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The log-linearized present value model (PVM) has been widely used in corporate finance to understand the long-run relationship between share price and dividends using panel data. However, the application of recently established panel econometric approaches that account for slope heterogeneity and cross-section dependency in the recent literature regarding the long-run link between share price and dividends in an Indian setting is limited. This paper re-examines the log-linearized PVM in an Indian setting using newly developed panel unit root, cointegration, and long-run dynamic estimation approaches. This study employed a panel dataset of 60 Bombay Stock Exchange (BSE)-listed Indian firms paying regular dividends for 28 years (1990–2017). The study found unit root, cointegration, and a long-run relationship between dividend and share price series for Indian firms during a 28-year sample period. By demonstrating the presence of a long-run link between share price and dividends, this paper contributes to the literature on the PVM, which is crucial in comprehending market rationality and share price behavior in India. This paper also discusses issues related to panel data, such as cross-section dependency and slope heterogeneity, as well as panel econometric approaches that can be applied in the appropriate settings. [ABSTRACT FROM AUTHOR]

Socially Responsible Indices allow investors to invest in those companies which are deemed to be socially responsible. These indices comprise those constituent companies screened and assessed for environmental, social and governance (ESG) criteria. This paper analyses the weak form of the Efficient Market Hypothesis (EMH) for socially responsible investment indices in India. The authors used the daily closing price of two indices, Carbonex and Greenex, from June 3, 2013, to December 31, 2022. This study conducted Augmented Dickey Fuller, normality, and autocorrelation tests to analyse the randomness of prices and test whether the future price can be predicted using the past price. The weak form theory of the efficient market hypothesis is violated if the returns are not random and dependent on past returns, thereby enabling investors to gain abnormal returns by extrapolating the past data. The research results suggest that the theory of weak form of efficient market hypothesis is valid for Carbonex and Greenex, which are the socially responsible indices of India. It implies that the future movement of returns for socially responsible investment indices in India cannot be predicted from past prices. Therefore, the opportunity to gain abnormal returns is not possible. [ABSTRACT FROM AUTHOR]

Purpose: Equity research in experimental psychology reveals investors' overreactions to bad news events. This study of asymmetric price structures in equity markets investigates whether such behavior predicts stock returns in an emerging market of India. Design/methodology/approach: The research decomposes Bombay Stock Exchange (BSE) Sensex returns into Extremely Positive Returns (EPR) and Extremely Negative Returns (ENR) based on extreme values at first and then tests their lead–lag relations. Findings: The empirical finding is consistent with the existing evidence of asymmetric news effects on stock returns in India. In precise, ENR robustly predicts one-month-ahead EPR for the sample period from January 1991 to March 2020. This predictive power persists even in the presence of popular valuation ratios and business cycle variables. Practical implications: The paper explains the rationale of extreme value modeling in price forecasting. Investors can find additional utility gains from market cycle information while predicting extreme returns in Indian stock market. Originality/value: The paper is unique to understand business cycle effects in extreme return reversals in emerging markets. [ABSTRACT FROM AUTHOR]

Investors step into the stock market with the objective of earning smart returns on their investments. The stock market can help in realising these goals of the investors, however, all investments are subject to risks. The origin of the risk is the uncertainty of realising the desired returns on the investment. This aspect is known as risk of the investment. This paper aims to search the best model to estimate and forecast volatility of Indian and Chinese stock market. The data for the paper is related to the two main indices of Indian Stock Market namely, SENSEX and NIFTY and two indices of Chinese stock market, namely, Shenzhen composite index and Shanghai composite index for the period July 2003 to June 2013. We applied symmetrical as well as asymmetrical GARCH models to the data. Among all the three models i.e. GARCH, EGARCH and TARCH, we found the GARCH (1,1) model as the best model to estimate and forecast the volatility of Chinese stock market for both the daily and weekly return series. For the Indian stock market, the recommended volatility estimation and forecasting model is EGARCH model that captures the leverage effect. We did not find volatility clustering and leverage effect for the monthly return series for both Indian and Chinese stock market. Thus, it is suggested to use the traditional time invariant volatility models for the monthly return series. [ABSTRACT FROM AUTHOR]

