I am working on a graduate level paper about using "Discriminate Analysis and other models" in Bankruptcy prediction and having trouble understanding the basic concepts of the overall nature of this assignment. I understand that it involves comparing statistical analysis but most of my research on "discriminate analysis" is taking me to medical references. Can you provide some direction on better understanding this concept?
The best-known, and most-widely used, multiple discriminant analysis method is the one proposed by Edward Altman, Professor of Finance at the Stern School of Business, New York University. Altman's z-score, or zeta model, combined various measures of profitability or risk. The resulting model was one that demonstrated a company's risk of bankruptcy relative to a standard. Altman's initial study proved his model to be very accurate; it correctly predicted bankruptcy in 94% of the initial sample (Altman 1968, 609).
Despite the positive results of his study, Altman's model had a key weakness: it assumed variables in the sample data to be normally distributed. "If all variables are not normally distributed, the methods employed may result in selection of an inappropriate set of predictors" (Sheppard 1994). Chistine Zavgren developed a model that corrected for this problem. Her model used logit analysis to predict bankruptcy. Due to its use of logit analysis, her model is considered "more robust" (Lo 1986, 151). Further, logit analysis actually provides a probability (in terms of a percentage) of bankruptcy. Also, the ...
I am working on a graduate level paper about using "Discriminate Analysis and other models" in Bankruptcy prediction and having trouble understanding the basic concepts of the overall nature of this assignment.