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Mixed logistic model with two independent random coefficients for financial crisis prediction: Argentinean companies

Author

Listed:
  • Norma Patricia Caro
  • Margarita Diaz
  • Fernando Garcia
  • Marcela Porporato

Abstract

The paper develops a mixed logistic financial distress prediction model with two independent random coefficients and validates it for public Argentinean companies. This study complements existing literature on bankruptcy prediction in emerging economies advancing the application of contemporary econometric methods (Caro et al., 2013). Anticipating bankruptcy risks increases portfolios' profitability. Emerging economies and frontier markets differ from developed economies in political, cultural, social and institutional terms. Given those differences, investors and lenders need specific bankruptcy and financial distress prediction models. The model developed achieves an excellent performance using financial statements from firms listed in the Buenos Aires Stock Exchange during 1993-2000 with ratios accepted in the literature (Altman, 1993; Jones and Hensher, 2004). Results show that profitability, assets turnover and cash flow from operations reduce the likelihood of financial distress while leverage increases it for companies operating in a frontier market such as Argentina.

Suggested Citation

  • Norma Patricia Caro & Margarita Diaz & Fernando Garcia & Marcela Porporato, 2020. "Mixed logistic model with two independent random coefficients for financial crisis prediction: Argentinean companies," International Journal of Accounting and Finance, Inderscience Enterprises Ltd, vol. 10(1), pages 40-63.
    • Handle: RePEc:ids:intjaf:v:10:y:2020:i:1:p:40-63
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