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This paper attempts to examine the presence of herd behavior among the foreign institutional investors (FIIs) when investing in Indian stock market. We also examine the impact of herding in FIIs on stock returns using panel regression approach. We apply the measure suggested by Lakonishok et al. (J Financ Econ 32(1):23-43, 1992), hereafter referred as LSV, to detect the buy-side and the sell-side herding in the Indian stock market. In order to find out intertemporal trading pattern of FIIs, we also use SIAS model. This paper makes use of daily data of 50 stocks of S&P CNX Nifty to achieve the goals. The study also tries to develop a volume-based herding ratio to extend the findings. The results support the evidence of presence of both buy-side and sell-side herding in the Indian stock market. The results based on panel regression approach highlights the destabilizing effect of FIIs in the Indian stock market that may be an issue of concern for the regulators. [ABSTRACT FROM AUTHOR]

This paper tried to investigate the behavior of volatility of Indian stock market keeping in mind, the US subprime crisis. Daily data from 1st April 2007 to 31st July 2010 on S&P CNX Nifty is used for analysis. This paper has used ARCH and GARCH framework for studying behavior of volatility of Indian stock market. The paper has also used threshold GARCH for describing asymmetric properties of stock return volatility. In particular, the objective of the study was to examine the short-term and long-term volatility spillover effects of the US sub-prime crisis on Indian stock market using component GARCH model. The results from the various GARCH models can be used to forecast more accurate volatility which can be used for various purposes like portfolio allocation and option valuation. The results established that stock return volatility of Indian stock market is characterized by persistence, asymmetric properties and permanent component of conditional variance is highly persistent. [ABSTRACT FROM AUTHOR]

The current study tries to empirically investigate the hedging and safe haven characteristics of gold against stock markets, crude and foreign exchange movement for India for the period 1 April 2008–31 March 2019 by taking daily closing prices obtained from www.investing.com (converted to returns). The methodology includes using both traditional OLS and quantile regression approaches by setting up both linear and nonlinear relationships amongst the assets. A separate section in the paper has been devoted which covers the Sub-Prime Crisis of 2008. The results of the study showed that gold acted as a hedge asset with respect to Nifty Stock Index and Exchange Rate but not against Crude when the OLS linear and nonlinear models were employed. Further both linear model and nonlinear OLS regression models ruled out the safe haven characteristics of gold with respect to any of the three assets. However, for quantile regression, hedge characteristics of gold were established at only few quantiles with respect to the same two assets, i.e. Nifty and foreign exchange. With respect to safe haven characteristics of gold under OLS, for both linear as well as nonlinear models, gold did not seem to act as a safe haven, while for quantile models, gold acted as a safe haven only at lower tail(s) for Exchange Rate in the linear model and against Nifty Stock Index for nonlinear model. This shows that quantile regression was able to capture the hedging and safe haven characteristics of gold in a superior manner by doing a comprehensive analysis which was based on eleven different quantiles. Such an analysis is much superior to the traditional OLS which gives only an overall broad assessment of the gold's hedging capacity. Further, the behaviour of gold return as an asset during the sub-period crisis of 2008 was not substantially different from its behaviour during other periods; however, when the yardstick of measurement was changed to return volatility of gold, the behaviour was found to be different from other periods. The asymmetric impact of return on gold with respect to all other assets was also proved in our study. [ABSTRACT FROM AUTHOR]

According to French and Roll (1986), there is greater volatility when the market is open than when it is closed. That is to say, the time series volatility of prices, where each stock is considered individually as a univariate time series, is higher when the market is open than when it is closed. We extend this result in this paper by showing that the cross-sectional analogue of this statement is true as well. Indeed, one of our major findings is that there is greater cross-sectional dispersion in prices when the market is open than when it is closed. [ABSTRACT FROM AUTHOR]

