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Forecasting The Rand-Dollar And Rand-Pound Exchange Rates Using Dynamic Model Averaging

Author

Listed:
  • Riane de Bruyn

    (Department of Economics, University of Pretoria)

  • Rangan Gupta

    (Department of Economics, University of Pretoria)

  • Renee van Eyden

    (Department of Economics, University of Pretoria)

Abstract
Traditionally, the literature on forecasting exchange rates with many potential predictors have primarily only accounted for parameter uncertainty using Bayesian Model Averaging (BMA). Though BMA-based models of exchange rates tend to outperform the random walk model, we show that when accounting for model uncertainty over and above parameter uncertainty through the use of Dynamic model Averaging (DMA), the gains relative to the random walk model are even bigger. That is, DMA models outperform not only the random walk model, but also the BMA model of exchange rates. We obtain these results based on fifteen potential predictors used to forecast two South African Rand-based exchange rates. In the process, we also unveil variables, which tends to vary over time, that are good predictors of the Rand-Dollar and Rand-Pound exchange rates at different forecasting horizons.

Suggested Citation

  • Riane de Bruyn & Rangan Gupta & Renee van Eyden, 2013. "Forecasting The Rand-Dollar And Rand-Pound Exchange Rates Using Dynamic Model Averaging," Working Papers 201307, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201307
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    References listed on IDEAS

    as
    1. Martin Feldkircher, 2012. "Forecast Combination and Bayesian Model Averaging: A Prior Sensitivity Analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 31(4), pages 361-376, July.
    2. Jacob Gyntelberg & Mico Loretan & Tientip Subhanij & Eric Chan, 2010. "Private information, stock markets, and exchange rates," BIS Papers chapters, in: Bank for International Settlements (ed.), The international financial crisis and policy challenges in Asia and the Pacific, volume 52, pages 186-210, Bank for International Settlements.
    3. L Bonga-Bonga, 2009. "Forward Exchange Rate Puzzle: Joining the Missing Pieces in the Rand-US Dollar Exchange Market," Studies in Economics and Econometrics, Taylor & Francis Journals, vol. 33(2), pages 33-48, August.
    4. Gary Koop & Dimitris Korobilis, 2012. "Forecasting Inflation Using Dynamic Model Averaging," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(3), pages 867-886, August.
    5. Rangan Gupta & Alain Kabundi, 2010. "Forecasting macroeconomic variables in a small open economy: a comparison between small- and large-scale models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 168-185.
    6. Simeon Coleman & Juan Carlos Cuestas & Estefanía Mourelle, 2011. "Investigating the oil price-exchange rate nexus: Evidence from Africa," Working Papers 2011015, The University of Sheffield, Department of Economics, revised May 2011.
    7. Wright, Jonathan H., 2008. "Bayesian Model Averaging and exchange rate forecasts," Journal of Econometrics, Elsevier, vol. 146(2), pages 329-341, October.
    8. Lumengo Bonga-Bonga, 2008. "Modelling the Rand-Dollar Future Spot Rates: The Kalman Filter Approach," The African Finance Journal, Africagrowth Institute, vol. 10(2), pages 60-75.
    9. Hooper, Peter & Morton, John, 1982. "Fluctuations in the dollar: A model of nominal and real exchange rate determination," Journal of International Money and Finance, Elsevier, vol. 1(1), pages 39-56, January.
    10. Samuel Zita & Rangan Gupta, 2008. "Modeling and Forecasting the Metical-Rand Exchange Rate," The IUP Journal of Monetary Economics, IUP Publications, vol. 0(4), pages 63-90, November.
    11. Pami Dua & Rajiv Ranjan, 2011. "Modelling and Forecasting the Indian Re/US Dollar Exchange Rate," Working papers 197, Centre for Development Economics, Delhi School of Economics.
    12. Sami Alpanda & Kevin Kotzé & Geoffrey Woglom, 2011. "Forecasting Performance Of An Estimated Dsge Model For The South African Economy," South African Journal of Economics, Economic Society of South Africa, vol. 79(1), pages 50-67, March.
    13. Riané de Bruyn & Rangan Gupta & Lardo Stander, 2013. "Testing the Monetary Model for Exchange Rate Determination in South Africa: Evidence from 101 Years of Data," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 7(1), March.
    14. Adrian W. Throop, 1993. "A generalized uncovered interest parity model of exchange rates," Economic Review, Federal Reserve Bank of San Francisco, pages 3-16.
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    Cited by:

    1. Gupta, Rangan & Hammoudeh, Shawkat & Kim, Won Joong & Simo-Kengne, Beatrice D., 2014. "Forecasting China's foreign exchange reserves using dynamic model averaging: The roles of macroeconomic fundamentals, financial stress and economic uncertainty," The North American Journal of Economics and Finance, Elsevier, vol. 28(C), pages 170-189.
    2. Mehmet Balcilar & Rangan Gupta & Charl Jooste, 2014. "Is the Rand Really Decoupled from Economic Fundamentals?," Working Papers 201439, University of Pretoria, Department of Economics.
    3. Goodness C. Aye & Mehmet Balcilar & Adél Bosch & Rangan Gupta & Francois Stofberg, 2013. "The out-of-sample forecasting performance of non-linear models of real exchange rate behaviour: The case of the South African Rand," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 10(1), pages 121-148, April.

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    More about this item

    Keywords

    Bayesian; state space models; exchange rates; macroeconomic fundamentals; forecasting;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications

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