Purpose: The Global recession of 2008 was the worst financial crisis in the postworld war economic history that brought in severe disruptions in global investments and capital flows. Not surprisingly, research interest in the field of market integration has considerably increased over the last decade. This paper analyses the dynamics of price integration among Asian financial markets during the postfinancial crisis period. Design/methodology/approach: We employ an Autoregressive Distributed Lag (ARDL) bounds testing approach to cointegration and a Granger Causality/Block Exogeniety test from a Vector Error Correction Model (VECM) on monthly stock index data of five leading Asian economies from April 2009 to March 2020. Findings: The cointegration results could not produce any conclusive evidence of long-run relations between stock markets. There exists weak price convergence among markets, and financial integration is partial and in an imperfect form. Research limitations/implications: Stock price performance in China is closely "coupled" with that in India, but both markets appear to be the short-run predictors of Asian stock returns. The research uses only the benchmark stock indices of the selected economies. Consideration of mid-cap and small-cap segments where foreign investments are significant today can validate the findings further. Practical implications: The asymmetric pattern of price behavior of Asian markets has important implications for the pricing efficiency of national markets and offers arbitrage potentials for global investors to optimize returns through market diversifications on a long-term perspective. The finding definitely will be a great help to investors who are potentially interested in a trading strategy that offers greater returns with limited exposure to market risks. Originality/value: Compared with previous studies, the research uses the most recent data of leading Asian markets and applies the robust method of ARDL Bounds testing approach that allows us to understand better if the economic recoveries and advancement have had an effect on market coupling and stock price transmissions. [ABSTRACT FROM AUTHOR]

Stock market performances has been observed through a good deal of literature out of which it has been found out that the behavior of investors is affected through many parameters exist in the market like occurrence of any sudden event or influence of Individual advice apart from the past behavior of the stock which is called rational information regarding stock performances as per the traditional finance theory. The main aim of this paper is to identify the mediating effect among various types of information available in the market for investors to invest their money into the stock market as a part of different behavioral biases in the Gujarat State, India. Three types of constructs have been derived as a part of exploratory research design for this study by applying exploratory factor analysis (EFA) which are Company History, IPO issues and Location benefit of the company out of the different variable taken for the study. Structural Equation modelling (SEM) techniques have been applied to check the mediating effect among these three constructs. The study has been concluded that Company information is an indirect construct, IPO issue is a dependent construct and Location of the company is a mediating construct which is revealing that there is a significant impact of Company information on the IPO issue done by any corporate in the market. IPO issue can also be affected by the Location of the company which has the mediating effect on it. [ABSTRACT FROM AUTHOR]

This paper employs a combination of unit root tests and fractional integration technique to test for rational bubbles in Bombay Stock Exchange (BSE). It is indicated in the paper that evidence of a unit root in dividend yield is consistent with presence of rational bubbles in the stock prices. The results in the paper strongly support evidence of rational bubbles in BSE. Moreover, the paper also investigates the degree of conditional volatility persistence to show persistence of shocks to stock price volatility is short-termed. [ABSTRACT FROM AUTHOR]

The paper examines the impact of new product announcements on the stock prices of announcing companies of the BSE 500 index. The paper analyzes a sample of 383 new product announcements for a period of 11 years. The authors have used the reliable CMIE's Prowess Database to collect the information regarding new product launches, announcements, approvals, unveils, etc. Traditional event study methodology is used in order to measure the abnormal stock market returns. The study found that there is a significant impact of the announcement of new products on the share prices and abnormal returns are generated on the event day. Also, t-test discloses that there is a significant difference between the pre and the post abnormal returns further emphasizing that there is an impact of the event on the abnormal returns. The means of the pre and post period reveals that the returns are positive for the pre period and negative for the post period. This emphasizes the fact that information is leaked to the market prior to the announcement and hence, abnormal returns are generated prior to the event day rather than the post abnormal return period. Therefore, the study concludes that new product announcements hold important information to the Indian stock market during the event and abnormal returns are generated on the event day and also, the returns are generated higher in the pre period than the post period of the event window. [ABSTRACT FROM AUTHOR]

Stock market trends forecast is one of the most current topics and a significant research challenge due to its dynamic and unstable nature. The stock data is usually non-stationary, and attributes are non-correlative to each other. Several traditional Stock Technical Indicators (STIs) may incorrectly predict the stock market trends. To study the stock market characteristics using STIs and make efficient trading decisions, a robust model is built. This paper aims to build up an Evolutionary Deep Learning Model (EDLM) to identify stock trends’ prices by using STIs. The proposed model has implemented the Deep Learning (DL) model to establish the concept of Correlation-Tensor. The analysis of the dataset of three most popular banking organizations obtained from the live stock market based on the National Stock exchange (NSE) – India, a Long Short Term Memory (LSTM) is used. The datasets encompassed the trading days from the 17th of Nov 2008 to the 15th of Nov 2018. This work also conducted exhaustive experiments to study the correlation of various STIs with stock price trends. The model built with an EDLM has shown significant improvements over two benchmark ML models and a deep learning one. The proposed model aids investors in making profitable investment decisions as it presents trend-based forecasting and has achieved a prediction accuracy of 63.59%, 56.25%, and 57.95% on the datasets of HDFC, Yes Bank, and SBI, respectively. Results indicate that the proposed EDLA with a combination of STIs can often provide improved results than the other state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