Stock market is an important segment of the financial system of any country as it plays an important role in channelizing savings from deficit sector to surplus sector. These stock markets have always been an area of serious concern for policy makers, economists and researchers. They are often defined as the barometer of any economy because they reflect the change and direction of pressure on the economy. The movement and volatility in stock markets often reflect the direction of any economy. The available literature suggests that since the inception of stock markets researchers are making attempts to establish relationship between change in macroeconomic factors and stock market returns. There are various models developed so far by scholars globally for establishing the relationship between stock returns and these factors such as - discounted cash flows model (DCFM), the capital asset pricing model (CAPM), and the arbitrage-pricing model (APM). But these existing models also suffer from many limitations based on the concept of market equilibrium and the existence of a perfect market. In many developing countries, there are market imperfections and other market characteristics, which make the existing models unsuitable for developing countries like India. From the literature review, the study has seen that asset-pricing theories do not specify the fundamental macroeconomic factors that affect securities prices. The purpose of this paper is to investigate the impact of change in macroeconomic factors on the Indian stock market. The findings of the study conclude that emerging economies like India in long term are more affected by domestic macroeconomic factors than global factors. The main domestic macroeconomic factors affecting the stock market in long run are industrial production; wholesale price index and interest rate. [ABSTRACT FROM AUTHOR]

The objective of this paper is to investigate if an accounting-based fundamental analysis strategy can help investors earn excess returns on a portfolio of high book-to-market companies in India. The strategy we adopt is based on Piotroski (2000) who identified 9 fundamental signals to form a composite score (F̱SCORE) capable of separating out ex-post winners from losers among high book-to-market companies in the US stock market. However, it is not clear whether the results of such a strategy could be directly applied to Indian stock markets,since there is evidence that market efficiency in India is at the most weak form. Also, during the 1990s when trading and investments were mostly domestic, the markets experienced scams like the Harshad Mehta scam. However, of late, India has been among the most favoured investment destinations in the world. Using the F̱SCORE framework from Piotroski (2000) but a different approach to portfolio formation (for practical purposes) we find convincing evidence that a fundamental analysis based investment strategy for high book-to-market companies can separate winners from eventual losers. We show that portfolios with high F̱SCORE (7 to 9) provide excellent returns far superior to market returns and risk-adjusted returns. Portfolios with low F̱SCORE (0 to 3) offer very poor returns and often underperform the markets or required risk-adjusted returns. A value investor could shift distribution of returns rightwards by investing only in high F̱SCORE companies. Shorting low F̱SCORE could further enhance returns. [ABSTRACT FROM AUTHOR]

The paper investigates the relevance of signaling hypothesis in India by examining market reaction and operating performance around distribution of bonus shares for a large sample of firms listed on the Bombay Stock Exchange (BSE). Our results indicate that cumulative abnormal returns of 12.73% exist for the 11-day period surrounding bonus announcements. Consistent with the signaling hypothesis, the abnormal return is positively related to the bonus ratio and negatively related to the size of the firm. Bonus issuers exhibit superior operating performance subsequent to the issue when compared to control firms with similar pre-event performance. The superior performance of bonus issuers is driven by the better profit margin rather than by asset utilization. We link the impact of corporate control mechanism on signaling by documenting a relationship between ownership-structure and post bonus issue operating performance. [ABSTRACT FROM AUTHOR]

Globalisation and capital market reforms should result in improved market efficiency. This paper examines the efficiency of the Indian stock market from 1991-2002, the period which roughly coincides with the period after liberalisation, globalisation and initiation of capital market reforms. Runs tests and serial correlation tests of the BSE 200 index and 158 stocks support the view that the market is moving towards efficiency. However, efficiency increased in the period following reforms, but decreased slightly in the subsequent period. Volatility also decreased after the first few years and subsequently increased. This indicates that there is need for vigilance as the benefits of globalisation and reforms can be diluted by inefficiency and volatility due to domestic and international events and market manipulation. Also, maximum departure from normality and efficiency was observed with daily data and minimum with monthly returns. This should be kept in mind when interpreting and comparing results from studies using varying data intervals. [ABSTRACT FROM AUTHOR]

The temporal relationship between the commodities market and the stock market has a lot of implications for not only the participants of the markets but also for the policy makers and the producers of the commodities and, in the case of developing nations, for the economy as a whole. This relationship may be studied using various methods and by identifying lead - lag relationship between the values of representative indices of the markets. In this paper, the dynamics of such information transfer among the commodities spot, the commodities derivatives, the stock and the stock derivatives markets in India are studied using the information theoretic concept of entropy, which captures non-linear dynamic relationship also. [ABSTRACT FROM AUTHOR]

