IDEAS home Printed from https://ideas.repec.org/a/eee/jimfin/v104y2020ics026156061830192x.html
   My bibliography  Save this article

Exchange rate forecasting on a napkin

Author

Listed:
  • Zorzi, Michele Ca’
  • Rubaszek, Michał

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, panel data techniques and non-linear models can outperform the random walk, but fail to beat this simple calibrated model.

Suggested Citation

  • Zorzi, Michele Ca’ & Rubaszek, Michał, 2020. "Exchange rate forecasting on a napkin," Journal of International Money and Finance, Elsevier, vol. 104(C).
  • Handle: RePEc:eee:jimfin:v:104:y:2020:i:c:s026156061830192x
    DOI: 10.1016/j.jimonfin.2020.102168
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S026156061830192X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jimonfin.2020.102168?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Kenneth Rogoff, 1996. "The Purchasing Power Parity Puzzle," Journal of Economic Literature, American Economic Association, vol. 34(2), pages 647-668, June.
    2. Cheung, Yin-Wong & Chinn, Menzie D. & Pascual, Antonio Garcia & Zhang, Yi, 2019. "Exchange rate prediction redux: New models, new data, new currencies," Journal of International Money and Finance, Elsevier, vol. 95(C), pages 332-362.
    3. Ca’ Zorzi, Michele & Kolasa, Marcin & Rubaszek, Michał, 2017. "Exchange rate forecasting with DSGE models," Journal of International Economics, Elsevier, vol. 107(C), pages 127-146.
    4. Lo, Ming Chien & Morley, James, 2015. "Bayesian analysis of nonlinear exchange rate dynamics and the purchasing power parity persistence puzzle," Journal of International Money and Finance, Elsevier, vol. 51(C), pages 285-302.
    5. Taylor, Mark P & Peel, David A & Sarno, Lucio, 2001. "Nonlinear Mean-Reversion in Real Exchange Rates: Toward a Solution to the Purchasing Power Parity Puzzles," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(4), pages 1015-1042, November.
    6. Kilian, Lutz & Taylor, Mark P., 2003. "Why is it so difficult to beat the random walk forecast of exchange rates?," Journal of International Economics, Elsevier, vol. 60(1), pages 85-107, May.
    7. Curran, Michael & Velic, Adnan, 2019. "Real exchange rate persistence and country characteristics: A global analysis," Journal of International Money and Finance, Elsevier, vol. 97(C), pages 35-56.
    8. Clarida, Richard H. & Sarno, Lucio & Taylor, Mark P. & Valente, Giorgio, 2003. "The out-of-sample success of term structure models as exchange rate predictors: a step beyond," Journal of International Economics, Elsevier, vol. 60(1), pages 61-83, May.
    9. Alan M. Taylor & Mark P. Taylor, 2004. "The Purchasing Power Parity Debate," Journal of Economic Perspectives, American Economic Association, vol. 18(4), pages 135-158, Fall.
    10. Byrne, Joseph P. & Korobilis, Dimitris & Ribeiro, Pinho J., 2016. "Exchange rate predictability in a changing world," Journal of International Money and Finance, Elsevier, vol. 62(C), pages 1-24.
    11. Cheung, Yin-Wong & Chinn, Menzie D. & Pascual, Antonio Garcia, 2005. "Empirical exchange rate models of the nineties: Are any fit to survive?," Journal of International Money and Finance, Elsevier, vol. 24(7), pages 1150-1175, November.
    12. Domenico Ferraro & Kenneth S. Rogoff & Barbara Rossi, 2011. "Can oil prices forecast exchange rates?," Working Papers 11-34, Federal Reserve Bank of Philadelphia.
    13. Dornbusch, Rudiger, 1976. "Expectations and Exchange Rate Dynamics," Journal of Political Economy, University of Chicago Press, vol. 84(6), pages 1161-1176, December.
    14. Michele Ca’ Zorzi & Jakub Muck & Michal Rubaszek, 2016. "Real Exchange Rate Forecasting and PPP: This Time the Random Walk Loses," Open Economies Review, Springer, vol. 27(3), pages 585-609, July.
    15. Oleg Itskhoki & Dmitry Mukhin, 2021. "Exchange Rate Disconnect in General Equilibrium," Journal of Political Economy, University of Chicago Press, vol. 129(8), pages 2183-2232.
    16. Norman, Stephen, 2010. "How well does nonlinear mean reversion solve the PPP puzzle?," Journal of International Money and Finance, Elsevier, vol. 29(5), pages 919-937, September.
    17. Molodtsova, Tanya & Papell, David H., 2009. "Out-of-sample exchange rate predictability with Taylor rule fundamentals," Journal of International Economics, Elsevier, vol. 77(2), pages 167-180, April.
    18. Ferraro, Domenico & Rogoff, Kenneth & Rossi, Barbara, 2015. "Can oil prices forecast exchange rates? An empirical analysis of the relationship between commodity prices and exchange rates," Journal of International Money and Finance, Elsevier, vol. 54(C), pages 116-141.
    19. López-Suárez, Carlos Felipe & Rodríguez-López, José Antonio, 2011. "Nonlinear exchange rate predictability," Journal of International Money and Finance, Elsevier, vol. 30(5), pages 877-895, September.
    20. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
    21. Mark P. Taylor, 2003. "Purchasing Power Parity," Review of International Economics, Wiley Blackwell, vol. 11(3), pages 436-452, August.
    22. 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.
    23. Meher Manzur, 2018. "Exchange rate economics is always and everywhere controversial," Applied Economics, Taylor & Francis Journals, vol. 50(3), pages 216-232, January.
    24. M S Eichenbaum & B K Johannsen & S T Rebelo, 2021. "Monetary Policy and the Predictability of Nominal Exchange Rates," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(1), pages 192-228.
    25. Alan M. Taylor & Mark P. Taylor, 2004. "The Purchasing Power Parity Debate," Journal of Economic Perspectives, American Economic Association, vol. 18(4), pages 135-158, Fall.
