Financial Distress Models of Determining a Firm’s Bankruptcy

                          Financial Distress Models of Determining a Firm’s Bankruptcy

                                             Taylor Mason

                                        Hampton University

                                                  3/28/16

                                                Abstract

In this paper the observing of the difference between the variety of financial distress models. These models help to determine a firm’s financial ability to stay afloat from going bankrupt. The financial distress models have different formulas that produce the sum also known as the z-score which is ranked on a scale of 0-3.0. The lower the number produced demonstrates a firms negative ability to stay afloat and the higher the number the safer the firm is away from bankruptcy. These findings suggest that there are multiple ways for a firm to determine their status when it comes to bankruptcy before it even happens.

How do you predict the financial failure of a firm?

         Financial failure can be defined as the inability of a firm to pay its current liabilities. Financial failure may lead firms to bankrupt or go into liquidation. Firms that cannot meet obligation standards or has difficulty fulfilling previously made obligations will begin to experience financial failure. Financial failure will continue to increase if cash flows could not meet the financial. The risk may continue to increase and become unfavorable for the firm depending on the conditions of the economy at that time. The company’s specific factors could also leave the firm in a difficult situation. When most individuals think of corporate failure it is not simply because of the closure of a company but has wider implications, the constructing of these models of corporate failure allow outsiders to form assessments and prediction. If bankruptcy can be predicted accurately, it may be possible for the firm to be restructured, thus avoiding failure. This would benefit owners, employees, creditors, and shareholders alike.

Financial Distress Model        

The Discriminant Analysis Model. The Discriminant Analysis Model can help to predict the value and qualification of a firm’s statistical ability to stay afloat as a firm. Discriminant analysis has statistical technique used to reduce the differences between a varieties of variables in order to classify them into a set of number of groups. In finance, this technique is used to compress the variance between securities while also allowing the person to screen for several variables. It is related to discriminant analysis, which, in simplified terms, tries to classify a data set by setting a rule (or selecting a value) that will provide the most meaningful separation. The earliest example of ratio analysis in predicting corporate failure is attributed to Patrick during the year 1932. Discriminant analysis is one of the most frequently used methods in examination of financial failure. Discriminant analysis is a technique that helps to provide information to different groups by using accurate mathematical techniques. It also helps to provide identity to the variables to intensify and determine what factors may or may not affect the differentiation between groups. In discriminant analysis you must test the validity and significance of models which is taken from the stepwise method because it is very important to meet the conditions and assumptions to prevent misstatement of problems.  Discriminant function formula is as follow (Z = α+ b1 X1 + b2 X2 + ………..+ bnXn).

        Z Score. The Z-score model is the next model that can help to predict financial bankruptcy. The formula for predicting bankruptcy was published in 1968 by Edward I. Altman. The formula is as follow (Z = 3.25 + 6.56X1 + 3.26X2 + 6.72X3 + 1.05X) Edward I. Altman at the time of this discovery was an Assistant Professor of Finance at New York University. The formula is used to predict the likelihood and probability that a firm will go into bankruptcy two years out. The Altman Z-Score after testing was found to be 72% accurate in predicting bankruptcy two years before the actual taking place of bankruptcy.

The Z-score model was found to be approximately 80%–90% accurate in predicting bankruptcy one year before the event. Altman applied the Z-score model to find the statistical method of discriminant analysis to a data set of publicly held manufacturers.  The Z-score is used to predict in advance the corporate misstatements. It allows for easy to calculate measures of control for the companies that are under financial distress status of companies in academic studies. The Z-score allows for investors and other viewers to use multiple corporate income and balance sheet values to measure the corporate health of the firm.

The Z-score is a linear combination of four or five common business ratios, weighted by coefficients. The coefficients were estimated by identifying a set of firms which had declared bankruptcy and then comparing the matched samples of firms who have succeeded, with matching by industry and approximate size of the value of assets. The estimation of how effective the Z-score was originally based on data from publicly held manufacturers, but has since been re-estimated based on other datasets for private manufacturing, non-manufacturing and service companies. The score helps to determine the likelihood of failure (companies with a Z score below 1.81 are in danger and possibly heading towards bankruptcy between 1.81 and 2.99 - companies with scores between 1.81 and 2.99 need further investigation and companies with a score of 3 or above are financially sound).