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Forecasting the Term Structure of Interest Rates of the BRICS: Evidence from a Nonparametric Functional Data Analysis

Author

Listed:
  • Joao F. Caldeira

    (Department of Economics, Universidade Federal do Rio Grande do Sul and CNPq, Brazil)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, South Africa)

  • Tahir Suleman

    (School of Economics and Finance, Victoria University of Wellington & School of Business, Wellington Institute of Technology, New Zealand)

  • Hudson S. Torrent

    (Department of Statistics, Universidade Federal do Rio Grande do Sul, Brazil)

Abstract

In this paper, we develop a non-parametric functional data analysis (NP-FDA) model to forecast the term-structure of Brazil, Russia, India, China and South Africa (BRICS). We use daily data over the period of January 1, 2010 to December 31, 2016. We find that, while it is in general difficult to beat the random-walk model in the shorter-horizons, at longer-runs our proposed NP-FDA approach outperforms not only the random-walk model, but also other popular competitors used in term-structure forecasting literature. Our results have important implications for both policymakers aiming to stabilize the economy, and for optimal portfolio allocation decisions of financial market agents.

Suggested Citation

  • Joao F. Caldeira & Rangan Gupta & Tahir Suleman & Hudson S. Torrent, 2019. "Forecasting the Term Structure of Interest Rates of the BRICS: Evidence from a Nonparametric Functional Data Analysis," Working Papers 201911, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201911
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    22. 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.
    23. JoÃo Caldeira & Hudson Torrent, 2017. "Forecasting the US Term Structure of Interest Rates Using Nonparametric Functional Data Analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(1), pages 56-73, January.
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    Cited by:

    1. Rangan Gupta & Syed Jawad Hussain Shahzad & Xin Sheng & Sowmya Subramaniam, 2023. "The role of oil and risk shocks in the high‐frequency movements of the term structure of interest rates: Evidence from the U.S. Treasury market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1845-1857, April.
    2. Rangan Gupta & Syed Jawad Hussain Shahzad & Xin Sheng & Sowmya Subramaniam, 2020. "The Role of Oil and Risk Shocks in the High-Frequency Movements of the Term Structure of Interest Rates of the United States," Working Papers 202063, University of Pretoria, Department of Economics.
    3. Elie Bouri & Rangan Gupta & Clement Kweku Kyei & Sowmya Subramaniam, 2020. "High-Frequency Movements of the Term Structure of Interest Rates of the United States: The Role of Oil Market Uncertainty," Working Papers 202085, University of Pretoria, Department of Economics.

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    More about this item

    Keywords

    Functional data analysis; yield curve forecasting; performance evaluation; BRICS;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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