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Dividend policy contributes significantly to the company's performance as well as its survival and growth. Formulation of such policy is a challenging task to the firm as it conveys positive signal about the company to its investors. In India, the impact of dividend announcement has been examined extensively, but its impact on the service sector companies is relatively unobserved. The purpose of this study is to conduct a detailed and systematic review of dividend announcement and analyze the effect of dividend announcement on stock prices of the service providing companies listed on National Stock Exchange of India. The study employs the event study methodology with an event window of 31 days. The study is carried out for a period ranging from January 1, 2018 to December 31, 2019. The findings of the study revealed that the stock prices react towards the dividend announcement event of the companies and thus there is a significant impact of dividend announcement on the stock prices during the event window which led to generation of abnormal returns. [ABSTRACT FROM AUTHOR]

Microstructure is price discovery mechanism under set of the rules. It studies frictions in trading process and tries to sort out the problem to make market smooth and orderly. Indian stock market has been continuously under reform to make strong market microstructure. Electronic trading has reduced frictions in stock market but still some areas require improvement. This paper has been tried to find out the critical areas in Indian stock market microstructure and its impact on the trading process. [ABSTRACT FROM AUTHOR]

This paper is an attempt to examine the presence of herd behavior in the stock market of India, which is one of the emerging economies of the world. The study uses the measures suggested by Christie and Huang (1995) and Chang et al. (2000) on National Stock Exchange data. Empirical results based on daily and monthly data indicate that during periods of extreme price movements, equity return dispersions tend to increase rather than decrease, thus providing evidence against the presence of herding in the Indian stock market for the years 2000-2012. Owing to reforms in Indian stock market and the increased presence of institutional players, investors' behavior seems to be more rational, facilitating the application of rational pricing models in the Indian stock markets. [ABSTRACT FROM AUTHOR]

This paper examines the effects of size, value and momentum on the cross-sectional relation between expected returns and risk in the Indian stock market. We find that the conditional Carhart four-factor model empirically describes the variation of cross-section of return better than the unconditional model. When size, book-to-market and momentum effects are controlled in the conditional model, the positive relation of market beta, book-to-market and momentum with expected returns remains economically and statistically significant. However, this evidence is found to be subject to characteristics of test portfolios. The expected returns are sensitive to changes in predictive macroeconomic variables. [ABSTRACT FROM AUTHOR]

This paper attempts to explore the possible impact of corporate announcement such as dividend on stock prices in Indian stock market. To find the empirical evidences of dividend announcement 20 listed companies were selected based on the market trading volumes and had announced in over the period January 2015 through December 2015.A standard event study methodology is adopted in this paper surrounding sixty days of the announcement dates. Abnormal Returns of the stock are calculated by using Capital Asset Pricing Model (CAPM). The results of t-test for means have shown that there are significant differences on share prices after announcement except Bank of Baroda. The Average Abnormal Returns (AAR) and Cumulative Average Abnormal Return (CAAR) of the event days are not equal to zero, though investors do not gain significant returns in pre or announcement day but gain in post announcement period as there are positive incidences of abnormal return noticed around two days post announcement for most of the companies having positive dividend announcement and a few companies have post negative returns. An investor can take the marginal returns by investing in companies with dividend event but can't expect speculative returns. [ABSTRACT FROM AUTHOR]

This paper presents an empirical analysis of the relationship between trading volume and stock return volatility in the Indian stock market. The initial analysis focus upon the volume-price change relationship. The relationship between price change and trading volume, irrespective of the direction of the price change, is significant across three alternative measures of daily trading volume for the aggregate market and individual stocks. Furthermore, evidence is found supporting the hypothesis that the volume-price change slope for negative returns is smaller than the slope for positive returns, thereby supporting an asymmetric relationship. Trading volume is then examined in the context of conditional volatility using a GARCH framework. The findings show a reduction in the significance and magnitude of the conditional variance equation coefficients, and a reduction in the persistence of variance when trading volume is added as an exogenous variable. Hence, there is prima facie evidence that if trading volume proxies for the rate of information arrival, then ARCH effects and much of the persistence in variance can be explained. [ABSTRACT FROM AUTHOR]

