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A nonparametric method for term structure fitting with automatic smoothing

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  • Vadim Kaushanskiy
  • Victor Lapshin

Abstract

We present a nonparametric method for fitting the term structure of interest rates from bond prices. Our method is a variant of the smoothing spline approach, but within our framework we are able to determine the smoothing coefficient automatically from data using the generalized cross-validation or maximum likelihood estimates. We present an effective numerical algorithm to simultaneously find the term structure and the optimal smoothing coefficient. Finally, we compare the proposed nonparametric fitting method with other parametric and nonparametric methods to find its superior performance. We find that existing term structure fitting methods perform well in liquid markets while illiquid markets present new challenges, which we address in this article.

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  • Vadim Kaushanskiy & Victor Lapshin, 2016. "A nonparametric method for term structure fitting with automatic smoothing," Applied Economics, Taylor & Francis Journals, vol. 48(58), pages 5654-5666, December.
    • Handle: RePEc:taf:applec:v:48:y:2016:i:58:p:5654-5666
    DOI: 10.1080/00036846.2016.1181835
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    1. Victor Lapshin, 2019. "A Nonparametric Approach to Bond Portfolio Immunization," Mathematics, MDPI, vol. 7(11), pages 1-12, November.

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    More about this item

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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