Sensitivity of Indian Stock Market vis-à-vis Price Volume Relationship in the Backdrop of FII

Abstract

This study aims to examine the changes in the dynamic relationship between return registered by stocks and trading volume because of the changes in the flow of Foreign Institutional Investments in the Indian stock market. Author has tested the relationship using daily data of S&P CNX Nifty (that is, NSE’s index) from 2000 to 2013 and methodologies described by Bollerslav (1986), Engle (1982) and Sims (1980), that is, Generalized Auto Regressive Conditional Heteroskedasticity (GARCH) (1, 1), Exponential Generalized Auto Regressive Conditional Heteroskedasticity (EGARCH) (1, 1), Vector Autoregression (VAR), Granger causality, Variance Decomposition (VDC) and Impulse Response Function (IRF). The empirical analysis evidences the significant role of trading volume in lessening volatility and also adjudges the Indian stock market highly inefficient due to the presence of volatility persistence. In addition, VAR results document serial correlation between trading volume coefficients and its lagged values in case of all the subsamples that confirm the flow of information arrival sequential. Besides this, VDC and IRF results also assert that the amount of information contributed by stock return for the prediction of trading volume is far greater than the other way around and announce the study of stock return more useful in predicting the future kinetics of stock return as well as trading volume.