Discrminanat analysis helps an user/researcher/analyst to study the difference between two or more group of objects with accordance to various variables. It helps in determining the meaningful differences between the groups and identifying the discriminating power of each variable.
It also helps in evaluating financial decision such as different shares of stock in a portfolio. An user/researcher/analyst takes multiple factors into account, such as different financial ratios, when choosing between stocks in order to design an efficient portfolio.
It is a statistical technique designed to predict the groups or categories into which individual cases will fall on the basis of a number of independent variables. Discriminant analysis attempts to identify which variables or combinations of variables accurately discriminate between groups or categories by means of a scatter diagram or classification table.
How it is being used by people: Discriminant analysis has applications in finance, for example, credit risk analysis, or in the prediction of company failure (in bankruptcy prediction), and in the field of marketing, for market segmentation purposes.
Discriminant analysis is most useful to simulate the impact of a recession on the manufacturing sector (& in bankruptcy prediction) so that a measure of our current financial vulnerability is produced. In a period of economic recession and declining stock market values investors may value the safety of investment factor (in the multiple discriminant model of stock price stability) more than it would be valued in more normal capital markets.
By:Siddhartha Khandelwal (Fin Grp- 6)