Prediction of Stock Performance in the Indian Stock Market Using Logistic Regression

10.6702/ijbi.2012.7.1.5

Avijan Dutta；Gautam Bandopadhyay；Suchismita Sengupta

Classification of stock performance ； Indian stock market ； logistic regression ； market rate of return ； financial ratios ； NIFTY

International Journal of Business and Information

7卷1期（2012 / 06 / 01）

105 - 136

英文

The authors use logistic regression (LR) and various financial ratios as independent variables to investigate indicators that significantly affect the performance of stocks actively traded on the Indian stock market. The study sample consists of the ratios of 30 large market capitalization companies over a four-year period. The study identifies and examines eight financial ratios that can classify the companies up to a 74.6% level of accuracy into two categories - ”good” or ”poor” - based on their rate of return. The paper asserts that the model developed can enhance an investor's stock price forecasting ability. Macroecomonic variables, which also can influence the share price, were not taken into account, however. The paper dicusses the practical implications of using the LR method to predict the probability of good stock performance. The authors state that the model can be used by investors, fund managers, and investment companies to enhance their abilty to select out-performing stocks.

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