ON LINEAR DISCRIMINATION WITH ACCOUNTING RATIOS
梳理了线性判别函数在会计比率建模中的最优性条件，指出不满足条件时模型输出存在偏差，并通过实证发现部分比率的截面性质不稳定，最后提出改进建议。
Much research in Accounting and Finance is concerned with using the linear discriminant function (LDF) to model accounting‐based ratios to predict financial events and other variables. Little attention has been given to the conditions under which the model is optimal, and to any resultant biases in model output associated with accounting ratios that do not meet optimality. This study lists conditions for LDF optimality, and discusses the potential problems when accounting numbers do not meet such conditions. This knowledge is extended by reported results of an empirical study which show that the cross‐sectional properties of some ratios arr not temporally stable. Finally, suggestions are offered to improve modeling efforts.