IDEAS home Printed from https://ideas.repec.org/a/wly/iecrev/v59y2018i4p2193-2218.html

Identifying Exchange Rate Common Factors

Author

Listed:
  • Ryan Greenaway‐McGrevy
  • Nelson C. Mark
  • Donggyu Sul
  • Jyh‐Lin Wu

Abstract

Using recently developed model selection procedures, we determine that exchange rate returns are driven by a two‐factor model. We identify them as a dollar factor and a euro factor. Exchange rates are thus driven by global, U.S., and euro‐zone stochastic discount factors. The identified factors can also be given a risk‐based interpretation. Identification motivates multilateral models for bilateral exchange rates. Out‐of‐sample forecast accuracy of empirically identified multilateral models dominates the random walk and a bilateral purchasing power parity fundamentals prediction model. Twenty‐four‐month‐ahead forecast accuracy of the multilateral model dominates those of a principal components forecasting model.

Suggested Citation

  • Ryan Greenaway‐McGrevy & Nelson C. Mark & Donggyu Sul & Jyh‐Lin Wu, 2018. "Identifying Exchange Rate Common Factors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(4), pages 2193-2218, November.
    • Handle: RePEc:wly:iecrev:v:59:y:2018:i:4:p:2193-2218
    DOI: 10.1111/iere.12334
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/iere.12334
    Download Restriction: no
    File URL: https://libkey.io/10.1111/iere.12334?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
    ---><---

    Other versions of this item:

    More about this item

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications

    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:wly:iecrev:v:59:y:2018:i:4:p:2193-2218. 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.

    We have no bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/deupaus.html .

    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.