A STUDY ON THE CAUSE-EFFECT RELATIONSHIP BETWEEN GROSS DOMESTIC PRODUCT AND STOCK MARKET PERFORMANCE IN INDIA

Abstract

 The Indian economy is the 5th largest economy by nominal GDP and the third-largest by purchasing power parity (PPP), which will continue to grow in the future. The growth of the Indian economy is likely to experience several ups and downs, including movements in its stock market. The study is designed to see the cause-effect relationship between GDP & Indian Stock Market. The data used in this study are the annual average stock market index (Sensex) and GDP rate (current US $) in India. BSE Sensex is the most used benchmark index in India, hence BSE Sensex has been used as a proxy for Indian Stock Market performance. Yearly data for the period from 1998 to 2019 have been put to Jarque- Bera test for Normality and Augmented Dickey-Fuller test for Unit Root. Then Granger Causality test have been performed between the two variables to know which one causes the other one. OLS method of regression has been used. Finally, Residual Diagnosis tests like residual normality, autocorrelation in the error term, and heteroscedasticity test have been resorted. From the analysis, it has been found that both variables are normal. With more than 95% level of confidence that the first difference of Sensex and GDP series is stationary, Granger Causality test showed that Sensex performance is cause by and not cause of GDP performance. The best fitted time series regression model showed that as much as 21.48% variation in Indian stock market performance is explained by Indian GDP performance only in general. The residual analysis with various tests confirmed that error terms are normally distributed, they are not correlated (no autocorrelation problem), and they are homoscedastic (i.e. there is no Heteroskedasticity problem).  Based on this analysis, the model is highly appreciable to predict Sensex flows in the context of Indian GDP performance.