IDEAS home Printed from
   My bibliography  Save this article

Does the prediction horizon matter for the forward premium anomaly? Evidence from panel data


  • Yang, Kun
  • Shintani, Mototsugu


No abstract is available for this item.

Suggested Citation

  • Yang, Kun & Shintani, Mototsugu, 2006. "Does the prediction horizon matter for the forward premium anomaly? Evidence from panel data," Economics Letters, Elsevier, vol. 93(2), pages 255-260, November.
  • Handle: RePEc:eee:ecolet:v:93:y:2006:i:2:p:255-260

    Download full text from publisher

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. Alexius, Annika, 2001. "Uncovered Interest Parity Revisited," Review of International Economics, Wiley Blackwell, vol. 9(3), pages 505-517, August.
    2. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    3. 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.
    4. Arellano, Manuel, 2003. "Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780199245291, June.
    5. 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.
    6. Chaboud, Alain P. & Wright, Jonathan H., 2005. "Uncovered interest parity: it works, but not for long," Journal of International Economics, Elsevier, vol. 66(2), pages 349-362, July.
    7. Fama, Eugene F., 1984. "Forward and spot exchange rates," Journal of Monetary Economics, Elsevier, vol. 14(3), pages 319-338, November.
    8. 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. Barrera, Carlos R., 2010. "Redes neuronales para predecir el tipo de cambio diario," Working Papers 2010-001, Banco Central de Reserva del PerĂº.
    2. Lahiri, Kajal & Sheng, Xuguang, 2008. "Evolution of forecast disagreement in a Bayesian learning model," Journal of Econometrics, Elsevier, vol. 144(2), pages 325-340, June.

    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:eee:ecolet:v:93:y:2006:i:2:p:255-260. 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: (Dana Niculescu). 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.