IDEAS home Printed from https://ideas.repec.org/p/crd/wpaper/08009.html
   My bibliography  Save this paper

A New Look at the Forward Premium Puzzle

Author

Abstract

This paper analyzes the sampling properties of the widely documented large negative slope estimates in regressions of future exchange returns on current forward premium. We argue that the abnormal behavior of the slope estimators in these regressions arises from the simultaneous presence of high persistence, low signal-to-noise ratio, strong endogeneity and an omitted variable problem. The paper develops the limiting theory for the slope parameter estimators in the levels and differenced forward premium regressions under some assumptions that match the empirical properties of the data. The asymptotic results derived in the paper help to reconcile the findings from the levels and difference specifications and provide important insights about the time series properties of the implied risk premium.

Suggested Citation

  • Nikolay Gospodinov, 2006. "A New Look at the Forward Premium Puzzle," Working Papers 08009, Concordia University, Department of Economics, revised Dec 2008.
  • Handle: RePEc:crd:wpaper:08009
    as

    Download full text from publisher

    File URL: http://alcor.concordia.ca/~gospodin/research/forwprem.pdf
    Download Restriction: no

    Other versions of this item:

    Citations

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


    Cited by:

    1. Frankel, Jeffrey & Poonawala, Jumana, 2010. "The forward market in emerging currencies: Less biased than in major currencies," Journal of International Money and Finance, Elsevier, vol. 29(3), pages 585-598, April.
    2. Carmen Gloria Silva, 2010. "Forward premium puzzle and term structure of interest rates: the case of New Zealand," Working Papers Central Bank of Chile 570, Central Bank of Chile.
    3. Aziz Chouikh & Abdelwahed Trabelsi, 2014. "Modeling Risk Premia in Forward Foreign Exchange Rates as Unobserved Components: The Model Identification Problem," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 5(3), pages 119-135, July.
    4. Phillips, Peter C.B. & Lee, Ji Hyung, 2013. "Predictive regression under various degrees of persistence and robust long-horizon regression," Journal of Econometrics, Elsevier, vol. 177(2), pages 250-264.
    5. Norman C. Miller, 2014. "Exchange Rate Economics," Books, Edward Elgar Publishing, number 14981.
    6. Bai, Shuming & Mollick, Andre Varella, 2010. "Currency crisis and the forward discount bias: Evidence from emerging economies under breaks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(5), pages 556-574, December.
    7. repec:eee:empfin:v:42:y:2017:i:c:p:199-211 is not listed on IDEAS
    8. Shehadeh, Ali & Li, Youwei & Moore, Michael, 2016. "The Forward Premium Bias, Carry Trade Return and the Risks of Volatility and Liquidity," MPRA Paper 71709, University Library of Munich, Germany.
    9. Raj Aggarwal & Brian M. Lucey & Fergal A. O'Connor, 2014. "Rationality in Precious Metals Forward Markets: Evidence of Behavioural Deviations in the Gold Markets," The Institute for International Integration Studies Discussion Paper Series iiisdp462, IIIS.
    10. Shang, Hua, 2013. "Inference in asset pricing models with a low-variance factor," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 1046-1060.
    11. Anatolyev, Stanislav & Gospodinov, Nikolay & Jamali, Ibrahim & Liu, Xiaochun, 2015. "Foreign exchange predictability during the financial crisis: implications for carry trade profitability," FRB Atlanta Working Paper 2015-6, Federal Reserve Bank of Atlanta.

    More about this item

    Keywords

    Forward premium anomaly; high persistence; low signal-to-noise ratio; local-to-unity asymptotics;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • F31 - International Economics - - International Finance - - - Foreign Exchange

    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:crd:wpaper:08009. 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: (Economics Department). General contact details of provider: http://edirc.repec.org/data/deconca.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.

    We have no references for this item. You can help adding them by using 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.