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The Depreciation of the Pound Post-Brexit: Could it have been Predicted?

Author

Listed:
  • Vasilios Plakandaras

    (Department of Economics, Democritus University of Thrace, Greece)

  • Rangan Gupta

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

  • Mark E. Wohar

    (College of Business Administration, University of Nebraska at Omaha USA, and School of Business and Economics, Loughborough University)

Abstract

The decision of the United Kingdom to leave the European Union (Brexit) after 43 years caused turmoil in exchange rate and global stock markets. More specifically, the pound relative to the dollar has lost close to 15 percent of its value in the weeks after the Brexit decision. In this paper we attempt to examine whether this sudden depreciation of the (pound-dollar) exchange rate is the reaction of market participants to the Brexit or whether the exodus of UK from the EU had little impact on the exchange rate. In doing so, we train linear and nonlinear econometric and machine learning models and evaluate out-of-sample forecasts of the exchange rate and its realized volatility in the pre- and post-Brexit period. We quantify uncertainty caused by the Brexit according to an index based on news related to economic uncertainty. We argue that in daily forecasting horizon our models adhere closely to the evolution of the exchange rate and that most of the depreciation is based on the uncertainty caused by the Brexit.

Suggested Citation

  • Vasilios Plakandaras & Rangan Gupta & Mark E. Wohar, 2016. "The Depreciation of the Pound Post-Brexit: Could it have been Predicted?," Working Papers 201670, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:201670
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    References listed on IDEAS

    as
    1. Mehmet Balcilar & Rangan Gupta & Clement Kyei & Mark E. Wohar, 2016. "Does Economic Policy Uncertainty Predict Exchange Rate Returns and Volatility? Evidence from a Nonparametric Causality-in-Quantiles Test," Open Economies Review, Springer, vol. 27(2), pages 229-250, April.
    2. 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.
    3. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    4. Theophilos Papadimitriou & Periklis Gogas & Vasilios Plakandaras, 2013. "Forecasting the NOK/USD Exchange Rate with Machine Learning Techniques," Working Paper series 59_13, Rimini Centre for Economic Analysis.
    5. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, Oxford University Press, vol. 131(4), pages 1593-1636.
    6. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    7. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
    8. Rubio, Ginés & Pomares, Héctor & Rojas, Ignacio & Herrera, Luis Javier, 2011. "A heuristic method for parameter selection in LS-SVM: Application to time series prediction," International Journal of Forecasting, Elsevier, vol. 27(3), pages 725-739, July.
    9. Rubio, Ginés & Pomares, Héctor & Rojas, Ignacio & Herrera, Luis Javier, 2011. "A heuristic method for parameter selection in LS-SVM: Application to time series prediction," International Journal of Forecasting, Elsevier, vol. 27(3), pages 725-739.
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    Cited by:

    1. Ning, Ye & Han, Chenyu & Wang, Yiming, 2018. "The multifractal properties of Euro and Pound exchange rates and comparisons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 578-587.
    2. Dao, Thong M. & McGroarty, Frank & Urquhart, Andrew, 2019. "The Brexit vote and currency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 59(C), pages 153-164.
    3. Rangan Gupta & Tahir Suleman & Mark E. Wohar, 2019. "Exchange rate returns and volatility: the role of time-varying rare disaster risks," The European Journal of Finance, Taylor & Francis Journals, vol. 25(2), pages 190-203, January.
    4. Christina Christou & Rangan Gupta & Christis Hassapis & Tahir Suleman, 2018. "The role of economic uncertainty in forecasting exchange rate returns and realized volatility: Evidence from quantile predictive regressions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(7), pages 705-719, November.
    5. Nikolaos A. Kyriazis & Emmanouil M. L. Economou, 2017. "Brexit Decision Effects on European Derivatives Markets: A Sectoral Analysis," Bulletin of Political Economy, Bulletin of Political Economy, vol. 11(1), pages 45-58, June.
    6. Dong, Xue & Minford, Patrick & Meenagh, David, 2019. "How important are the international financial market imperfections for the foreign exchange rate dynamics: A study of the sterling exchange rate," Journal of International Money and Finance, Elsevier, vol. 94(C), pages 62-80.
    7. Akram Alkhatib & Murad Harasheh, 2018. "Performance of Exchange Traded Funds during the Brexit Referendum: An Event Study," IJFS, MDPI, vol. 6(3), pages 1-12, July.
    8. Plakandaras, Vasilios & Tiwari, Aviral Kumar & Gupta, Rangan & Ji, Qiang, 2020. "Spillover of sentiment in the European Union: Evidence from time- and frequency-domains," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 105-130.
    9. Abuzayed, Bana & Al-Fayoumi, Nedal & Bouri, Elie, 2022. "Hedging UK stock portfolios with gold and oil: The impact of Brexit," Resources Policy, Elsevier, vol. 75(C).
    10. Han, Chenyu & Wang, Yiming & Ning, Ye, 2019. "Comparative analysis of the multifractality and efficiency of exchange markets: Evidence from exchange rates dynamics of major world currencies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    11. Huang, Yisu & Ma, Feng & Bouri, Elie & Huang, Dengshi, 2023. "A comprehensive investigation on the predictive power of economic policy uncertainty from non-U.S. countries for U.S. stock market returns," International Review of Financial Analysis, Elsevier, vol. 87(C).

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    More about this item

    Keywords

    Brexit; Economic Uncertainty; Machine Learning;
    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

    NEP fields

    This paper has been announced in the following NEP Reports:

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