Abstract

PREDICTION OF BANKS STOCK PERFORMANCE IN NIGERIA STOCK EXCHANGE MARKET: AN APPLICATION OF LOGISTIC REGRESSION MODEL

C. L. Ani,1 U. M. Hassan2 and M. I. Maiwando3

---

The key purpose behind the study is to use binary logistic regression model to predict stock performance of banks in Nigeria. For this purpose, different financial ratios were used as independent variables in determining bank stock performance (i.e. either ?good? or ?poor?) as dependent variable. The sample consist of six financial ratios of 18 selected listed banks of Nigeria?s Stock Exchange (NSE) over seven year period. The result shows that step three (3) model significantly predict the stock performance. The findings indicate that, the classification results showed high predictive accuracy rates of 100 percent, which indicates that the step 3 model can accurately predict good as well as poor performing stock. Also, the goodness of fit test showed that step 3 model chi-square value is found to be 0.000 (Hosmer and Lemeshow test), which indicates acceptance of the null hypothesis of the model, meaning there is not much difference between observed and predicted values. This result shows that the model appears to fit the data. The model can be used by investors, fund managers and investment banks to enhance their ability to pick outperforming stock. Thus, this study shows that Logistic regression model can be used by investors, individual as well as institutions or fund managers to enhance their ability to predict ?good or poor? stock. Keywords: Stock Performance Classification, Logistic Regression, Goodness-of-fit, Financial Ratios, Nigeria Stock Exchange.

PDF