Models to Predict Bankruptcy

Running Head: MODELS TO PREDICT BANKRUPTCY

Using Discriminate Analysis and Other Models to Predict Bankruptcy

Abstract

In light of today’s volatile economic climate and uncertain credit markets, it is important that investors and organizations alike identify key distress factors that could result in bankruptcy. When financial distress is experienced by firms, the objective should be to minimize losses and recreate processes for future success. Bankruptcy prediction models can assist organizations in analyzing their weaknesses and where necessary identify improvements as needed. Prediction models can also aid healthy firms in decision making as their customers and suppliers are confronted with the risk of bankruptcy.

Using Discriminate Analysis and Other Models to Predict Bankruptcy

Threats that cause a company to consider bankruptcy are many. General economic conditions, industry trends, and company-specific problems such as shifting consumer tastes, obsolescent technology and changing demographics are among the factors that can cause a company’s intrinsic value to decline (Bringham and Ehrhardt, 2011). However, bankruptcy is not isolated to the organization. Bankruptcy can be considered by customers, suppliers and investors. Therefore, it is vital that awareness become a priority in recognizing early warning signals in order to minimize losses.

Bankruptcy prediction models have been developed and are still evolving as the perfect model has yet to be discovered. Models involve accounting and market-based indicators and assess bankruptcy predictions, corporate distress, corporate failure prediction, credit risk and default predictions are among the many indicators (Atiya, 2001). Models used to predict corporate bankruptcy are based on univariate analysis, multiple discriminate analysis (MDA), linear probability analysis, logit analysis, probit analysis, cumulative sums methodology, partial adjustment process, recursively partitioned decision...