The central goal of this paper is to study the small sample properties of non-parametric multiple variance ratio tests and the runs test and to apply suitable tests on the daily data of the stock prices of Indian sectoral indices to study their martingale behavior. We have also used moving a subsample approach to examine the dynamic behavior of the test statistics. This helps us to identify the sensitivity of results to a particular sample period and to obtain inferential findings robust to possible structural changes and presence of influential outliers. Joint sign test turns out to be better than other tests for sample size less than and equal to 1000. Our results provide evidence against the weak-form efficiency of all the sectoral indices, except for CNX IT. According to our analysis based on the moving sub-sample approach, except for BANK NIFTY and CNX INFRA, all the other indices have become more efficient after the sub-prime crisis. [ABSTRACT FROM AUTHOR]

The present paper examines the relation between commodity market and capital market using 22 years monthly data for the period April, 1991 to March, 2013. Gold price represents commodity market and BSE Sensex is taken as proxy for capital market in India. The unit root test clarified that gold price and stock price were found to be integrated of order one using Augmented Dicky-Fuller test for unit root. The Granger causality test confirmed the presence of unidirectional causality which runs from gold price to stock price. It is established from the Johansen cointegration test that gold price and stock price are cointegrated, indicating an existence of long run equilibrium relationship between the two. VECM and wald test finally confirmed that there is a bi-directional relationship in the long-run between the two variables. We find a negative but low correlation between gold and sensex. Based on these results, we incline to suggest the favourable property of gold as an investment asset for the Indian emerging market. At least, gold provides a diversification and safe haven benefit to investors in the Indian market. The domestic Indian gold market tends to have resistance to heightened risk in the stock market as it preserves its low negative relation with stock market variations regardless of the market conditions. [ABSTRACT FROM AUTHOR]

During the past decades, the efficient market hypothesis (EMH) has been at the heart of the debate in the financial literature because of its crucial implications. Fama (1970) defined a market as being efficient if prices fully reflect all available information, and suggested three models for testing market efficiency: the Fair Game model, the Submartingale model, and the Random Walk model. Also, according to Fama (1970), the market is said to be efficient at three levels-weak form, semi strong form and strong form. In emerging stock markets, most empirical studies have focused on the weak form, the lowest level of EMH because if the evidence fails to support the weak-form of market efficiency, it is not necessary to examine the EMH at the stricter levels of semi-strong and strong form (Wong and Kwong, 1984).This paper examines the weak form of market efficiency of Indian stock market i.e. National Stock Exchange (NSE) in the recent years from April 1, 1997 to March 31, 2010 with EMH. The study has tested weak form of efficiency using Runs test based on the secondary data i.e. the daily stock prices of companies involved in the formation of NIFTY. The evidences from the test support the weak form of efficiency of NSE. The findings reveal that the stock market has turned efficient to the extent that the stock prices fully reflect all information of the past. [ABSTRACT FROM AUTHOR]

Macroeconomic stability is crucial not only for economic growth but also for the living standards and investments in a market economy. The macroeconomic variables like crude oil price, gold price, exchange rate, inflation and stock returns are highly correlated to each other and are highly volatile, and the volatility in one market spills over to other markets. This paper analyses the dynamic causality between crude oil price, exchange rate and BSE Sensex and their volatilities in India. The daily data on macro variables for 14 years between January 2006 to March 2019 is used in the GARCH estimation of causal effects of volatility spillovers. The GARCH estimates show that the volatility and volatility spillover of one market cause volatility and volatility spillovers in other markets in India. The crude oil price and exchange rate volatility and volatility spillovers cause volatility in BSE Sensex. The volatility in BSE Sensex is highly overdone by internal shocks of the stock market itself. [ABSTRACT FROM AUTHOR]

This paper aims to identify the critical corporate fundamental factors that have a significant effect on stock price movements as mirrored by two leading stock indices, Sensex and Nifty, which in turn have an influence on the entire market movement. [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]

In this paper, we study the relevance of stock options open interest in conveying information about the future price movements in the underlying stocks. This investigation has been carried out by using daily closing data of 26 stocks in the National Stock Exchange (NSE) derivatives segment for the period May 2007 to October 2008. The result proves that stock options open interest does contain valuable information about future price movements in the underlying stocks. [ABSTRACT FROM AUTHOR]

