IDEAS home Printed from https://ideas.repec.org/p/sgh/kaewps/2020053.html
   My bibliography  Save this paper

One model or many? Exchange rates determinants and their predictive capabilities

Author

Listed:
  • Piotr Dybka

Abstract

In this paper the Dynamic Bayesian Model Averaging (DMA) algorithm is used to establish the key determinants of the nominal exchange rates of 5 currencies: CAD, EUR, GBP, CHF and JPY against the US dollar. My results indicate that the importance of the variables in the exchange rate forecasting can substantially differ in time. Even among the set of developed countries, there are visible differences in the set of key determinants of the exchange rate. However, the lagged value of the exchange rate remains always an important variable indicating significant persistence in the exchange rate time series. Furthermore, the PPP rate, Terms of Trade (TOT) and output per worker are also variables that have high Posterior Inclusion Probabilities among the analyzed countries. My results show that macroeconomic fundamentals are not leading indicators of the exchange rates. As a result, to outperform the random walk (naive) forecast of the exchange rate using the macroeconomic fundamentals, a good quality of the forecast of the explanatory variables is required.

Suggested Citation

  • 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.
  • Handle: RePEc:sgh:kaewps:2020053
    as

    Download full text from publisher

    File URL: http://kolegia.sgh.waw.pl/pl/KAE/Documents/WorkingPapersKAE/WPKAE_2020_053.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Charles Engel & Steve Pak Yeung Wu, 2023. "Liquidity and Exchange Rates: An Empirical Investigation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(5), pages 2395-2438.
    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. 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.
    4. Couharde, Cécile & Delatte, Anne-Laure & Grekou, Carl & Mignon, Valérie & Morvillier, Florian, 2018. "EQCHANGE: A world database on actual and equilibrium effective exchange rates," International Economics, Elsevier, vol. 156(C), pages 206-230.
    5. Michał Chojnowski & Piotr Dybka, 2017. "Is Exchange Rate Moody? Forecasting Exchange Rate with Google Trends Data," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 2(1), pages 1-21, June.
    6. Gary Koop & Dimitris Korobilis, 2012. "Forecasting Inflation Using Dynamic Model Averaging," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(3), pages 867-886, August.
    7. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    8. Dąbrowski, Marek A. & Papież, Monika & Śmiech, Sławomir, 2014. "Exchange rates and monetary fundamentals in CEE countries: Evidence from a panel approach," Journal of Macroeconomics, Elsevier, vol. 41(C), pages 148-159.
    9. Lúcio Otávio Seixas Barbosa & Frederico G. Jayme & Fabricio José Missio, 2018. "Determinants of the real exchange rate in the long-run for developing and emerging countries: a theoretical and empirical approach," International Review of Applied Economics, Taylor & Francis Journals, vol. 32(1), pages 62-83, January.
    10. Ca’ Zorzi, Michele & Chudik, Alexander & Dieppe, Alistair, 2012. "Thousands of models, one story: Current account imbalances in the global economy," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1319-1338.
    11. 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.
    12. Bork, Lasse & Møller, Stig V., 2015. "Forecasting house prices in the 50 states using Dynamic Model Averaging and Dynamic Model Selection," International Journal of Forecasting, Elsevier, vol. 31(1), pages 63-78.
    13. Frankel, Jeffrey A, 1979. "On the Mark: A Theory of Floating Exchange Rates Based on Real Interest Differentials," American Economic Review, American Economic Association, vol. 69(4), pages 610-622, September.
    14. Montero-Manso, Pablo & Athanasopoulos, George & Hyndman, Rob J. & Talagala, Thiyanga S., 2020. "FFORMA: Feature-based forecast model averaging," International Journal of Forecasting, Elsevier, vol. 36(1), pages 86-92.
    15. Beata K. Bierut & Piot Dybka, 2019. "Institutional determinants of export competitiveness among the EU countries: evidence from Bayesian model averaging," KAE Working Papers 2019-043, Warsaw School of Economics, Collegium of Economic Analysis.
    16. Buncic, Daniel & Moretto, Carlo, 2015. "Forecasting copper prices with dynamic averaging and selection models," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 1-38.
    17. 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.
    18. Piotr Dybka & Michal Rubaszek, 2017. "What Determines the Current Account: Intratemporal versus Intertemporal Factors," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 67(1), pages 2-14, March.
    19. Buncic, Daniel & Piras, Gion Donat, 2016. "Heterogeneous agents, the financial crisis and exchange rate predictability," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 313-359.
    20. Theo S. Eicher & Chris Papageorgiou & Adrian E. Raftery, 2011. "Default priors and predictive performance in Bayesian model averaging, with application to growth determinants," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(1), pages 30-55, January/F.
    21. 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.
    22. Annina Kaltenbrunner, 2015. "A post Keynesian framework of exchange rate determination: a Minskyan approach," Journal of Post Keynesian Economics, Taylor & Francis Journals, vol. 38(3), pages 426-448, October.
    23. Zorzi, Michele Ca’ & Rubaszek, Michał, 2020. "Exchange rate forecasting on a napkin," Journal of International Money and Finance, Elsevier, vol. 104(C).
    24. Mr. Ronald MacDonald & Mr. Peter B. Clark, 1998. "Exchange Rates and Economic Fundamentals: A Methodological Comparison of BEERs and FEERs," IMF Working Papers 1998/067, International Monetary Fund.
    25. Moral-Benito, Enrique & Roehn, Oliver, 2016. "The impact of financial regulation on current account balances," European Economic Review, Elsevier, vol. 81(C), pages 148-166.
    26. 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.
    27. Menzie D. Chinn & Guy Meredith, 2004. "Monetary Policy and Long-Horizon Uncovered Interest Parity," IMF Staff Papers, Palgrave Macmillan, vol. 51(3), pages 409-430, November.
    28. Bela Balassa, 1964. "The Purchasing-Power Parity Doctrine: A Reappraisal," Journal of Political Economy, University of Chicago Press, vol. 72(6), pages 584-584.
    29. Dornbusch, Rudiger, 1976. "Expectations and Exchange Rate Dynamics," Journal of Political Economy, University of Chicago Press, vol. 84(6), pages 1161-1176, December.
    30. 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.
    31. Shahram M. Amini & Christopher F. Parmeter, 2012. "Comparison Of Model Averaging Techniques: Assessing Growth Determinants," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(5), pages 870-876, August.
    32. Xavier Sala-I-Martin & Gernot Doppelhofer & Ronald I. Miller, 2004. "Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach," American Economic Review, American Economic Association, vol. 94(4), pages 813-835, September.
    33. Grabowski, Wojciech & Welfe, Aleksander, 2020. "The Tobit cointegrated vector autoregressive model: An application to the currency market," Economic Modelling, Elsevier, vol. 89(C), pages 88-100.
    34. Wang, Yudong & Ma, Feng & Wei, Yu & Wu, Chongfeng, 2016. "Forecasting realized volatility in a changing world: A dynamic model averaging approach," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 136-149.
    35. 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.
    36. Taylor, John B., 1993. "Discretion versus policy rules in practice," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 39(1), pages 195-214, December.
    37. Marek A. Dąbrowski & Monika Papież & Sławomir Śmiech, 2018. "Uncovering the link between a flexible exchange rate and fundamentals: the case of Central and Eastern European economies," Applied Economics, Taylor & Francis Journals, vol. 50(20), pages 2273-2296, April.
    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. Piotr Dybka & Bartosz Olesiński & Marek Rozkrut & Andrzej Torój, 2023. "Measuring the model uncertainty of shadow economy estimates," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 30(4), pages 1069-1106, August.