Volatility forecasting is an important area of research in financial markets and lot of effort has been expended in improving volatility models since better forecasts translates into better pricing of options and better risk management. In this direction, this paper attempts to evaluate the ability of ten different statistical and econometric volatility forecasting models in the context of Indian stock and forex markets. These competing models are evaluated on the basis of two categories of evaluation measures — symmetric and asymmetric error statistics. Based on an out-of-sample forecasts and using a majority of evaluation measures we find that GARCH (4, 1) and EWMA methods will lead to better volatility forecasts in the Indian stock market and GARCH (5, 1) will achieve the same in the forex market. The same models perform better on the basis of asymmetric error statistics also. [ABSTRACT FROM AUTHOR]

This paper uses a quality control approach to study the volatility of common stock in India at the market level and devises a trading behaviour at BSE. It addresses an important question, namely, ‘how have the returns in the Indian stock market behaved, following financial liberalisation’? Considering ‘volatility’ an important indicator of stock market efficiency and development, the average level of volatility is measured for the period 1980 to 2003. The data sample period, from Jan. 1, 1980 to Dec. 31, 2003, covers a wide range of political and economic events that may have influenced the economy and, hence, the stock market. Estimates of the standard deviation of monthly return in a year, daily return in a year and daily return in a month are made to have a complete idea of the level (size) and nature of volatility. Further, we have tried to study acceptable limits of volatility that may be embedded in the decision making of investors, depending on the type of investors. [ABSTRACT FROM AUTHOR]

The information theoretic concept of entropy is a useful tool in studying price manipulation in stock markest, Sample entropy values computed for the price data of a scrip, for various trading days in the period during which the scrip is reported to be subject to price manipulation, prove to be potential evidence for manipulation of the scrip's price. An attempt is made in this paper to select appropriate values for the parameters used for computation of sample entropy of a short time series of stack prices. [ABSTRACT FROM AUTHOR]

The present paper is an endeavor to investigate seasonal anomalies, if any, existing in stock returns in developed and developing countries. The former is represented by the US and the later by the Indian stock market. The daily closing prices of two indices . S&P CNX Nifty and S&P 500 have been used in order to comment on seasonality in the two markets under investigation. The reference period ranges from January 1998 to August 2005, which is further broken into two sets- January 1998 to December 2001 and January 2002 to August 2005. The study examines five types of anomalies, namely, turn of the month effect, semi-monthly effect, monthly effect, Monday effect and Friday effect. The findings of this study indicate that none of the above anomalies exist in the US market and thus this market can be considered as informationally efficient. On the other hand, the Indian stock market reveals turn of the month effect as well as semi-monthly effect but the day effect is not found. [ABSTRACT FROM AUTHOR]

Liberalization of financial markets in emerging economies usually leads to an increase in the foreign ownership of the host country's stocks. Heavy investment of these foreign investors may have deep impact on host country's stock market. The motivation for this study is to understand the investment pattern of foreign institutional investors (FIIs) and their trading behavior, and its impact on the stock market. The present study is an attempt to evaluate the investment pattern of FIIs' investment and its relation to the stock market return in the Indian stock market. Daily data from January 2003 to June 2014 has been collected and analyzed with vector auto regression and multivariate regression models. The results of the study suggest the prevalence of unintentional herding among FIIs that creates short term volatility in the Indian stock market. FIIs' herding tendency is more intense on the buy-side rather than the sell side. Although the impact of FIIs' herding creates short-term volatility, it may still impede the price efficiency of the stock market. [ABSTRACT FROM AUTHOR]

This study examines the asymmetric relationship between India volatility index (India VIX) and stock market returns, and demonstrates that Nifty returns are negatively related to the changes in India VIX levels, but in case of high upward movements in the market, the returns on the two indices tend to move independently. When the market takes sharp downward turn, the relationship is not as significant for higher quantiles. This property of India VIX makes it a strong candidate for risk management tool whereby derivative products based on the volatility index can be used as a tool for portfolio insurance against worst declines. We also find that India VIX captures stock market volatility better than traditional measures of volatility including ARCH/GARCH class of models. Finally, we test whether changes in India VIX can be used as a signal for switching portfolios. Our analysis of timing strategy based on change in India VIX exhibits that switching to large-cap (mid-cap) portfolio when India VIX increases (decreases) by a certain percentage point can be useful for maintaining positive returns on a portfolio. [ABSTRACT FROM AUTHOR]

