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Cash Flow Patterns and Financial Distress Prediction

Author

Listed:
  • Adeyemi Aderin

    (University of Benin)

  • Otivbo Amede

    (University of Benin)

Abstract

The study investigates the ability of cash flow patterns to accurately predict the incidence of financial distress. A total of four hundred and ninety (490) firm-year observations were sampled consisting of non-financial firms quoted on the Nigerian Stock Exchange between 2011 and 2017. Several models were developed to capture different variants of the cash flow patterns along with the possibility of the life-cycle effect. The developed models were analysed using a combination of the Generalised Least Squares (GLS) and the Generalised Method of Moments (GMM). The results indicate that cash flow patterns have predictive ability in determining the incidence of financial distress both in the current period and in the immediately prior period. This predictive ability, however, does not extend to subsequent prior periods. Also, the life cycle effect significantly affects the pattern of relationship between the cash flow patterns and financial distress prediction. The study was able to correct the problem of assignment of weights to individual cash flow patterns, but recommended the inculcation of the complete life cycle effects capturing individual stages of organisational development in the models.

Suggested Citation

  • Adeyemi Aderin & Otivbo Amede, 2022. "Cash Flow Patterns and Financial Distress Prediction," EuroEconomica, Danubius University of Galati, issue 1(12), pages 45-56, April.
    • Handle: RePEc:dug:journl:y:2022:i:1:p:45-56
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    File URL: https://dj.univ-danubius.ro/index.php/JAM/article/view/1544
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