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Forecasting the daily exchange rate of the UK pound sterling against the US dollar

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  • Darvas, Zsolt
  • Schepp, Zoltán

Abstract

This paper is the first to use an economic theory-based model—the monetary model of exchange rates within a rational expectations present value framework—to forecast the daily exchange rate of a major currency. Our out-of-sample forecast evaluation period, spanning from 1990 to 2024, is longer than that of any other exchange rate forecasting study. We find that our model's forecasts outperform the random walk across all forecasting horizons, ranging from one day to five years. Moreover, a trading strategy based on our model's forecasts yields economically and statistically significant excess returns, surpassing those of the carry trade strategy.

Suggested Citation

  • Darvas, Zsolt & Schepp, Zoltán, 2025. "Forecasting the daily exchange rate of the UK pound sterling against the US dollar," Finance Research Letters, Elsevier, vol. 71(C).
    • Handle: RePEc:eee:finlet:v:71:y:2025:i:c:s1544612324014806
    DOI: 10.1016/j.frl.2024.106451
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    References listed on IDEAS

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    1. Charles Engel & Kenneth D. West, 2005. "Exchange Rates and Fundamentals," Journal of Political Economy, University of Chicago Press, vol. 113(3), pages 485-517, June.
    2. Ren, Yu & Wang, Qin & Zhang, Xiangyu, 2019. "Short-term exchange rate predictability," Finance Research Letters, Elsevier, vol. 28(C), pages 148-152.
    3. Engel, Charles, 2014. "Exchange Rates and Interest Parity," Handbook of International Economics, in: Gopinath, G. & Helpman, . & Rogoff, K. (ed.), Handbook of International Economics, edition 1, volume 4, chapter 0, pages 453-522, Elsevier.
    4. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    5. Darvas, Zsolt & Schepp, Zoltán, 2024. "Exchange rates and fundamentals: Forecasting with long maturity forward rates," Journal of International Money and Finance, Elsevier, vol. 143(C).
    6. Vasilios Plakandaras & Theophilos Papadimitriou & Periklis Gogas, 2015. "Forecasting Daily and Monthly Exchange Rates with Machine Learning Techniques," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(7), pages 560-573, November.
    7. Rime, Dagfinn & Sarno, Lucio & Sojli, Elvira, 2010. "Exchange rate forecasting, order flow and macroeconomic information," Journal of International Economics, Elsevier, vol. 80(1), pages 72-88, January.
    8. Breen, John David & Hu, Liang, 2021. "The predictive content of oil price and volatility: New evidence on exchange rate forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    9. Shiu‐Sheng Chen & Cheng‐Che Hsu, 2019. "Do stock markets have predictive content for exchange rate movements?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(7), pages 699-713, November.
    10. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    11. Clark, Todd E. & West, Kenneth D., 2006. "Using out-of-sample mean squared prediction errors to test the martingale difference hypothesis," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 155-186.
    12. Pincheira, Pablo M. & West, Kenneth D., 2016. "A comparison of some out-of-sample tests of predictability in iterated multi-step-ahead forecasts," Research in Economics, Elsevier, vol. 70(2), pages 304-319.
    13. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    14. Mark, Nelson C, 1995. "Exchange Rates and Fundamentals: Evidence on Long-Horizon Predictability," American Economic Review, American Economic Association, vol. 85(1), pages 201-218, March.
    15. 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.
    16. Blaskowitz, Oliver & Herwartz, Helmut, 2014. "Testing the value of directional forecasts in the presence of serial correlation," International Journal of Forecasting, Elsevier, vol. 30(1), pages 30-42.
    17. Yin, Libo, 2020. "Can the intermediary capital risk predict foreign exchange rates?," Finance Research Letters, Elsevier, vol. 37(C).
    18. Plakandaras, Vasilios & Gupta, Rangan & Wohar, Mark E., 2017. "The depreciation of the pound post-Brexit: Could it have been predicted?," Finance Research Letters, Elsevier, vol. 21(C), pages 206-213.
    19. Chinn, Menzie D. & Meese, Richard A., 1995. "Banking on currency forecasts: How predictable is change in money?," Journal of International Economics, Elsevier, vol. 38(1-2), pages 161-178, February.
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    More about this item

    Keywords

    Currency trading; Exchange rates; Error correction; Forecasting; Monetary model; Out-of-sample; Random walk;
    All these keywords.

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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