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Exchange Rate Predictability with Nine Alternative Models for BRICS Countries

Author

Listed:
  • Afees A. Salisu

    (Centre for Econometric & Allied Research, University of Ibadan, Ibadan, Nigeria)

  • Rangan Gupta

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

  • Won Joong Kim

    (Department of Economics, Konkuk University, Seoul, Republic of Korea)

Abstract

We examine exchange rate predictability using time-varying and constant parameter models that are conditioned on three variants of Taylor rules as well as six additional alternative models, namely, monetary model (MM); purchasing power parity (PPP); uncovered interest rate parity (UIRP) and three different factor (F1, F2 and F3) models, for BRICS countries. Monthly consumer price index, industrial production index, interest rate, broad money and exchange rates were used to construct the alternative fundamentals for exchange rate predictability for the period of January 1999 and March 2020. The out-of-sample forecast performances of the contending models were evaluated at the forecasting horizons of 1, 4, 8 and 12 using RMSFE and DM statistics, under the full, pre-GFC and post-GFC sample periods. We find that models conditioned on the Taylor rule fundamentals with homogeneous coefficients without interest rate smoothing as well as PPP- and UIRP-based fundamentals offer better exchange rate predictability of the BRICS than the random walk model across the forecast horizons. In addition, constant parameter models offer superior forecasting ability relative to the time-varying parameter models. Our results are sensitive to the data sample, frequency and the choice of fundamentals captured in the predictive model of exchange rate.

Suggested Citation

  • Afees A. Salisu & Rangan Gupta & Won Joong Kim, 2021. "Exchange Rate Predictability with Nine Alternative Models for BRICS Countries," Working Papers 202116, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202116
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    Cited by:

    1. Utkarsh Kumar & Wasim Ahmad & Gazi Salah Uddin, 2024. "Bayesian Markov switching model for BRICS currencies' exchange rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2322-2340, September.
    2. Wu, Yimin, 2024. "Estimating the precise form of uncovered interest parity under the Stock–Watson dynamic OLS approach," Finance Research Letters, Elsevier, vol. 67(PB).
    3. Tanujit Chakraborty & Donia Besher & Madhurima Panja & Shovon Sengupta, 2025. "Neural ARFIMA model for forecasting BRIC exchange rates with long memory under oil shocks and policy uncertainties," Papers 2509.06697, arXiv.org.

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    Keywords

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    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications

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