Advanced Search
MyIDEAS: Login to save this paper or follow this series

Stock Picking via Nonsymmetrically Pruned Binary Decision Trees

Contents:

Author Info

  • Anton Andriyashin
Registered author(s):

    Abstract

    Stock picking is the field of financial analysis that is of particular interest for many professional investors and researchers. In this study stock picking is implemented via binary classification trees. Optimal tree size is believed to be the crucial factor in forecasting performance of the trees. While there exists a standard method of tree pruning, which is based on the cost-complexity tradeoff and used in the majority of studies employing binary decision trees, this paper introduces a novel methodology of nonsymmetric tree pruning called Best Node Strategy (BNS). An important property of BNS is proven that provides an easy way to implement the search of the optimal tree size in practice. BNS is compared with the traditional pruning approach by composing two recursive portfolios out of XETRA DAX stocks. Performance forecasts for each of the stocks are provided by constructed decision trees. It is shown that BNS clearly outperforms the traditional approach according to the backtesting results and the Diebold-Mariano test for statistical significance of the performance difference between two forecasting methods.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2008-035.pdf
    Download Restriction: no

    Bibliographic Info

    Paper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2008-035.

    as in new window
    Length: 36 pages
    Date of creation: May 2008
    Date of revision:
    Handle: RePEc:hum:wpaper:sfb649dp2008-035

    Contact details of provider:
    Postal: Spandauer Str. 1,10178 Berlin
    Phone: +49-30-2093-5708
    Fax: +49-30-2093-5617
    Email:
    Web page: http://sfb649.wiwi.hu-berlin.de
    More information through EDIRC

    Related research

    Keywords: decision tree; stock picking; pruning; earnings forecasting; data mining;

    Find related papers by JEL classification:

    This paper has been announced in the following NEP Reports:

    References

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
    as in new window
    1. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 20(1), pages 134-44, January.
    2. Balvers, Ronald J & Cosimano, Thomas F & McDonald, Bill, 1990. " Predicting Stock Returns in an Efficient Market," Journal of Finance, American Finance Association, American Finance Association, vol. 45(4), pages 1109-28, September.
    3. Hamao, Yasushi & Campbell, John, 1992. "Predictable Stock Returns in the United States and Japan: A Study of Long-Term Capital Market Integration," Scholarly Articles 3207694, Harvard University Department of Economics.
    4. Neftci, Salih N, 1991. "Naive Trading Rules in Financial Markets and Wiener-Kolmogorov Prediction Theory: A Study of "Technical Analysis."," The Journal of Business, University of Chicago Press, University of Chicago Press, vol. 64(4), pages 549-71, October.
    5. Donald B. Keim & Robert F. Stambaugh, . "Predicting Returns in the Stock and Bond Markets," Rodney L. White Center for Financial Research Working Papers, Wharton School Rodney L. White Center for Financial Research 15-85, Wharton School Rodney L. White Center for Financial Research.
    6. Fama, Eugene F & French, Kenneth R, 1988. "Permanent and Temporary Components of Stock Prices," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 96(2), pages 246-73, April.
    7. Newey, Whitney K & West, Kenneth D, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," Review of Economic Studies, Wiley Blackwell, Wiley Blackwell, vol. 61(4), pages 631-53, October.
    8. Hartzmark, Michael L, 1991. "Luck versus Forecast Ability: Determinants of Trader Performance in Futures Markets," The Journal of Business, University of Chicago Press, University of Chicago Press, vol. 64(1), pages 49-74, January.
    9. Fama, Eugene F. & French, Kenneth R., 1988. "Dividend yields and expected stock returns," Journal of Financial Economics, Elsevier, Elsevier, vol. 22(1), pages 3-25, October.
    10. Fama, Eugene F, 1991. " Efficient Capital Markets: II," Journal of Finance, American Finance Association, American Finance Association, vol. 46(5), pages 1575-617, December.
    11. Kar Yan Tam & Melody Y. Kiang, 1992. "Managerial Applications of Neural Networks: The Case of Bank Failure Predictions," Management Science, INFORMS, INFORMS, vol. 38(7), pages 926-947, July.
    12. Fama, Eugene F & French, Kenneth R, 1992. " The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, American Finance Association, vol. 47(2), pages 427-65, June.
    13. Chen, Nai-Fu, 1991. " Financial Investment Opportunities and the Macroeconomy," Journal of Finance, American Finance Association, American Finance Association, vol. 46(2), pages 529-54, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:hum:wpaper:sfb649dp2008-035. 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: (RDC-Team).

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 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.