Earlier Ratio Analysis was used as an analytical technique to measure the performance of the companies. The performance of the companies, as measured by the ratios , such as profitability, liquidity and solvency prevailed as the most significant indicator but the order of their importance is not being clear , since in each and every case taken ,some different ratio came out as the most important factor and sometimes it might seem to be confusing , for instance, a firm with a poor profitability / solvency record may be regarded as potentially bankrupt.
Discriminant Analysis is a technique , which has been applied nowadays successfully to financial problems such as credit evaluation (as had been illustrated in class) and investment analysis. It is a parametric technique to determine , which weightings of quantitative variables or predictors best discriminate between 2 or more than 2 groups of cases. Analysis creates a discriminant function , which is a linear combination of the weightings and scores on these variables. The maximum no. Of functions is either the no. Of predictors or the no. of groups minus one , whichever of these two values is the smaller.
Where Zjk = Z score of discriminate function
Wi=Discriminant coefficient for the independent variable i
Xi =independent variable i
In a 2 group discriminant function, cutting score is used to classify he two groups uniquely. Optimal cutting score is halfway between the centroid of two groups.
The primary goal is to find dimensions that groups differ on and ,create classification functions , then we need to find along how many dimensions do groups differ reliably.
By discriminant analysis , we can find which ratios are affecting the performance of a company .
Where Xis can be working capital / total assets, retained earnings / total assets, EBIT/total assets, B/E value, sales/ total assets etc.
It can then be applied to similar other companies.
We use discriminant analysis in evaluating consumer loan application. A fast and efficient device for detecting unfavourable credit risks might avoid the loan officer to avoid disastrous decisions. Thus it can be thought of as a potential weapon to be used in business sector.
Neeraj Kumar Singh