IDEAS home Printed from
   My bibliography  Save this paper

Conditional Evaluation of Exchange Rate Predictive Ability in Long Run Regressions


  • Pablo Pincheira


In this paper we evaluate exchange rate predictability using a new framework developed by Giacomini and White (2004). In this new framework we test for conditional predictive ability rather than for unconditional predictive ability, which has been the usual approach thus far. Using several shrinkage based forecasting methods, including new methods proposed here, we evaluate conditional predictability of five bilateral exchange rates at differing horizons. Our results indicate that for most currencies a random walk would not be the best forecasting method in a real time forecasting exercise, at least for some predictive horizons. We also show that our proposed shrinkage methods in general perform on par with Bayesian shrinkage and ridge regressions, and sometimes they even perform better.

Suggested Citation

  • Pablo Pincheira, 2006. "Conditional Evaluation of Exchange Rate Predictive Ability in Long Run Regressions," Working Papers Central Bank of Chile 378, Central Bank of Chile.
  • Handle: RePEc:chb:bcchwp:378

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. 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.
    2. 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.
    3. McCracken, Michael W & Sapp, Stephen G, 2005. "Evaluating the Predictability of Exchange Rates Using Long-Horizon Regressions: Mind Your p's and q's!," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 473-494, June.
    4. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
    5. West, Kenneth D, 1996. "Asymptotic Inference about Predictive Ability," Econometrica, Econometric Society, vol. 64(5), pages 1067-1084, September.
    6. Ronald MacDonald & Ian W. Marsh, 1997. "On Fundamentals And Exchange Rates: A Casselian Perspective," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 655-664, November.
    7. 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.
    8. Chinn, Menzie D. & Meese, Richard A., 1995. "Banking on currency forecasts: How predictable is change in money?," Journal of International Economics, Elsevier, vol. 38(1-2), pages 161-178, February.
    9. 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)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Laura D'Amato & Lorena Garegnani & Emilio Blanco, 2016. "GDP Nowcasting: Assessing the Cyclical Conditions of the Argentine Economy," Ensayos Econ├│micos, Central Bank of Argentina, Economic Research Department, vol. 1(74), pages 7-26, December.
    2. Laura D┬┤Amato & Lorena Garegnani & Emilio Blanco, 2015. "GDP Nowcasting: Assessing business cycle conditions in Argentina," BCRA Working Paper Series 201569, Central Bank of Argentina, Economic Research Department.

    More about this item


    Access and download statistics


    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:chb:bcchwp:378. 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: (Claudio Sepulveda). General contact details of provider: .

    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.