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Revisiting the Dynamic Linkages of Treasury Bond Yields for the BRICS: A Forecasting Analysis

Author

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  • Stelios Bekiros

    (Department of Economics, European University Institute (EUI), I-50014 Florence, Italy
    Athens University of Economics and Business, (AUEB), 10434 Athens, Greece)

  • Christos Avdoulas

    (Athens University of Economics and Business, (AUEB), 10434 Athens, Greece
    Interamerican Research Center (IRC), INTERAMERICAN part of ACHMEA, 11782 Athens, Greece)

Abstract

We examined the dynamic linkages among money market interest rates in the so-called “BRICS” countries (Brazil, Russia, India, China, and South Africa) by using weekly data of the overnight, one-, three-, and six- months, as well as of one year, Treasury bills rates covering the period from January 2005 to August 2019. A long-run relationship among interest rates was established by employing the Vector Error Correction modeling (VECM), which revealed the validation of the Expectation Hypothesis Theory (EH) of the term structure of interest rates, taking into account long-run deviations from equilibrium and inherent nonlinearities. We unveiled short-run dynamic adjustments for the term structure of the BRICS, subject to regime switches. We then used Markov Switching Vector Error Correction models (MS-VECM) to forecast them dynamically during an out-of-sample period of May 2016 through August 2019. The MSIH-VECM forecasts were found to be superior to the VECM approaches. The novelty of our paper is mainly due to the exploration of the possibility of parameter instability as a crucial factor, which might explain the rejection of the restricted version of the cointegration space, and on the dynamic out-of-sample forecasts of the term structure over a more recent time span in order to assess further the usefulness of our nonlinear MS-VECM characterization of the term structure, capturing the effects of the global and domestic financial crisis.

Suggested Citation

  • Stelios Bekiros & Christos Avdoulas, 2020. "Revisiting the Dynamic Linkages of Treasury Bond Yields for the BRICS: A Forecasting Analysis," Forecasting, MDPI, vol. 2(2), pages 1-28, May.
  • Handle: RePEc:gam:jforec:v:2:y:2020:i:2:p:6-129:d:359124
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    References listed on IDEAS

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    3. Oleksandr Castello & Marina Resta, 2022. "Modeling the Yield Curve of BRICS Countries: Parametric vs. Machine Learning Techniques," Risks, MDPI, vol. 10(2), pages 1-18, February.

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