This paper studies the impact of market opening to FIIs, on Indian stock market behavior. India announced its policy regarding the opening of stock market to FIIs for investment in equity and related instruments on 14th September 1992. Using stock market data related to Bombay Stock Exchange, for both before and after the FIIs policy announcement day. An empirical examination has been conducted to assess the impact of the market opening on the returns and volatility of stock return. We found that while there is no significant changes in the Indian stock market average returns, volatility is significantly reduced after India unlocked its stock market to foreign investors. [ABSTRACT FROM AUTHOR]

Purpose — The paper aims to study the impact of the introduction of Nifty index futures on the volatility of the Indian spot markets by use of econometric models. Design/methodology/approach — The study considered six measures of volatility, the dynamic linear regression model, and the GARCH models to investigate volatility in National Stock Exchange (NSE) Nifty prices both before and after the onset of futures trading. Findings — The GARCH analysis confirmed no structural change after the introduction of futures trading on Nifty, and found that whilst the pre-futures sample was integrated, the post-futures sample was stationary. Spot returns volatility is found to be less important in explaining spot returns after the advent of futures trading in NSE Nifty. Practical implications — The results imply that futures markets serve their prescribed role of improving pricing efficiency and improve the quality of information flowing to spot markets. This will enable investors to prudently structure their strategies investing in both spot and futures markets. Originality/value — This study is an original piece of work towards exploring the impact of the introduction of futures trading on cash market volatility in an emerging economy like India. [ABSTRACT FROM AUTHOR]

Stock splits are a relatively new phenomenon in the Indian context. This paper examines the market effect of stock splits on stock price, return, volatility, and trading volume around the split ex-dates for a sample of stock splits undertaken in the Indian stock market over the period 1999–2005. The traditional view of stock splits as cosmetic transactions that simply divide the same pie into more slices is inconsistent with the significant wealth effect associated with the announcement of a stock split. However, the empirical evidence confirms a negative effect on price and return of stock splits. The overall cumulative abnormal returns after the split are negative. These results suggest that stock splits have induced the market to revise its optimistic valuation about future firm performance, rejecting signaling hypothesis to which splits convey positive information to markets. Hence, stock splits have reduced the wealth of the shareholders. The results also show that presence of a positive effect on volatility and trading volume following the split events, thus suggesting that split events enhance liquidity. [ABSTRACT FROM AUTHOR]

This paper carries out a dynamic analysis of stock pricing in emerging economies, using a cointegration model on panel data, using ‘nested’ procedures with subsets of company groupings and time periods — taking Indian stock markets as the concrete case. It is observed that all classifications of company groupings do not result in similar observations. This helps in developing an approach to panel data estimation for financial markets without using structural equations. At the same time it develops a dynamic asset pricing model for emerging economies using India as a concrete case with net worth, profit, dividend, debt–equity ratio, interest cost and their growths as control variables.Journal of Asset Management (2007) 7, 335–346. doi:10.1057/palgrave.jam.2250041 [ABSTRACT FROM AUTHOR]

Evidence of inefficiencies existing in the Indian Stock Market has once again generated interest in technical analytical methods, which attempt to achieve superior returns based on past price movements. This paper tests and describes the applicability of trading rules in the Indian stock market under the present scenario with a ban on short-selling. It also analyses the effect of transaction costs on the prospective returns for an individual investor and the utility of a percentage band to remove erroneous Whiplash signals. The paper further explores and hypothesises that individual investors should be able to outsmart the market post-transaction-costs using longer moving averages which represent long-term market cycle trends, since these will involve low transaction costs but such gains are likely to be achieved over long cycle times since longer moving averages capture long cycle trends. [ABSTRACT FROM AUTHOR]

This research paper discusses the growth of primary market in India. The study is based on secondary data result in number of amount wise issues in the year, issue price and to measures the growth of Initial Public Offering in different sector . When a company issues shares to the public through a prospects it is popularly known as an IPO. Credit of shares allotted in IPO's can be affected in the investors Demat account in Demat form directly. A corporate may raise capital in the primary market by way of an Initial Public offer, rights issue or private placement. An initial public offer (IPO) is the selling of securities to the public in the primary market. It is the largest source of funds with or indefinite maturity for the company. The IPO's is when an unlisted company makes either a fresh issue of securities or offer sales of its existing securities or both to the first time to the public. This paves way for listing of trading of the issuer's securities. The primary market is the arena for raising funds from the primary source of savings, (i.e.) investors. A market where the issuers access the prospective investor directly for funds required by them generally either for expansion or meeting the working capital needs. This process is called disinter mediation where the funds flow directly from the investors to issue. So this study helps to know about the growth of amount issued in various sectors and the data were collected using through website that are listed in NSE. Based on the analytical research the findings and suggestion were conducted. [ABSTRACT FROM AUTHOR]

