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The monetary model of exchange rates is better than the random walk in out-of-sample forecasting

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  • Imad Moosa
  • Kelly Burns

Abstract

It is demonstrated that the monetary model of exchange rates is better than the random walk in out-of-sample forecasting if forecasting accuracy is measured by metrics that take into account the magnitude of the forecasting errors and the ability of the model to predict the direction of change. It is suggested that such a metric is the numerical value of the Wald test statistic for the joint coefficient restriction implied by the line of perfect forecast. The results reveal that the monetary model outperforms the random walk in out-of-sample forecasting for four different exchange rates.

Suggested Citation

  • Imad Moosa & Kelly Burns, 2013. "The monetary model of exchange rates is better than the random walk in out-of-sample forecasting," Applied Economics Letters, Taylor & Francis Journals, vol. 20(14), pages 1293-1297, September.
    • Handle: RePEc:taf:apeclt:v:20:y:2013:i:14:p:1293-1297
    DOI: 10.1080/13504851.2013.799753
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    References listed on IDEAS

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    1. Imad Moosa, 2013. "Why is it so difficult to outperform the random walk in exchange rate forecasting?," Applied Economics, Taylor & Francis Journals, vol. 45(23), pages 3340-3346, August.
    2. Philippe Bacchetta & Eric Van Wincoop, 2006. "Can Information Heterogeneity Explain the Exchange Rate Determination Puzzle?," American Economic Review, American Economic Association, vol. 96(3), pages 552-576, June.
    3. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
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    1. Imad Moosa & Kelly Burns, 2016. "The random walk as a forecasting benchmark: drift or no drift?," Applied Economics, Taylor & Francis Journals, vol. 48(43), pages 4131-4142, September.
    2. Imad A. Moosa, 2015. "The random walk versus unbiased efficiency: can we separate the wheat from the chaff?," Journal of Post Keynesian Economics, Taylor & Francis Journals, vol. 38(2), pages 251-279, October.
    3. Kelly Burns, 2016. "A Reconsideration of the Meese-Rogoff Puzzle: An Alternative Approach to Model Estimation and Forecast Evaluation," Multinational Finance Journal, Multinational Finance Journal, vol. 20(1), pages 41-83, March.
    4. Works, Richard Floyd, 2016. "Econometric modeling of exchange rate determinants by market classification: An empirical analysis of Japan and South Korea using the sticky-price monetary theory," MPRA Paper 76382, University Library of Munich, Germany.
    5. Moosa, Imad & Burns, Kelly, 2014. "The unbeatable random walk in exchange rate forecasting: Reality or myth?," Journal of Macroeconomics, Elsevier, vol. 40(C), pages 69-81.
    6. Dipanwita Barai & Thomas M. Fullerton, Jr. & Adam G. Walke, 2018. "Exchange Rate Forecast Futility For The Taka," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 6(2), pages 1-7.

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