Siegel Model: A Practitioner Approach," MPRA Paper 68377, University Library of Munich, Germany.
    4. 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.
    5. 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.
    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. 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. 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.
    9. Alois Geyer & Richard Mader, 1999. "Estimation of the term structure of interest rates - A parametric approach," Working Papers 37, Oesterreichische Nationalbank (Austrian Central Bank).
    10. 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.
    11. 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.
    12. 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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    More about this item

    Keywords

    yield curve; bootstrapping; Nelson-Siegel model;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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