    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. 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.
    2. Piotr Dybka & Bartosz Olesiński & Marek Rozkrut & Andrzej Torój, 2023. "Measuring the model uncertainty of shadow economy estimates," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 30(4), pages 1069-1106, August.
    3. Piotr Dybka & Bartosz Olesiński & Marek Rozkrut & Andrzej Torój, 2020. "Measuring the uncertainty of shadow economy estimates using Bayesian and frequentist model averaging," KAE Working Papers 2020-046, Warsaw School of Economics, Collegium of Economic Analysis.
    4. Joseph Agyapong, 2021. "Application of Taylor Rule Fundamentals in Forecasting Exchange Rates," Economies, MDPI, vol. 9(2), pages 1-27, June.
    5. Andrew Lilley & Matteo Maggiori & Brent Neiman & Jesse Schreger, 2019. "Exchange Rate Reconnect," NBER Working Papers 26046, National Bureau of Economic Research, Inc.
    6. 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).
    7. 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.
    8. 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.
    9. Rubaszek, Michał & Beckmann, Joscha & Ca' Zorzi, Michele & Kwas, Marek, 2022. "Boosting carry with equilibrium exchange rate estimates," Working Paper Series 2731, European Central Bank.
    10. Jan Prüser, 2019. "Adaptive learning from model space," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(1), pages 29-38, January.
    11. 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.
    12. Stijn Claessens & M Ayhan Kose, 2017. "Asset prices and macroeconomic outcomes: a survey," BIS Working Papers 676, Bank for International Settlements.
    13. Colombo, Emilio & Pelagatti, Matteo, 2020. "Statistical learning and exchange rate forecasting," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1260-1289.
    14. Cheung, Yin-Wong & Wang, Wenhao, 2022. "Uncovered interest rate parity redux: Non-uniform effects," Journal of Empirical Finance, Elsevier, vol. 67(C), pages 133-151.
    15. 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.
    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. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    18. Ron Alquist & Menzie D. Chinn, 2008. "Conventional and unconventional approaches to exchange rate modelling and assessment," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 13(1), pages 2-13.
    19. 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.
    20. 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).

    More about this item

    Keywords

    Exchange rates; forecasting; Bayesian Model Averaging;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • F14 - International Economics - - Trade - - - Empirical Studies of Trade
    • F15 - International Economics - - Trade - - - Economic Integration

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:sgh:kaewps:2020053. 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: Dariusz Nojszewski (email available below). General contact details of provider: https://edirc.repec.org/data/kawawpl.html .

    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.