    26. 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.
    27. Taylor, Mark P. & Peel, David A., 2000. "Nonlinear adjustment, long-run equilibrium and exchange rate fundamentals," Journal of International Money and Finance, Elsevier, vol. 19(1), pages 33-53, February.
    28. James H. Stock & Mark W. Watson, 1998. "A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series," NBER Working Papers 6607, National Bureau of Economic Research, Inc.
    29. Beckmann, Joscha & Schüssler, Rainer, 2016. "Forecasting exchange rates under parameter and model uncertainty," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 267-288.
    30. G. Elliott & C. Granger & A. Timmermann (ed.), 2013. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 2, number 2.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nasir, Muhammad Ali, 2020. "Forecasting inflation under uncertainty: The forgotten dog and the frisbee," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    2. 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.
    3. 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.
    4. 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).
    5. Engel, Charles & Wu, Steve Pak Yeung, 2023. "Forecasting the U.S. Dollar in the 21st Century," Journal of International Economics, Elsevier, vol. 141(C).
    6. 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).
    7. David Alaminos & M. Belén Salas & Manuel Á. Fernández-Gámez, 2023. "Quantum Monte Carlo simulations for estimating FOREX markets: a speculative attacks experience," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-21, December.
    8. Rubaszek, Michał & Beckmann, Joscha & Ca' Zorzi, Michele & Kwas, Marek, 2022. "Boosting carry with equilibrium exchange rate estimates," Working Paper Series 2731, European Central Bank.
    9. 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.
    10. 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.
    11. 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.
    12. 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).
    13. 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.
    14. Marek Kwas & Michał Rubaszek, 2021. "Forecasting Commodity Prices: Looking for a Benchmark," Forecasting, MDPI, vol. 3(2), pages 1-13, June.
    15. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. 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.
    3. Stijn Claessens & M Ayhan Kose, 2017. "Asset prices and macroeconomic outcomes: a survey," BIS Working Papers 676, Bank for International Settlements.
    4. Ca' Zorzi, Michele & Longaric, Pablo Anaya & Rubaszek, Michał, 2021. "The predictive power of equilibrium exchange rate models," Economic Bulletin Articles, European Central Bank, vol. 7.
    5. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    6. Ca’ Zorzi, Michele & Kolasa, Marcin & Rubaszek, Michał, 2017. "Exchange rate forecasting with DSGE models," Journal of International Economics, Elsevier, vol. 107(C), pages 127-146.
    7. Hai Long Vo & Duc Hong Vo, 2023. "The purchasing power parity and exchange‐rate economics half a century on," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 446-479, April.
    8. Xie, Zixiong & Chen, Shyh-Wei, 2019. "Exchange rates and fundamentals: A bootstrap panel data analysis," Economic Modelling, Elsevier, vol. 78(C), pages 209-224.
    9. 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.
    10. 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).
    11. Yuan, Chunming, 2011. "The exchange rate and macroeconomic determinants: Time-varying transitional dynamics," The North American Journal of Economics and Finance, Elsevier, vol. 22(2), pages 197-220, August.
    12. Michele Ca’ Zorzi & Jakub Muck & Michal Rubaszek, 2016. "Real Exchange Rate Forecasting and PPP: This Time the Random Walk Loses," Open Economies Review, Springer, vol. 27(3), pages 585-609, July.
    13. Wu, Jyh-Lin & Hu, Yu-Hau, 2009. "New evidence on nominal exchange rate predictability," Journal of International Money and Finance, Elsevier, vol. 28(6), pages 1045-1063, October.
    14. 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).
    15. Lasha Kavtaradze & Manouchehr Mokhtari, 2018. "Factor Models And Time†Varying Parameter Framework For Forecasting Exchange Rates And Inflation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 302-334, April.
    16. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    17. Beckmann, Joscha & Czudaj, Robert L. & Arora, Vipin, 2020. "The relationship between oil prices and exchange rates: Revisiting theory and evidence," Energy Economics, Elsevier, vol. 88(C).
    18. Ahmed, Shamim & Liu, Xiaoquan & Valente, Giorgio, 2016. "Can currency-based risk factors help forecast exchange rates?," International Journal of Forecasting, Elsevier, vol. 32(1), pages 75-97.
    19. Christopher J. Neely & Lucio Sarno, 2002. "How well do monetary fundamentals forecast exchange rates?," Review, Federal Reserve Bank of St. Louis, vol. 84(Sep), pages 51-74.
    20. Demetrescu, Matei & Rodrigues, Paulo M.M. & Taylor, A.M. Robert, 2023. "Transformed regression-based long-horizon predictability tests," Journal of Econometrics, Elsevier, vol. 237(2).

    More about this item

    Keywords

    Forecasting; Exchange rates; Mean reversion; Purchasing power parity; Panel data;
    All these keywords.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jimfin:v:104:y:2020:i:c:s026156061830192x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30443 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.