The world had noticed that pandemic and the coexisting economy is very practically identical to the distinguish among wellbeing and abundance at large. India had witnessed the lockdown since 25 March 2020 due to which stock market was badly affected because of Covid-19. This paper has analysed the movement of Indian stock market with large, mid and small cap stocks during Covid-19 pandemic. This study has come across time series analysis using multiple regression analysis and E-garch using data from Jan 30, 2020 to Nov 27, 2020.This study uses the data of Covid-19 related daily confirmed cases, death cases and closing prices of nifty 50 for large cap, midcap 150 for mid cap stocks and small cap 250 for small cap, used lockdown dummy variable and 20 lakh crore also used as other dummy variable for better analysis of the study. The results of the research suggested that Covid-19 confirmed cases are manipulating index performance of the stock. We can witness that the increasing pace of the confirmed cases, the economy caused significant damage, reflected by the Indian economy being decreased due to which the stock exchange experienced fall in nature. [ABSTRACT FROM AUTHOR]

Neural networks are powerful forecasting tools that draw on the most recent developments in artificial intelligence research. They are non-linear models that can be trained to map past and future values of time series data and thereby extract hidden structures and relationships that direct the data. Many studies have shown that artificial neural networks have the capacity to learn the underlying mechanics of stock markets. In fact, artificial neural networks have been widely used for forecasting financial markets. However, such applications to Indian stock markets are scarce. The paper investigates the application of artificial neural networks to the dynamic interrelations between macroeconomic variables i.e. Foreign Exchange rate, Foreign Exchange reserves and Wholesale price index. Multilayer perceptron network is used to build the monthly prices model for CNX Nifty and the network is trained using Error Back Propagation algorithm. It is found that the predictive power of the network model is influenced by the previous values. The study shows that satisfactory results can be achieved when applying neural networks to predict the Indian Stock prices. [ABSTRACT FROM AUTHOR]

The present paper endeavors to empirically investigate the long run equilibrium relationship between the stock market of India, U.S., China, Singapore and Germany with special emphasis on evaluating the influence of U.S. based global financial crisis (2008) on this long run relationship. This exercise is based on the monthly closing data of the stock market indices for all the selected countries. Single equation Engle-Granger co-integration approach has been applied to examine one to one relationship of Indian stock market with the stock markets of other countries. The influence of U.S. financial crisis (2008) has been seen with the help of dummy variables. Apart from single equation analysis, another approach called multivariate approach given by Johansen and Juselius(1988,1991) is employed to study long run relationship among all the stock markets which suggests that co-movements of stock prices among the selected countries has increased after the 2008 financial crisis. [ABSTRACT FROM AUTHOR]

In this paper, we study the effect of overall stock market sentiment in India on sectoral indices and on individual stock prices in terms of co-movement, dependence and volatility transmission along with the magnitude and persistence of the effects. The study uses wavelet decomposition framework for breaking down different financial time series into time-varying components. Quantile Regression, Wavelet Multiple Correlation and Cross-Correlation analysis, and Diebold-Yilmaz spillover analysis are then applied to investigate the nature of dependence, association, and spillover dynamics. For further focus, we have considered different time periods separately to identify the effect of market phases. Interesting results are obtained with respect to persistence of shocks, both across and within time periods. These have implications with respect to understanding market behavior and also perception of sectors and stocks. [ABSTRACT FROM AUTHOR]

This paper aims to study the stock market reaction around buyback announcements made during a 10-year period between 2000-01 and 2009-10 by taking the S&P CNX 500 index companies and dividing the period into normal and active market conditions. Through the standard event study methodology, it also intends to analyze the buyback information impact on stock returns during different conditions and comment on market efficiency in assimilating the information into prices. While evidencing semi-strong form of efficiency during the two periods considered, the study documents the different dosages in the reaction (signaling) of the Indian stock market to buyback announcements in accordance with differing market conditions considered. [ABSTRACT FROM AUTHOR]

