IDEAS home Printed from https://ideas.repec.org/h/eme/aecozz/s0731-905320140000033019.html
   My bibliography  Save this book chapter

Assessing the Power of Long-Horizon Predictive Tests in Models of Bull and Bear Markets

In: Essays in Honor of Peter C. B. Phillips

Author

Listed:
  • Alex Maynard
  • Dongmeng Ren

Abstract

Abstract We compare the finite sample power of short- and long-horizon tests in nonlinear predictive regression models of regime switching between bull and bear markets, allowing for time varying transition probabilities. As a point of reference, we also provide a similar comparison in a linear predictive regression model without regime switching. Overall, our results do not support the contention of higher power in longer horizon tests in either the linear or nonlinear regime switching models. Nonetheless, it is possible that other plausible nonlinear models provide stronger justification for long-horizon tests.

Suggested Citation

  • Alex Maynard & Dongmeng Ren, 2014. "Assessing the Power of Long-Horizon Predictive Tests in Models of Bull and Bear Markets," Advances in Econometrics,in: Essays in Honor of Peter C. B. Phillips, volume 33, pages 673-711 Emerald Publishing Ltd.
  • Handle: RePEc:eme:aecozz:s0731-905320140000033019
    as

    Download full text from publisher

    File URL: http://www.emeraldinsight.com/10.1108/S0731-905320140000033019?utm_campaign=RePEc&WT.mc_id=RePEc
    Download Restriction: Access to full text is restricted to subscribers

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

    More about this item

    Keywords

    Predictive regression; long-horizon regression; regime-switching; nonlinear; stock return predictability; G12; G14; C51; C53; C58;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

    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:eme:aecozz:s0731-905320140000033019. 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: (Charlotte Maiorana). General contact details of provider: http://www.emeraldinsight.com .

    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.