Gourishankar S. Hiremath

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

Long Memory in Stock Market Volatility

Long memory in variance or volatility refers to a slow hyperbolic decay in autocorrelation functions of the squared or log-squared returns. The conventional volatility models extensively used in empirical analysis do not account for long memory in volatility. This chapter revisits the Indian stock market by using the fractionally integrated generalized autoregressive conditional heteroscedasticity (FIGARCH) model. For empirical modeling, daily values of 14 indices from the National stock exchange (NSE) and Bombay Stock Exchange (BSE) from June 1997 to March 2010 are used. The results of the study confirm the presence of long memory in volatility of index returns. This shows that FIGARCH model better describes the persistence in volatility than the conventional GARCH models. Against the evidence of fractional behavior of volatility in Indian stock market, it is essential to factor the long memory in derivative pricing and value at risk models.

Scaling behaviour of Treasury rates in India

ABSTRACT This study finds that the scaling properties of India’s nominal and real Treasury rates are time varying, as is their multiscaling behaviour. We observe an association between the scaling behaviour of interest rates and the stages of development of the bill market. Interest rate behaviour is influenced by structural reforms, microstructure changes, and improvement in the operational efficiency of the Treasury market. Our findings suggest that monetary policy shocks have a persistent effect, but rates eventually revert to the mean. We show that the adaptive market hypothesis helps to delineate the dynamics of an emerging market undergoing a series of institutional and structural changes.

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.

Random Walk Characteristics of Stock Returns

This chapter studies the behavior of stock returns in India. For this purpose, data from 1997 to 2010 of 14 indices traded on the National stock exchange (NSE) and Bombay stock exchange (BSE) are used and several parametric and non-parametric methods are employed to empirically test the random walk characteristics of stock returns and examine the weak form efficiency of the Indian stock market. The results from parametric tests are mixed and validity of random walk hypothesis (RWH) is suggested only for large cap and high liquid indices traded on the BSE. However, the same is not true in the case of NSE index returns. The non-parametric tests resoundingly reject the null of random walk for the chosen indices. The results broadly suggest non-random walk behavior of stock returns and invalidate the weak form efficiency in case of India. The evidence of dependence in stock returns call for appropriate regulatory and policy changes to ensure further dissemination of information and quick and correct price aggregation in the market.

Mean-Reverting Tendency in Stock Returns

This chapter re-examines the issue of mean-reversion in Indian stock market. Unlike earlier studies, the present one carries out multiple structural breaks tests and uses new and disaggregated data from June 1997 to March 2010. The study finds significant structural breaks in the returns series of all selected indices and thus provides evidence of trend stationary process in the Indian stock returns. The significant structural breaks that are endogenously searched occurred in the years 2000, 2003, 2006, 2007, and 2008 for most of the indices indicating, respectively, rise in international oil prices, global recession, erratic fluctuations in exchange rates, sub-prime crisis and global meltdown. The evidence of structural breaks and mean-reverting tendency indicates the possibility of prediction of returns and thus implies that efficient market hypothesis (EMH) does not hold in Indian context. The study finds that small indices with less liquidity and lower market capitalization are more vulnerable to shocks particularly external events rather than the high liquid and Large cap indices. Further, the sub-sample analysis shows that there was increasing nonrandom walk behavior in stock returns during the structural breaks periods. The results call for appropriate policies and regulatory measures particularly related to external events to improve the efficiency of the market.

Long Memory in Stock Returns: Theory and Evidence

Long memory is a characteristic of a data generating process, in which autocorrelation function decays hyperbolically at a slower rate and the underlying time series realizations display significant temporal dependence at very distant observations. The issue of long memory though has important theoretical and practical implications, has not received due importance in India. The present chapter tests for the presence of long memory in mean of the stock returns by employing a set of semiparametric tests. A comprehensive data sample from June 1997 to March 2010 is used for the analysis. The findings of the study suggest the presence of long memory in mean returns. Furthermore, there are no significant and consistent evidence which could suggest that smaller indices are generally characterized by the long memory process. It implies a potential prediction of future returns over a longer period. The use of linear model in the presence of long memory would result in misleading inferences and this calls for further analysis of long memory forecasting models.