Indian stock market was functioning with Accounting Period settlement cycle till December 31, 2001. But as per the recommendation of G-30 which was a group to determine the best international practices for securities clearing and settlements, Indian stock market has adopted T+2 rolling settlement cycle on April 1, 2003. Difference of settlement and clearing cycles of different stock exchanges might lead to the day of the week anomaly. Day anomaly in return and volatility of stock market was found to be affected by settlement cycle, and it changes over the period of time. Therefore, present study tries to investigate the effect of introduction of T+2 settlement cycle on day of the week anomaly in return and volatility of Indian stock market. Study analyzes daily closing price data of Sensex and Nifty over the period January 2, 1991 to January 31, 2013 covering 5,763 samples. Study computes descriptive statistics of each week days for both subperiods as well as for complete sample period. It also applies GARCH (1, 1) model for investigating the presence of day of the week effect in both return and volatility of Indian stock market. Empirical result reveals that before introduction of T+2 settlement, returns of Monday and Thursday were negative, while after the introduction of T+2 settlement, returns of all days are positive. By applying GARCH model, this study concludes that after the introduction of T+2 settlement, day of the week effect exists only in return of Indian stock market, but it does not exist in volatility of Indian stock market. [ABSTRACT FROM AUTHOR]

Empirical literature has documented that there does not exist scope for arbitrage profit for the cross-listed ADRs of developed countries (Foerster and Karolyi, 1999). Whereas, even after the introduction of twoway fungibility in 2002, almost all Indian ADRs trade at high premium levels - above the transaction cost band indicating scope for arbitrage profit (Majumdar,2007). However, that does not imply that the Indian ADRs and domestic markets are perfectly segmented and no conversion / re-conversion takes place between ADRs and the domestic stocks. The existence of arbitrage has been identified by practitioners (e.g. fund managers in US) long ago (Knauk 2007). Against this backdrop, we study about 5 years of daily data on opening and closing prices of 9 Indian ADRs. Multiple Regression and VECM are used to examine the following: Movements in which market causes the change in ADRs premium levels? How liquidity, trading volume, volatility and turnover in both the markets influence the change in ADRs premium levels? Is there any structural break? If yes, why? Whether the 'headroom' clause is solely responsible for the existence of premia? What are the transaction cost bands for Indian ADRs? Whether FII trading in the domestic market has any influence on the premium levels of the ADRs? Our initial findings suggest the influence of US market is more on ADRs returns than Indian market. The premium-levels of the Indian ADRs change over time. The changes are in tandem with the changing levels of market indices. Inverse relationship exists between domestic market turnover and ADRs premiums. There are evidences of structural breaks in the level of ADRs premiums. [ABSTRACT FROM AUTHOR]

Weak form efficiency hypothesis (EMH) stipulates that asset prices fully reflect information contained in past stock prices. The present study documents extensive evidence on price behavior in the Indian stock markets. One of the striking features of the results is that runs analysis too exuberate weak form efficiency further and the instances of return drift noted earlier have disappeared. On the whole, the results signify that trading strategies based on historic prices cannot be relied for abnormal gains consistently, except when these coincide with underlying drifts in the stock price movements. [ABSTRACT FROM AUTHOR]

This study investigates the effect of shifting of shares from one group to another on share prices and market liquidity on the Bombay Stock Exchange. The study uses an event study to analyse share price changes and liquidity around announcement and actual date of switching. The overall results suggest weak evidence of positive reaction of the market to the up-switch of shares from Group B1 to Group A. However, there is a negative reaction in case of up-switch from Group B2 to Group B1. In case of down-switch from Group A to Group B1 and from Group B1 to Group B2, the study found that the market does not respond to the announcement of the down switch but incorporates such information at the time of actual switch. The study also reveals a sharp fall in liquidity after the date of announcement for both the up-switched and the down-switched firms but this decline is relatively subdued after the date of actual switch. [ABSTRACT FROM AUTHOR]

Using the (1,1) variant of the Generalised Auto Regressive Coefficient of Heteroscedasticity (GARCH 1,1) the study shows that daily spot market volatility in India has marginally declined since the introduction of futures trading in India, The study also shows a simultaneously significant improvement in the information coefficient 'α' and reduction in 'β', the persistence coefficient that we forward as case in the growing efficiency of the Indian stock market. The study seeks to break new ground by examining the expiration- day effect of futures trading on spot market volatility and contends that contrary to experience elsewhere, there is a significant, albeit small, decline in daily volatility on expiration day. [ABSTRACT FROM AUTHOR]