IDEAS home Printed from https://ideas.repec.org/a/dug/actaec/y2014i5p28-38.html
   My bibliography  Save this article

The Prediction of Exchange Rates with the Use of Auto-Regressive Integrated Moving-Average Models

Author

Listed:
  • Daniela Spiesová

    (Czech Technical University in Prague)

Abstract

Currency market is recently the largest world market during the existence of which there have been many theories regarding the prediction of the development of exchange rates based on macroeconomic, microeconomic, statistic and other models. The aim of this paper is to identify the adequate model for the prediction of non-stationary time series of exchange rates and then use this model to predict the trend of the development of European currencies against Euro. The uniqueness of this paper is in the fact that there are many expert studies dealing with the prediction of the currency pairs rates of the American dollar with other currency but there is only a limited number of scientific studies concerned with the long-term prediction of European currencies with the help of the integrated ARMA models even though the development of exchange rates has a crucial impact on all levels of economy and its prediction is an important indicator for individual countries, banks, companies and businessmen as well as for investors. The results of this study confirm that to predict the conditional variance and then to estimate the future values of exchange rates, it is adequate to use the ARIMA (1,1,1) model without constant, or ARIMA [(1,7),1,(1,7)] model, where in the long-term, the square root of the conditional variance inclines towards stable value.

Suggested Citation

  • Daniela Spiesová, 2014. "The Prediction of Exchange Rates with the Use of Auto-Regressive Integrated Moving-Average Models," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 10(5), pages 28-38, October.
  • Handle: RePEc:dug:actaec:y:2014:i:5:p:28-38
    as

    Download full text from publisher

    File URL: http://journals.univ-danubius.ro/index.php/oeconomica/article/view/2556/2245
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dunis, Christian L & Huang, Xuehuan, 2002. "Forecasting and Trading Currency Volatility: An Application of Recurrent Neural Regression and Model Combination," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(5), pages 317-354, August.
    2. 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.
    Full references (including those not matched with items on IDEAS)

    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. Coudert, Virginie & Mignon, Valérie, 2013. "The “forward premium puzzle” and the sovereign default risk," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 491-511.
    2. Rime, Dagfinn & Sarno, Lucio & Sojli, Elvira, 2010. "Exchange rate forecasting, order flow and macroeconomic information," Journal of International Economics, Elsevier, vol. 80(1), pages 72-88, January.
    3. Lothian, James R., 1997. "Multi-country evidence on the behavior of purchasing power parity under the current float," Journal of International Money and Finance, Elsevier, vol. 16(1), pages 19-35, February.
    4. Carlo Altavilla & Paul De Grauwe, 2010. "Forecasting and combining competing models of exchange rate determination," Applied Economics, Taylor & Francis Journals, vol. 42(27), pages 3455-3480.
    5. Goncalves, Silvia & Kilian, Lutz, 2004. "Bootstrapping autoregressions with conditional heteroskedasticity of unknown form," Journal of Econometrics, Elsevier, vol. 123(1), pages 89-120, November.
    6. 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.
    7. Athanasia Gavala & Nikolay Gospodinov & Deming Jiang, 2006. "Forecasting volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(6), pages 381-400.
    8. Neely, Christopher J. & Weller, Paul, 2000. "Predictability in International Asset Returns: A Reexamination," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(4), pages 601-620, December.
    9. Moerman, G.A., 2001. "Unpredictable After All? A short note on exchange rate predictability," ERIM Report Series Research in Management ERS-2001-29-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    10. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    11. Engel, Charles, 1994. "Can the Markov switching model forecast exchange rates?," Journal of International Economics, Elsevier, vol. 36(1-2), pages 151-165, February.
    12. Sager, Michael & Taylor, Mark P., 2014. "Generating currency trading rules from the term structure of forward foreign exchange premia," Journal of International Money and Finance, Elsevier, vol. 44(C), pages 230-250.
    13. Philippe Andrade & Catherine Bruneau, 2002. "Excess returns, portfolio choices and exchange rate dynamics. The yen/dollar case, 1980–1998," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(3), pages 233-256, July.
    14. Evans, Martin D.D., 2014. "External balances, trade flows and financial conditions," Journal of International Money and Finance, Elsevier, vol. 48(PB), pages 271-290.
    15. Richard H. Clarida & Lucio Sarno & Mark P. Taylor & Giorgio Valente, 2006. "The Role of Asymmetries and Regime Shifts in the Term Structure of Interest Rates," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1193-1224, May.
    16. Florian Huber, 2014. "Forecasting Exchange Rates using Bayesian Threshold Vector Autoregressions," Economics Bulletin, AccessEcon, vol. 34(3), pages 1687-1695.
    17. Chang, Ming-Jen & Su, Che-Yi, 2014. "The dynamic relationship between exchange rates and macroeconomic fundamentals: Evidence from Pacific Rim countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 30(C), pages 220-246.
    18. Levent KORAP, 2008. "Exchange Rate Determination Of Tl/Us$:A Co-Integration Approach," Istanbul University Econometrics and Statistics e-Journal, Department of Econometrics, Faculty of Economics, Istanbul University, vol. 7(1), pages 24-50, May.
    19. Bacchetta, Philippe & van Wincoop, Eric, 1998. "Does Exchange Rate Stability Increase Trade and Capital Flows?," CEPR Discussion Papers 1962, C.E.P.R. Discussion Papers.
    20. Stuart Landon & Constance E. Smith, 2003. "The Risk Premium, Exchange Rate Expectations, and the Forward Exchange Rate: Estimates for the Yen–Dollar Rate," Review of International Economics, Wiley Blackwell, vol. 11(1), pages 144-158, February.

    More about this item

    Keywords

    ADF; stationarity; ARIMA; EUR; prediction;
    All these keywords.

    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:dug:actaec:y:2014:i:5:p:28-38. 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: Daniela Robu (email available below). General contact details of provider: https://edirc.repec.org/data/fedanro.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.