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Predicting Financial Distress: Multi Scenarios Modeling Using Neural Network

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  • Mohamed Gameel
  • Khairy El-Geziry

Abstract

This paper aims to investigate the best scenario to predict financial distress in the Egyptian stock market using a neural network model. The sample consists of 37 company listed on the EGX100. The sample period is eight years from 2001 to 2008, so we can isolate the effects of global financial Depression in the end of 2008, and the effect of economic instability, which coincided with the Egyptian revolution in 2011 tell now. The results show evidence that the best scenario for predicting distress in Egypt is that the company will be distressed if there is a decreasing in liquidity, decreasing in generating cash from sales with increasing in financial leverage.

Suggested Citation

  • Mohamed Gameel & Khairy El-Geziry, 2016. "Predicting Financial Distress: Multi Scenarios Modeling Using Neural Network," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(11), pages 159-159, November.
    • Handle: RePEc:ibn:ijefaa:v:8:y:2016:i:11:p:159
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    References listed on IDEAS

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    4. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    5. Zmijewski, Me, 1984. "Methodological Issues Related To The Estimation Of Financial Distress Prediction Models," Journal of Accounting Research, Wiley Blackwell, vol. 22, pages 59-82.
    6. Mensah, Ym, 1984. "An Examination Of The Stationarity Of Multivariate Bankruptcy Prediction Models - A Methodological Study," Journal of Accounting Research, Wiley Blackwell, vol. 22(1), pages 380-395.
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    Cited by:

    1. Sunday Nosa UGBOGBO (Ph.D) & Sunday Nosa UGBOGBO (Ph.D), 2023. "Capital Structure and Corporate Financial Distress of Quoted Non-Financial Firms in Nigeria," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 7(6), pages 1302-1314, June.

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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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