Jyoti Kumari

Stock returns predictability and the adaptive market hypothesis in emerging markets: evidence from India.

This study addresses the question of whether the adaptive market hypothesis provides a better description of the behaviour of emerging stock market like India. We employed linear and nonlinear methods to evaluate the hypothesis empirically. The linear tests show a cyclical pattern in linear dependence suggesting that the Indian stock market switched between periods of efficiency and inefficiency. In contrast, the results from nonlinear tests reveal a strong evidence of nonlinearity in returns throughout the sample period with a sign of tapering magnitude of nonlinear dependence in the recent period. The findings suggest that Indian stock market is moving towards efficiency. The results provide additional insights on association between financial crises, foreign portfolio investments and inefficiency.JEL codesG14; G12; C12

Investor Sentiment and Stock Market Volatility: Evidence from India

ABSTRACT In this article, the authors probe the role of irrational investor sentiment in the determination of Indian stock market volatility. The authors developed a new irrational aggregate sentiment index (IASI) to examine the issue. The conditional volatility is extracted from the nonlinear univariate models for the market indices and the IASI. The vector autoregression (VAR) is carried out to analyze the relationship between the volatility of irrational aggregate sentiment index and stock market volatility. The authors find a unidirectional causality from sentiment to stock market volatility, and their findings highlight the significance of sentiment in explaining the stock market volatility in India.

Is There Long Memory in Indian Stock Market Returns? An Empirical Search

The issue of long memory, though has important theoretical and practical implications, has not received much attention in India. This article examines the issue of long memory in mean of the stock returns by employing a set of sophisticated time-series tests including a bias reduced log periodogram test of Andrews and Guggenberger. The study used daily values of 29 major indices including sectoral indices traded on the National Stock Exchange and Bombay Stock Exchange from April 2003 to March 2012, which provide insights into relation between composition of indices and long memory. The findings of the study suggest significant presence of long memory in mean returns of the medium- and small-sized indices and weaker evidences for large cap indices. Further, the study identifies a relationship between presence of long memory and market structure variables. The use of linear models in the presence of long memory would result in incorrect inferences, and this calls for investigation of appropriate long memory model to generate profits in Indian stock market.