IDEAS home Printed from https://ideas.repec.org/a/wly/jforec/v40y2021i6p977-999.html
   My bibliography  Save this article

Forecasting exchange rates for Central and Eastern European currencies using country‐specific factors

Author

Listed:
  • Krystian Jaworski

Abstract

This study builds on two strands of the literature regarding exchange rates—developing methods to forecast them and attempting to find a link between exchange rates and macroeconomic fundamentals (i.e., addressing so called “exchange rate disconnect puzzle”). We propose looking separately at its global component (common for all the currencies) and the local component (country‐specific one) instead of modeling and forecasting the exchange rate directly. We demonstrate that in the last few years, local factors have been gaining importance in shaping the exchange rate returns for the Polish Zloty, Hungarian Forint, Czech Koruna, and Romanian Leu. We further show that the main drivers of the local component of exchange rate returns are the future values of the gross domestic product growth rate and consumer price index inflation. Using principal component analysis combined with linear regression, we exploit this tendency for forecasting purposes. Our novel approach yields superior results compared to the random walk in out‐of‐sample forecasting exercise at horizons of 1 month to over a year in the case of Central and Eastern European currencies. The results withstand the sensitivity and robustness analysis.

Suggested Citation

  • 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.
  • Handle: RePEc:wly:jforec:v:40:y:2021:i:6:p:977-999
    DOI: 10.1002/for.2749
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/for.2749
    Download Restriction: no

    File URL: https://libkey.io/10.1002/for.2749?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
    ---><---

    References listed on IDEAS

    as
    1. Angela Abbate & Massimiliano Marcellino, 2018. "Point, interval and density forecasts of exchange rates with time varying parameter models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(1), pages 155-179, January.
    2. 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.
    3. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    4. 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.
    5. Gabriele Galati & Corrinne Ho, 2003. "Macroeconomic News and the Euro/Dollar Exchange Rate," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 32(3), pages 371-398, November.
    6. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    7. Molodtsova, Tanya & Nikolsko-Rzhevskyy, Alex & Papell, David H., 2008. "Taylor rules with real-time data: A tale of two countries and one exchange rate," Journal of Monetary Economics, Elsevier, vol. 55(Supplemen), pages 63-79, October.
    8. Charles Engel & Nelson C. Mark & Kenneth D. West, 2015. "Factor Model Forecasts of Exchange Rates," Econometric Reviews, Taylor & Francis Journals, vol. 34(1-2), pages 32-55, February.
    9. Hanno Lustig & Nikolai Roussanov & Adrien Verdelhan, 2011. "Common Risk Factors in Currency Markets," The Review of Financial Studies, Society for Financial Studies, vol. 24(11), pages 3731-3777.
    10. Koop, Gary & Korobilis, Dimitris, 2013. "Large time-varying parameter VARs," Journal of Econometrics, Elsevier, vol. 177(2), pages 185-198.
    11. Peter R. Hansen & Asger Lunde & James M. Nason, 2011. "The Model Confidence Set," Econometrica, Econometric Society, vol. 79(2), pages 453-497, March.
    12. Jakub Muck & Pawel Skrzypczynski, 2012. "Can we beat the random walk in forecasting CEE exchange rates?," NBP Working Papers 127, Narodowy Bank Polski.
    13. Haakon Kavli & Kevin Kotzé, 2014. "Spillovers in Exchange Rates and the Effects of Global Shocks on Emerging Market Currencies," South African Journal of Economics, Economic Society of South Africa, vol. 82(2), pages 209-238, June.
    14. Alexander Jakob Dautel & Wolfgang Karl Härdle & Stefan Lessmann & Hsin-Vonn Seow, 2020. "Forex exchange rate forecasting using deep recurrent neural networks," Digital Finance, Springer, vol. 2(1), pages 69-96, September.
    15. Ardic, Oya Pinar & Ergin, Onur & Senol, G. Bahar, 2008. "Exchange Rate Forecasting: Evidence from the Emerging Central and Eastern European Economies," MPRA Paper 7505, University Library of Munich, Germany.
    16. 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.
    17. Zorzi, Michele Ca’ & Rubaszek, Michał, 2020. "Exchange rate forecasting on a napkin," Journal of International Money and Finance, Elsevier, vol. 104(C).
    18. Jesús Crespo Cuaresma & Jaroslava Hlouskova, 2005. "Beating the random walk in Central and Eastern Europe," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(3), pages 189-201.
    19. Maurice Obstfeld & Kenneth Rogoff, 2001. "The Six Major Puzzles in International Macroeconomics: Is There a Common Cause?," NBER Chapters, in: NBER Macroeconomics Annual 2000, Volume 15, pages 339-412, National Bureau of Economic Research, Inc.
    20. Chadwick, Meltem Gülenay & Fazilet, Fatih & Tekatli, Necati, 2015. "Understanding the common dynamics of the emerging market currencies," Economic Modelling, Elsevier, vol. 49(C), pages 120-136.
    21. Berg, Kimberly A. & Mark, Nelson C., 2015. "Third-country effects on the exchange rate," Journal of International Economics, Elsevier, vol. 96(2), pages 227-243.
    22. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Vega, Clara, 2007. "Real-time price discovery in global stock, bond and foreign exchange markets," Journal of International Economics, Elsevier, vol. 73(2), pages 251-277, November.
    23. Ryan Greenaway‐McGrevy & Nelson C. Mark & Donggyu Sul & Jyh‐Lin Wu, 2018. "Identifying Exchange Rate Common Factors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(4), pages 2193-2218, November.
    24. Mohsen Bahmani‐Oskooee & Amr Hosny & N. Kundan Kishor, 2015. "The Exchange Rate Disconnect Puzzle Revisited," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 20(2), pages 126-137, March.
    25. 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.
    26. Lucio Sarno & Maik Schmeling, 2014. "Which Fundamentals Drive Exchange Rates? A Cross‐Sectional Perspective," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(2-3), pages 267-292, March.
    27. Chen, Wei & Xu, Huilin & Jia, Lifen & Gao, Ying, 2021. "Machine learning model for Bitcoin exchange rate prediction using economic and technology determinants," International Journal of Forecasting, Elsevier, vol. 37(1), pages 28-43.
    28. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    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. 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.

