IDEAS home Printed from https://ideas.repec.org/a/eme/sefpps/v26y2009i3p171-181.html
   My bibliography  Save this article

Evaluating random walk forecasts of exchange rates

Author

Listed:
  • Hamid Baghestani

Abstract

Purpose - The random walk forecast of exchange rate serves as a standard benchmark for forecast comparison. The purpose of this paper is to assess whether this benchmark is unbiased and directionally accurate under symmetric loss. The focus is on the random walk forecasts of the dollar/euro for 1999‐2007 and the dollar/pound for 1971‐2007. Design/methodology/approach - A forecasting framework to generate the one‐ to four‐quarter‐ahead random walk forecasts at varying lead times is designed. This allows to compare forecast accuracy at different lead times and forecast horizons. Using standard evaluation methods, this paper further evaluates these forecasts in terms of unbiasedness and directional accuracy. Findings - The paper shows that forecast accuracy improves with a reduction in the lead time but deteriorates with an increase in the forecast horizon. More importantly, the random walk forecasts are unbiased and accurately predict directional change under symmetric loss and thus are of value to a user who assigns similar cost to incorrect upward and downward move predictions in the exchange rates. Research limitations/implications - The one‐ to four‐quarter‐ahead random walk forecasts evaluated here are for averages of daily figures and not for the (end‐of‐quarter) rates in 3‐, 6‐, 9‐ and 12‐months. Thus, the framework is of value to a market participant who is interested in forecasting quarterly average rates rather than the end‐of‐quarter rates. Originality/value - The exchange rate forecasting framework presented in this paper allows the evaluation of the random walk forecasts in terms of directional accuracy which (to the best of knowledge) has not been done before.

Suggested Citation

  • Hamid Baghestani, 2009. "Evaluating random walk forecasts of exchange rates," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 26(3), pages 171-181, July.
  • Handle: RePEc:eme:sefpps:v:26:y:2009:i:3:p:171-181
    DOI: 10.1108/10867370910974008
    as

    Download full text from publisher

    File URL: https://www.emerald.com/insight/content/doi/10.1108/10867370910974008/full/html?utm_source=repec&utm_medium=feed&utm_campaign=repec
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://www.emerald.com/insight/content/doi/10.1108/10867370910974008/full/pdf?utm_source=repec&utm_medium=feed&utm_campaign=repec
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1108/10867370910974008?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Jeremy Berkowitz & Lorenzo Giorgianni, 2001. "Long-Horizon Exchange Rate Predictability?," The Review of Economics and Statistics, MIT Press, vol. 83(1), pages 81-91, February.
    2. Frankel, Jeffrey A & Froot, Kenneth A, 1987. "Using Survey Data to Test Standard Propositions Regarding Exchange Rate Expectations," American Economic Review, American Economic Association, vol. 77(1), pages 133-153, March.
    3. 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.
    4. Michael P. Clements & David F.Hendry, 2001. "Forecasting with difference-stationary and trend-stationary models," Econometrics Journal, Royal Economic Society, vol. 4(1), pages 1-19.
    5. Ito, Takatoshi, 1990. "Foreign Exchange Rate Expectations: Micro Survey Data," American Economic Review, American Economic Association, vol. 80(3), pages 434-449, June.
    6. Richard A. Meese & Andrew K. Rose, 1991. "An Empirical Assessment of Non-Linearities in Models of Exchange Rate Determination," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(3), pages 603-619.
    7. Cheung, Yin-Wong & Erlandsson, Ulf G., 2005. "Exchange Rates and Markov Switching Dynamics," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 314-320, July.
    8. Fair, Ray C & Shiller, Robert J, 1990. "Comparing Information in Forecasts from Econometric Models," American Economic Review, American Economic Association, vol. 80(3), pages 375-389, June.
    9. Engel, Charles, 1994. "Can the Markov switching model forecast exchange rates?," Journal of International Economics, Elsevier, vol. 36(1-2), pages 151-165, February.
    10. 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.
    11. Kilian, Lutz, 1999. "Exchange Rates and Monetary Fundamentals: What Do We Learn from Long-Horizon Regressions?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 491-510, Sept.-Oct.
    12. 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.
    13. Giuseppe Parigi & Roberto Golinelli, 2007. "The use of monthly indicators to forecast quarterly GDP in the short run: an application to the G7 countries," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(2), pages 77-94.
    14. Jeffrey A. Frankel & Kenneth A. Froot, 1985. "Using Survey Data to Test Some Standard Propositions Regarding Exchange Rate Expectations," NBER Working Papers 1672, National Bureau of Economic Research, Inc.
    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. Hamid Baghestani, 2010. "Evaluating Blue Chip forecasts of the trade-weighted dollar exchange rate," Applied Financial Economics, Taylor & Francis Journals, vol. 20(24), pages 1879-1889.
    2. Baghestani, Hamid & Toledo, Hugo, 2019. "Oil prices and real exchange rates in the NAFTA region," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 253-264.

