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Exchange rate forecasting on a napkin

Author

Listed:
  • Michele Ca' Zorzi

    (European Central Bank)

  • Micha􏰀l Rubaszek

    (SGH Warsaw School of Economics)

Abstract

This paper shows that there are two regularities in foreign exchange markets in advanced countries with flexible regimes. First, real exchange rates are mean-reverting, as implied by the Purchasing Power Parity model. Second, the adjustment takes place via nominal exchange rates. These features of the data can be exploited, even on the back of a napkin, to generate nominal exchange rate forecasts that outperform the random walk. The secret is to avoid estimating the pace of mean reversion and assume that relative prices are unchanged. Direct forecasting or panel data techniques are better than the random walk but fail to beat this simple calibrated model.

Suggested Citation

  • Michele Ca' Zorzi & Micha􏰀l Rubaszek, 2018. "Exchange rate forecasting on a napkin," GRU Working Paper Series GRU_2018_025, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    • Handle: RePEc:cth:wpaper:gru_2018_025
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    File URL: https://www.cb.cityu.edu.hk/ef/doc/GRU/WPS/GRU%232018-025%20Ca'Zorzi.pdf
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    2. Michał Rubaszek & Joscha Beckmann & Michele Ca’ Zorzi & Marek Kwas, 2025. "Boosting Carry with Equilibrium Exchange Rate Estimates," Open Economies Review, Springer, vol. 36(4), pages 1281-1307, September.
    3. Yin-Wong Cheung & Wenhao Wang & Frank Westermann, 2025. "An In-Sample Evaluation of Exchange Rate Models: In Search of Scapegoats," IEER Working Papers 125, Institute of Empirical Economic Research, Osnabrueck University.
    4. Oscar Claveria & Enric Monte & Petar Soric & Salvador Torra, 2022. "“An application of deep learning for exchange rate forecasting”," AQR Working Papers 202201, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2022.
    5. Martin McCarthy, Stephen Snudden, 2024. "Forecasts of Period-Average Exchange Rates: New Insights from Real-Time Daily Data," LCERPA Working Papers jc0148, Laurier Centre for Economic Research and Policy Analysis, revised Oct 2024.
    6. Yang, Hu & Chen, Yu & Chen, Kedong & Wang, Haijun, 2024. "Temporal-spatial dependencies enhanced deep learning model for time series forecast," International Review of Financial Analysis, Elsevier, vol. 94(C).
    7. Nasir, Muhammad Ali, 2020. "Forecasting inflation under uncertainty: The forgotten dog and the frisbee," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    8. de Souza Vasconcelos, Camila & Hadad Júnior, Eli, 2023. "Forecasting exchange rate: A bibliometric and content analysis," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 607-628.
    9. Kwas, Marek & Beckmann, Joscha & Rubaszek, Michał, 2024. "Are consensus FX forecasts valuable for investors?," International Journal of Forecasting, Elsevier, vol. 40(1), pages 268-284.
    10. Liu, Congzheng & Letchford, Adam N. & Svetunkov, Ivan, 2022. "Newsvendor problems: An integrated method for estimation and optimisation," European Journal of Operational Research, Elsevier, vol. 300(2), pages 590-601.
    11. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    12. Ca’ Zorzi, Michele & Rubaszek, Michał, 2023. "How many fundamentals should we include in the behavioral equilibrium exchange rate model?," Economic Modelling, Elsevier, vol. 118(C).
    13. Piotr Dybka, 2020. "One model or many? Exchange rates determinants and their predictive capabilities," KAE Working Papers 2020-053, Warsaw School of Economics, Collegium of Economic Analysis.
    14. Helder Ferreira de Mendonça & Luciano Vereda & Luan Mateus Matos de Araújo, 2025. "Fundamentals Models Versus Random Walk: Evidence From an Emerging Economy," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(6), pages 1884-1906, September.
    15. 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).
    16. Feng, Wenjun & Zhang, Zhengjun, 2023. "Currency exchange rate predictability: The new power of Bitcoin prices," Journal of International Money and Finance, Elsevier, vol. 132(C).
    17. Wada, Tatsuma, 2022. "Out-of-sample forecasting of foreign exchange rates: The band spectral regression and LASSO," Journal of International Money and Finance, Elsevier, vol. 128(C).
    18. Engel, Charles & Wu, Steve Pak Yeung, 2023. "Forecasting the U.S. Dollar in the 21st Century," Journal of International Economics, Elsevier, vol. 141(C).
    19. Krystian Jaworski, 2021. "Forecasting exchange rates for Central and Eastern European currencies using country‐specific factors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 977-999, September.
    20. David Alaminos & M. Belén Salas & Manuel Á. Fernández-Gámez, 2023. "Quantum Monte Carlo simulations for estimating FOREX markets: a speculative attacks experience," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 10(1), pages 1-21, December.
    21. Marek Kwas & Michał Rubaszek, 2021. "Forecasting Commodity Prices: Looking for a Benchmark," Forecasting, MDPI, vol. 3(2), pages 1-13, June.
    22. Jen Baggs & Loretta Fung & Beverly Lapham, 2021. "An Empirical Evaluation of the Effect of Covid-19 Travel Restrictions on Canadians' Cross Border Travel and Canadian Retailers," Working Paper 1457, Economics Department, Queen's University.
    23. Jackson, Karen & Magkonis, Georgios, 2024. "Exchange rate predictability: Fact or fiction?," Journal of International Money and Finance, Elsevier, vol. 142(C).

    More about this item

    Keywords

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics

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