    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. Ryan Greenaway‐McGrevy & Nelson C. Mark & Donggyu Sul & Jyh‐Lin Wu, 2018. "Identifying Exchange Rate Common Factors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(4), pages 2193-2218, November.
    2. Joscha Beckmann & Gary Koop & Dimitris Korobilis & Rainer Alexander Schüssler, 2020. "Exchange rate predictability and dynamic Bayesian learning," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 410-421, June.
    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. Stijn Claessens & M Ayhan Kose, 2017. "Asset prices and macroeconomic outcomes: a survey," BIS Working Papers 676, Bank for International Settlements.
    5. Raheem, Ibrahim, 2020. "Global financial cycles and exchange rate forecast: A factor analysis," MPRA Paper 105358, University Library of Munich, Germany.
    6. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    7. Joseph P. Byrne & Dimitris Korobilis & Pinho J. Ribeiro, 2018. "On The Sources Of Uncertainty In Exchange Rate Predictability," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(1), pages 329-357, February.
    8. 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.
    9. Ince, Onur & Molodtsova, Tanya & Papell, David H., 2016. "Taylor rule deviations and out-of-sample exchange rate predictability," Journal of International Money and Finance, Elsevier, vol. 69(C), pages 22-44.
    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. Dahlquist, Magnus & Hasseltoft, Henrik, 2020. "Economic momentum and currency returns," Journal of Financial Economics, Elsevier, vol. 136(1), pages 152-167.
    12. Salisu, Afees A. & Gupta, Rangan & Kim, Won Joong, 2022. "Exchange rate predictability with nine alternative models for BRICS countries," Journal of Macroeconomics, Elsevier, vol. 71(C).
    13. Ryan Greenaway-McGrevy & Nelson C. Mark & Donggyu Sul & Jyh-Lin Wu, 2012. "Exchange Rates as Exchange Rate Common Factors," Working Papers 212012, Hong Kong Institute for Monetary Research.
    14. David Alan Peel & Pantelis Promponas, 2016. "Forecasting the nominal exchange rate movements in a changing world. The case of the U.S. and the U.K," Working Papers 144439514, Lancaster University Management School, Economics Department.
    15. 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.
    16. Kharrat, Sabrine & Hammami, Yacine & Fatnassi, Ibrahim, 2020. "On the cross-sectional relation between exchange rates and future fundamentals," Economic Modelling, Elsevier, vol. 89(C), pages 484-501.
    17. 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.
    18. Takashi Matsuki & Ming-Jen Chang, 2016. "Out-of-Sample Exchange Rate Forecasting and Macroeconomic Fundamentals: The Case of Japan," Australian Economic Papers, Wiley Blackwell, vol. 55(4), pages 409-433, December.
    19. Byrne, Joseph P. & Korobilis, Dimitris & Ribeiro, Pinho J., 2014. "On the Sources of Uncertainty in Exchange Rate Predictability," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon TN 2015-24, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    20. Niko Hauzenberger & Florian Huber, 2020. "Model instability in predictive exchange rate regressions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 168-186, March.

    More about this item

    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:wly:jforec:v:40:y:2021:i:6:p:977-999. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www3.interscience.wiley.com/cgi-bin/jhome/2966 .

    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.