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Abstract

The catenas between Foreign Direct Investment (FDI) and Stock Market Indices have always been a point of considerable debate in time series econometrics. It elevates a pragmatic question, whether the FDI have an effect on stock market indices or whether it is a consequence of development in stock market. This paper empirically investigates the impact of FDI on the S&P BSE Indices as an aggregate and at sectoral level with the help classical regression model, which is used for predicting the upcoming stock indices. Before forecasting the stock price, Kolmogorov-Smirnov, Shapiro-Wilk normality test and Q -Q plot technique were conducted on the sample data to conclude that the data are normally distributed and feasible to forecast. In order to avoid the possibility of biased result emanating from a likely existence, the overall performance as well as forecast accuracy of the model was examined by Mean Absolute Percentage Error (MAPE). Based on the findings, some of the requirements for entry of FDI into market should be relaxed to ensure that more FDI should come with new skills and technologies and ultimately contribute to economic growth of the Indian Economy.