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

Avijan Dutta ； Gautam Bandopadhyay ； Suchismita Sengupta

《International Journal of Business and Information》 7卷1期 (2012/06) Pp. 105-136

https://doi.org/10.6702/ijbi.2012.7.1.5

並列摘要

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.

並列關鍵字

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

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