    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. 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.
    2. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    3. 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.
    4. Manzan, Sebastiano & Westerhoff, Frank H., 2007. "Heterogeneous expectations, exchange rate dynamics and predictability," Journal of Economic Behavior & Organization, Elsevier, vol. 64(1), pages 111-128, September.
    5. Lucio Sarno & Giorgio Valente, 2009. "Exchange Rates and Fundamentals: Footloose or Evolving Relationship?," Journal of the European Economic Association, MIT Press, vol. 7(4), pages 786-830, June.
    6. 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.
    7. Hamid Baghestani, 2010. "Evaluating Blue Chip forecasts of the trade-weighted dollar exchange rate," Applied Financial Economics, Taylor & Francis Journals, vol. 20(24), pages 1879-1889.
    8. Faust, Jon & Rogers, John H. & H. Wright, Jonathan, 2003. "Exchange rate forecasting: the errors we've really made," Journal of International Economics, Elsevier, vol. 60(1), pages 35-59, May.
    9. Qi, Min & Wu, Yangru, 2003. "Nonlinear prediction of exchange rates with monetary fundamentals," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 623-640, December.
    10. 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.
    11. 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.
    12. 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.
    13. Atsushi Inoue & Lutz Kilian, 2005. "In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?," Econometric Reviews, Taylor & Francis Journals, vol. 23(4), pages 371-402.
    14. Michał Rubaszek & Paweł Skrzypczyński & Grzegorz Koloch, 2010. "Forecasting the Polish Zloty with Non-Linear Models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 2(2), pages 151-167, March.
    15. Atsushi Inoue & Lutz Kilian, 2005. "In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?," Econometric Reviews, Taylor & Francis Journals, vol. 23(4), pages 371-402.
    16. Zsolt Darvas & Zoltán Schepp, 2007. "Forecasting Exchange Rates of Major Currencies with Long Maturity Forward Rates," Working Papers 0705, Department of Mathematical Economics and Economic Analysis, Corvinus University of Budapest.
    17. Medel, Carlos & Camilleri, Gilmour & Hsu, Hsiang-Ling & Kania, Stefan & Touloumtzoglou, Miltiadis, 2015. "Robustness in Foreign Exchange Rate Forecasting Models: Economics-based Modelling After the Financial Crisis," MPRA Paper 65290, University Library of Munich, Germany.
    18. 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.
    19. Wright, Jonathan H., 2008. "Bayesian Model Averaging and exchange rate forecasts," Journal of Econometrics, Elsevier, vol. 146(2), pages 329-341, October.
    20. Kenneth S. Rogoff & Vania Stavrakeva, 2008. "The Continuing Puzzle of Short Horizon Exchange Rate Forecasting," NBER Working Papers 14071, National Bureau of Economic Research, Inc.

    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:eme:sefpps:v:26:y:2009:i:3:p:171-181. 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: Emerald Support (email available below). General contact details of provider: .

    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.