We build a cross‐sectional factor model for investors' direct stockholdings and estimate it using data from almost 10 million retail accounts in the Indian stock market. Our model identifies strong investor clienteles for stock characteristics, most notably firm age and share price, and for particular clusters of stock characteristics. These clienteles are intuitively associated with investor attributes such as account age, size, and diversification. Coheld stocks tend to have higher return covariance, inconsistent with simple models of diversification but suggestive that clientele demands influence stock returns. [ABSTRACT FROM AUTHOR]

This paper examines the stock price liquidity chances before and after the bonus and rights issue announcement. Liquidity measured using raw trading volume ratio, relative trading volume ratio and liquidity ratio suggest that raw trading volume and relative trading volume have decreased around bonus and rights announcements, though insignificantly. Market depth, as measured by the liquidity ratio, has significantly decreased after the bonus and rights issue announcement in the Indian stock market. There is evidence of negative and significant decrease in stock price liquidity for bonus and rights issue announcements similar to other issue announcements in US, UK and other emerging economies. The results support cash substitution hypothesis and signaling theory but rejects liquidity hypothesis with respect to bonus and rights issue announcements. [ABSTRACT FROM AUTHOR]

This paper uses Johansen and Juselius (1990) multivariate cointegration technique to explore the long-run relationships between NSE-Nifty share price index and certain other crucial macroeconomic variables, namely, index of industrial production, money supply, interest rate, exchange rate, consumer price index and the US stock price index. Besides, the multivariate Vector Error Correction Model (VECM) was also applied to examine the short-run causal nexus between NSE-Nifty share price index and the selected macroeconomic variables in India. The empirical results reveal that the NSE-Nifty share price index has a significantly positive long-run relationship with money supply, interest rate, index of industrial production, and the US stock market index. Further, there exists a significant negative relationship between the NSE-Nifty share price index and exchange rate in the long run. Further, the empirical results indicate that there is a strong unidirectional causation running from interest rate to NSE stock market return and the US stock market return to NSE stock market return. Other than this, there is significant short-run causality between a few monetary variables like money supply and interest rate, inflation and money supply, and the US stock market and exchange rate. [ABSTRACT FROM AUTHOR]

This paper attempts to enhance the stock selection process by employing value-based investment criteria to select stocks in the Indian stock market. Neural networks are used to identify stocks for the portfolio which are likely to outperform the market, given the fundamental accounting information of stocks. The analysis uses ten financial ratios and employs a backpropagation neural network to select the stocks with the highest predicted returns in the Indian stock market. The BSE 500 index of the Bombay Stock Exchange constitutes the sample, and the study is conducted for the period 1995-2005. The returns obtained from the equally weighted portfolio formed by the stocks selected by neural networks significantly outperform the benchmark index, the BSE Sensex. The analysis also establishes the existence of a value premium in Indian stock market and utility of fundamental characteristics as price predictors. [ABSTRACT FROM AUTHOR]

In this paper, we find that there exists a nonlinear relationship between futures and cash indexes. Within the arbitrage bounds, the change in- basis can affect prices in both markets and a significant feedback relationship between futures and cash markets is noted. Besides, price discovery is not evident in the futures markets due to almost the same speed of information flows in both markets. While outside the arbitrage bounds, the influence of the change in basis on both futures and cash indexes is statistically insignificant and the change in the futures price leads the cash price, thereby indicating notably the function of price discovery in the futures market. As a result, the Bivariate model that allows for dynamic interrelationship between futures mid cash prices is better than the traditional one in revealing both the price discovery of futures and cash indexes and arbitrage behavior within and outside the arbitrage bounds. [ABSTRACT FROM AUTHOR]

The paper aims to present theoretical framework of efficiency of stock markets and test the Indian stock market for weak form efficiency. Statistically, the study shows that Indian stock markets are weak form efficient and price changes follow a random walk. Data for the period 1st April 2005 to 31st march 2007 has been used for Sensex and Nifty. For other BSE indices and individual share prices, data for one year from 1st April 2006 to 31st March 2007 has been used. Though no tests of trading rules have been carried out, statistical independence of price changes does imply that trading rules based on technical analysis can not be used to earn excess risk adjusted returns. Increasing investor interest in emerging markets has motivated a great deal of research aimed at understanding the return risk characteristics of stock prices in these markets. [ABSTRACT FROM AUTHOR]

