IDEAS home Printed from https://ideas.repec.org/a/wly/jforec/v33y2014i1p15-31.html

In‐Sample and Out‐of‐Sample Prediction of stock Market Bubbles: Cross‐Sectional Evidence

Author

Listed:
  • Helmut Herwartz
  • Konstantin A. Kholodilin

Abstract

We evaluate the informational content of ex post and ex ante predictors of periods of excess stock (market) valuation. For a cross section comprising 10 OECD economies and a time span of at most 40 years alternative binary chronologies of price bubble periods are determined. Using these chronologies as dependent processes and a set of macroeconomic and financial variables as explanatory variables, logit regressions are carried out. With model estimates at hand, both in-sample and out-of-sample forecasts are made. Overall, the degree of ex ante predictability is limited if an analyst targets the detection of particular turning points of market valuation. The set of 13 potential predictors is classified in measures of macroeconomic or monetary performance, stock market characteristics, and descriptors of capital valuation. The latter turn out to have strongest in-sample and out-of-sample explanatory content for the emergence of price bubbles. In particular, the price to book ratio is fruitful to improve the ex-ante signalling of stock price bubbles.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Helmut Herwartz & Konstantin A. Kholodilin, 2014. "In‐Sample and Out‐of‐Sample Prediction of stock Market Bubbles: Cross‐Sectional Evidence," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(1), pages 15-31, January.
    • Handle: RePEc:wly:jforec:v:33:y:2014:i:1:p:15-31
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1002/for.2269
    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. Hans-Eggert Reimers, 2012. "Early Warning Indicator Model of Financial Developments Using an Ordered Logit," Business and Economic Research, Macrothink Institute, vol. 2(2), pages 171-191, December.
    2. Zhi-Qiang Jiang & Gang-Jin Wang & Askery Canabarro & Boris Podobnik & Chi Xie & H. Eugene Stanley & Wei-Xing Zhou, 2018. "Short term prediction of extreme returns based on the recurrence interval analysis," Quantitative Finance, Taylor & Francis Journals, vol. 18(3), pages 353-370, March.
    3. Kholodilin, Konstantin A. & Michelsen, Claus, 2019. "Zehn Jahre nach dem großen Knall: wie ist es um die Stabilität der internationalen Immobilienmärkte bestellt?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 5(1), pages 67-87.
    4. Konstantin A. Kholodilin & Sebastian Kohl & Florian Müller, 2023. "Government-Made House Price Bubbles? Austerity, Homeownership, Rental, and Credit Liberalization Policies and the “Irrational Exuberance” on Housing Markets," Discussion Papers of DIW Berlin 2061, DIW Berlin, German Institute for Economic Research.
    5. Helmut Herwartz & Konstantin A. Kholodilin, 2014. "Uncertainty of Macroeconomic Forecasters and the Prediction of Stock Market Bubbles," Discussion Papers of DIW Berlin 1405, DIW Berlin, German Institute for Economic Research.
    6. Fu, Junhui & Zhou, Qingling & Liu, Yufang & Wu, Xiang, 2020. "Predicting stock market crises using daily stock market valuation and investor sentiment indicators," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    7. Li, Wei-Xuan & Chen, Clara Chia-Sheng & French, Joseph J., 2015. "Toward an early warning system of financial crises: What can index futures and options tell us?," The Quarterly Review of Economics and Finance, Elsevier, vol. 55(C), pages 87-99.

    More about this item

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - 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:jforec:v:33:y:2014:i:1:p:15-31. 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: http://www3.interscience.wiley.com/cgi-bin/jhome/2966 .

    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.