Stock Market Volatility and Anomalies in India: A Behavioural Approach

Abstract

Purpose: The major objective of this research is to investigate the existence of volatility-based anomalies in Indian stock market, which are the result of various behavioural biases. The nature of Indian stock market volatility is investigated employing various volatility models such as spillover effect profoundly acknowledged as herding, leverage effect prominently entitled as low volatility anomaly and persistence of long- and short-term volatility. Design/Methodology/Approach: The present study has employed various autoregressive conditional heteroscedasticity (ARCH) family models such as generalised autoregressive conditional heteroscedasticity (GARCH), exponential GARCH (EGARCH) and component GARCH (CGARCH) to appraise assorted nature of volatility patterns in Indian stock market. Findings: The results empirically validate that herding endures in both bullish and bearish trend, whereas herding has amplified for Nifty and Smallcap in bearish trend. Furthermore, the results divulge the existence of stock market inefficiency due to low volatility anomaly. The outcomes pragmatically verify the persistence of volatility in long and short run. The empirical evidences also assist in acknowledging the degree of subsistence of anomalies and biases in market uptrends and downtrends in order to comprehend the level of rationality of investors in diverse market situations. Practical Implications: Various GARCH models, employed in the study, alleviate a direction for forecasting as regards volatility to assemble optimum portfolio in diverse market situations. Originality/Value: The present study gives a distinctive insight on the existence of volatility-based anomalies using exclusive econometric models. It informs about the market anomalies and states about the most prominent bias.