Predicting corporate financial distress: Reflections on choice-based sample bias

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A real-valued genetic algorithm to optimize the parameters of support vector machine for predicting bankruptcy (2007, methodology): “A lower matching ratio (e.g., 1:1 or 1:2) corresponds to higher bias in the selection in choicebased, which leads to oversampling ( Platt & Platt, 2002; Zmijewski, 1984).”
Remaining Financially Healthy and Competitive: The Role of Financial Predictors (2020, background): “Platt & Platt (2002) emphasize the deficiency of a uniform definition of the situation when a financial distress occurs in an enterprise and attempts to epitomize various operational determinations of financial distress in one way.”
Firm exit after distress: differentiating between bankruptcy, voluntary liquidation and M&A (2011, positive): “…working capital, retained earnings deficits, share sales to private investors, capital restructuring or reorganization, negative shareholder’s funds, suspension of dividend payments, and major restructurings or layoffs (McKeown et al. 1991; McLeay and Omar 2000; Platt and Platt 2002, 2006).”
Corporate Financial Distress: An Empirical Analysis of Distress Risk (2007, background): “36 Platt and Platt (2002) highlight the lack of a consistent definition when a company enters financial distress and try to summarize different operational definitions of financial 31 See e.g. Altman (2000), Beaver (1966), Duffi and Wang (2004), Ohlson (1980), Zmijewski (1984).”