IDEAS home Printed from https://ideas.repec.org/p/ris/duthrp/2013_005.html
   My bibliography  Save this paper

Forecasting the NOK/USD Exchange Rate with Machine Learning Techniques

Author

Listed:
  • Papadimitriou, Theophilos

    () (Democritus University of Thrace, Department of Economics)

  • Gogas, Periklis

    () (Democritus University of Thrace, Department of Economics)

  • Plakandaras, Vasilios

    () (Democritus University of Thrace, Department of Economics)

Abstract

In this paper, we approximate the empirical findings of Papadamou and Markopoulos (2012) on the NOK/USD exchange rate under a Machine Learning (ML) framework. By applying Support Vector Regression (SVR) on a general monetary exchange rate model and a Dynamic Evolving Neuro-Fuzzy Inference System (DENFIS) to extract model structure, we test for the validity of popular monetary exchange rate models. We reach to mixed results since the coefficient sign of interest rate differential is in favor only with the model proposed by Bilson (1978), while the inflation rate differential coefficient sign is approximated by the model of Frankel (1979). By adopting various inflation expectation estimates, our SVR model fits actual data with a small Mean Absolute Percentage Error when an autoregressive approach excluding energy prices is adopted for inflation expectation. Overall, our empirical findings conclude that for a small open petroleum producing country such as Norway, fundamentals possess significant forecasting ability when used in exchange rate forecasting.

Suggested Citation

  • Papadimitriou, Theophilos & Gogas, Periklis & Plakandaras, Vasilios, 2013. "Forecasting the NOK/USD Exchange Rate with Machine Learning Techniques," DUTH Research Papers in Economics 5-2013, Democritus University of Thrace, Department of Economics.
  • Handle: RePEc:ris:duthrp:2013_005
    as

    Download full text from publisher

    File URL: http://utopia.duth.gr/~vplakand/Forecasting%20the%20NOK_USD%20Exchange%20Rate%20with%20Machine%20Learning%20Techniques.docx
    File Function: Full text
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Della Corte, Pasquale & Sarno, Lucio & Tsiakas, Ilias, 2011. "Spot and forward volatility in foreign exchange," Journal of Financial Economics, Elsevier, vol. 100(3), pages 496-513, June.
    2. Frenkel, Jacob A, 1976. " A Monetary Approach to the Exchange Rate: Doctrinal Aspects and Empirical Evidence," Scandinavian Journal of Economics, Wiley Blackwell, vol. 78(2), pages 200-224.
    3. Stephanos Papadamou & Thomas Markopoulos, 2012. "The Monetary Approach to the Exchange Rate Determination for a “Petrocurrency”: The Case of Norwegian Krone," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 18(3), pages 299-314, August.
    4. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    5. 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.
    6. 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.
    7. Tatsuyoshi Miyakoshi, 2000. "The monetary approach to the exchange rate: empirical observations from Korea," Applied Economics Letters, Taylor & Francis Journals, vol. 7(12), pages 791-794.
    8. Q. Farooq Akram, 2004. "Oil prices and exchange rates: Norwegian evidence," Econometrics Journal, Royal Economic Society, vol. 7(2), pages 476-504, December.
    9. Abhyankar, Abhay & Sarno, Lucio & Valente, Giorgio, 2005. "Exchange rates and fundamentals: evidence on the economic value of predictability," Journal of International Economics, Elsevier, vol. 66(2), pages 325-348, July.
    10. 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.
    11. Backus, David K & Gregory, Allan W & Telmer, Chris I, 1993. " Accounting for Forward Rates in Markets for Foreign Currency," Journal of Finance, American Finance Association, vol. 48(5), pages 1887-1908, December.
    12. Cushman, David O., 2007. "A portfolio balance approach to the Canadian-U.S. exchange rate," Review of Financial Economics, Elsevier, vol. 16(3), pages 305-320.
    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. Lee Chin & M. Azali & Zulkornain Yusop & Mohammed Yusoff, 2007. "The monetary model of exchange rate: evidence from The Philippines," Applied Economics Letters, Taylor & Francis Journals, vol. 14(13), pages 993-997.
    15. repec:kap:iaecre:v:18:y:2012:i:3:p:299-314 is not listed on IDEAS
    16. Lee Chin & M. Azali & K. G. Matthews, 2007. "The monetary approach to exchange rate determination for Malaysia," Applied Financial Economics Letters, Taylor and Francis Journals, vol. 3(2), pages 91-94.
    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. Plakandaras, Vasilios & Gupta, Rangan & Wohar, Mark E., 2017. "The depreciation of the pound post-Brexit: Could it have been predicted?," Finance Research Letters, Elsevier, vol. 21(C), pages 206-213.
    2. Christina Christou & Rangan Gupta & Christis Hassapis & Tahir Suleman, 2017. "The Role of Economic Uncertainty in Forecasting Exchange Rate Returns and Realized Volatility: Evidence from Quantile Predictive Regressions," Working Papers 201774, University of Pretoria, Department of Economics.

    More about this item

    Keywords

    International Financial Markets; Foreign Exchange; Support Vector Regression; Monetary exchange rate models;

    JEL classification:

    • F30 - International Economics - - International Finance - - - General
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:ris:duthrp:2013_005. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Periklis Gogas). General contact details of provider: http://edirc.repec.org/data/didutgr.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.