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Predicting Firm Failure: A Behavioral Finance Perspective

  • Rassoul Yazdipour

    (California State University, Fresno)

  • Richard Constand

    (University of West Florida)

Registered author(s):

    In this article we first argue that researchers in the area of financial distress and failure cannot ignore the human/managerial/decision-making side of the business and just focus on the business' operations side; as has been the case so far for almost all the research in the area. We then discuss how psychological phenomena and principles, known as heuristics or mental shortcuts, could be utilized in building more powerful success/failure prediction models especially for small and medium sized enterprises (SMEs).

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    File URL: http://jefsite.org/RePEc/pep/journl/jef-2010-14-3-d-yazdipour.pdf
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    Article provided by Pepperdine University, Graziadio School of Business and Management in its journal Journal of Entrepreneurial Finance.

    Volume (Year): 14 (2010)
    Issue (Month): 3 (Fall)
    Pages: 90-104

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    Handle: RePEc:pep:journl:v:14:y:2010:i:3:p:90-104
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    Web page: http://bschool.pepperdine.edu/jef

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    1. Zhang, Guoqiang & Y. Hu, Michael & Eddy Patuwo, B. & C. Indro, Daniel, 1999. "Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis," European Journal of Operational Research, Elsevier, vol. 116(1), pages 16-32, July.
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    15. Harlan Platt & Marjorie Platt, 2002. "Predicting corporate financial distress: Reflections on choice-based sample bias," Journal of Economics and Finance, Springer, vol. 26(2), pages 184-199, June.
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