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Term structure estimation with missing data: Application for emerging markets

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  • Nagy, Krisztina
Abstract
This paper addresses the challenge of estimating the term structure of interest rates with missing data. There is a void in the term structure literature when it comes to estimation techniques addressing the challenge of sparse bond price data. Our aim is twofold: (1) to establish an estimation technique that can deal with the missing data problem, and (2) to apply this technique to estimate the term structure of interest rates in Hungary. Hungary offers a unique test of the state-space methodology because it is a relatively developed and stable economy while the bond market is not mature. We show that state-space form of the Nelson–Siegel yield curve can provide efficient estimation in the presence of missing data.

Suggested Citation

  • Nagy, Krisztina, 2020. "Term structure estimation with missing data: Application for emerging markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 347-360.
    • Handle: RePEc:eee:quaeco:v:75:y:2020:i:c:p:347-360
    DOI: 10.1016/j.qref.2019.04.002
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    2. Alamoodi, A.H. & Zaidan, B.B. & Zaidan, A.A. & Albahri, O.S. & Chen, Juliana & Chyad, M.A. & Garfan, Salem & Aleesa, A.M., 2021. "Machine learning-based imputation soft computing approach for large missing scale and non-reference data imputation," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    3. Makushkin, Mikhail & Lapshin, Victor, 2023. "Dynamic Nelson–Siegel model for market risk estimation of bonds: Practical implementation," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 69, pages 5-27.
    4. Oleksandr Castello & Marina Resta, 2023. "A Machine-Learning-Based Approach for Natural Gas Futures Curve Modeling," Energies, MDPI, vol. 16(12), pages 1-22, June.

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    More about this item

    Keywords

    Term structure; Yield curve; Factor model; Nelson–Siegel curve; Emerging markets; State-space models;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • E4 - Macroeconomics and Monetary Economics - - Money and Interest Rates
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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