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Exploring the total positivity of yields correlations

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  • A. Goia
  • E. Salinelli

Abstract

We test the plausibility of the total positivity assumption of interest rates changes recently introduced in order to justify the presence of shift, slope and curvature for yield curves. To this aim, we introduce and discuss a test of total positivity of order for covariance and correlation matrices. The explicit expressions of the test statistics are given for Gaussian samples and an extension to a distribution-free framework is made via a bootstrap method. After exploring with simulation the robustness of such tests, we show using real data how it is realistic to assume that correlation matrices of interest rates changes are totally positive of order two. Conclusions on total positivity of order three are more controversial.

Suggested Citation

  • A. Goia & E. Salinelli, 2016. "Exploring the total positivity of yields correlations," Quantitative Finance, Taylor & Francis Journals, vol. 16(4), pages 605-624, April.
    • Handle: RePEc:taf:quantf:v:16:y:2016:i:4:p:605-624
    DOI: 10.1080/14697688.2015.1051097
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    1. John Schoenmakers & Brian Coffey, 2003. "Systematic Generation of Parametric Correlation Structures for the LIBOR Market Model," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 6(05), pages 507-519.
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