The purpose of current study is to investigate whether a stock split is still considered a policy that creates value for the underlying company and the rational behind such action for companies listed on the BSE-sensex. The event study methodology of Strong is employed to examine the effect of stock split ex-date on stock prices. This paper examines the effect of stock split on return and liquidity for the stock performing the part of the BSE Sensex around the Ex-date. Empirical evidence suggests that stock splits are associated with positive abnormal return on the day of the stock split Ex-Date as well as on the day following the Ex-date. Thus the result indicates that market registers an increased activity in the stock near the Ex-dates of stock split when it associated with liquidity we can observe a clear trend of measuring liquidity as measured by increased turnover around the event date. [ABSTRACT FROM AUTHOR]

The paper analyzes the varying perceptions of stock price volatility of Indian capital markets along with identifying possible reasons for volatility and measures the degree of volatility. It is evident from the values of co-efficient of variation and standard deviation that the market capitalization of NSE was highly volatile or less consistent when compared to BSE. There was a greater crash in the market prices was on account of Kethan Parekh stock market scam, Coupled with bearish trend in the markets apart from various other factors. Number of companies listed has declined abnormally over a decade and the share of NSE as increased significantly and equaling with that of BSE listed companies. Volatility in number of shares traded daily on NSE and BSE varies between 1.90 to 1.24 and 2.00 to 1.32 respectively. This represents that the volatility rate in BSE is greater than that of NSE. Relevance of the budget on stock price volatility is diminishing every year because of the critical policy decisions are taken on a regular basis by the government. [ABSTRACT FROM AUTHOR]

Purpose — An understanding on the linkages between financial development and economic growth in general and the stock market with economic activity in particular is imperative in emerging economies. The objective of this paper is to find out the causal linkages between stock market and economic activity in India. Design/methodology/approach — The paper applies recently developed Granger non-causality tests by Toda-Yamamota, Dolado and Lutkephol (popularly known as the TYDL model) for an empirical exercise. Findings — The notable finding of the paper is that both the stock price (BSE Sensex) and economic activity (IIP) are integrated of order one, i.e. I(1). The Johansen-Juselius co-integration tests suggest the existence of one co-integrating vector. This rules out spurious relations and suggests the presence of at least one direction of causality. The TYDL model suggests that there is bi-directional causality between stock price and economic activity during the post-liberalization period, implying that a well-developed stock market could enhance economic activity and vice-versa. Research limitations/implications — In the broader framework of financial markets, the presence and role of the stock market is minuscule in the context of India. Despite this, it could play a considerable role in the process of the economic development of the country. However, to analyze the cause and effect relationship between stock market and economic activity, it is essential to analyze the issue in greater detail and depth. The main limitation of the paper is the use of IIP as a proxy for economic activity, which neglects the agricultural sector, being the primary sector in India and also the service sector. This is of course due to the non-availability of GDP data on a monthly basis. Further, a detailed study on the issue could be highly appreciable from the perspective of policy implications. Originality/value — The findings of the paper have some valuable implications. It could give some insight for policy makers about the possible linkages between stock market and the economy. Coming to empirical parts, this is perhaps the first paper in the context of India to apply the TYDL model to examine the relationship between stock price and economic activity. [ABSTRACT FROM AUTHOR]

A stock exchange's efficiency can be measured by its liquidity and price discovery mechanism. An exchange that provides price discovery will have high liquidity. By measuring the speed of stock price adjustment to its intrinsic value with the arrival of new information, we can understand the price discovery process and productive efficiency of a stock exchange. India has 23 stock exchanges, 20 of which have almost become dysfunctional due to negligible trading during the last five years. Measuring productive efficiency of the current active stock exchanges will help to understand the future direction of the Indian stock market. Using the corrected model and a new model proposed in this paper, I found that information adjustment in the Indian market is very slow. Contrary to the developed markets, in the Indian stock market, stock prices overreact before adjusting to their intrinsic values. I also found that market-wide information adjusts faster than firm-specific information. [ABSTRACT FROM AUTHOR]

The study of behaviour of stock prices and information dissemination plays an important role in the development of stock market and to ensure effective allocation of capital to the most productive sectors of economy. It is particularly, more sensitive in the context of Indian Economy being a developing one and there is immense need to boost the economic process by accumulating resources from private sectors. It is well documented in the financial literature that private sector flourishes in the presence of efficient capital market. In this study a rigorous attempt was put forth to find whether the trading activities in the stock markets are satiable to counter the informational impact on share price by different researches and also to further instigate the new folds needed for conducting research in extended manner. There are numerous studies available to address the level of efficiency pertaining to the stock market, though this study is intended to cover the most influential available literature. [ABSTRACT FROM AUTHOR]