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This study is intended to investigate the volatility patterns in Bombay Stock Exchange Limited Sensitivity Index (BSE Sensex) based on time series data collected for 10 years period of time. To reach out the predefined objectives of the study, the authors have employed generalized autoregressive conditional heteroscedastic models. The study revealed that the presence of heteroscedasticiy is found in BSE Sensex. Further, the model produced highly accurate results when the researchers compared the estimated results from actual. Furthermore, the volatility of BSE Sensex has shown the features of clustering and significant time varying. Moreover, the model has indicated that there is a positive correlation between daily stock returns and the BSE Sensex volatility.

The study examines the cross-sectional and asymmetric relationship of investor sentiment with the stock returns and volatility in India.

The investor sentiment is captured using a market-based measure Market Mood Index (MMI) and a survey-based measure Consumer Sentiment Index (CSI). The asymmetric effect of the relationship is examined using quantile causality approach and cross-sectional effect is examined by considering indices such as the BSE Sensex, and the various size indices such as BSE Large cap, BSE Mid cap and BSE Small cap.

The result of the study found that investor sentiment (MMI) cause stock returns at extreme quantiles. Lower sentiment induces fear-induced selling, thereby lowers the returns and high sentiment is followed by lower future returns as market reverts to fundamentals. On the other hand, bullish shifts in sentiment lower the volatility. There exists a positive feedback effect of stock return and volatility in the formation of investor sentiment.

The study captures both asymmetric and cross-sectional relationship of investor sentiment and stock market in an emerging economy, India. The study uses a novel data set (i.e.) MMI which captures the sentiment based on market indicators and are widely disseminated to the public.

The present study seeks to investigate the relative edge between the market microstructure of the two leading stock exchanges of the Indian capital market, that is BSE and NSE with a focus on analysing their trading mechanism, efficiency, liquidity and volatility.

We analyse the microstructure of BSE and NSE on the basis of: (1) trading mechanism – ownership structure, listing of securities, trading system and settlement and clearing process; (2) information efficiency using unit root test, serial correlation, runs test, variance ratio and the ARIMA model; (3) liquidity using trading statistics no. of listed Companies, market capitalisation, no. of trades etc. and (4) volatility using standard deviation and GARCH(1,1) model.

A comprehensive scrutiny on microstructure of BSE and NSE makes it evident that the two leading stock exchanges of India are mostly similar and leave no scope to choose between them. Both the exchanges are demutualised corporate entities with a fully automated trading system in an order-driven market, informationally inefficient as evidenced by the predictability of returns, have shown tremendously growing trading statistics and by and large a declining trend in volatility over the years.

Understanding the components of the microstructure black-box will provide the regulatory bodies with an intellectual framework to strengthen the market architecture. Both the exchanges will get aware of the dynamics of trading, can grow to be more competitive and attract more firms for listing and investors for trading of securities. Also, investors, portfolio managers and equity analysts will be able to make better investment strategies by understanding how the market works.

Research in the area of market microstructure has been severely neglected, especially in the context of the Indian market. India is the world's fastest growing economies and we have witnessed tremendous reforms in the capital market. The past two and a half decades have brought about several innovations via demutualisation, screen-based trading, emergence of clearing corporations, innovative financial products and intense use of IT in the Indian stock market. A spurt of reforms and the emerging environment make it crucial to deeply analyse the market structure and design of two premier stock exchanges of India – BSE and NSE.

Despite volumes of research on the efficient market hypothesis (EMH) over the last six decades, the results are inconclusive as some studies supported the hypothesis, and some studies rejected it. The study aims to examine the market efficiency of the Indian stock market.

For analysis, nine Bombay Stock Exchange (BSE) broad market indices were selected covering the study period from 01 January 2011 to 31 December 2020. The data collected for this study are daily open, high, low and closing prices of selected indices. The tools used in this study are: (1) unit root test to check the stationarity of time series, (2) descriptive statistics, (3) autocorrelation and (4) runs test.

The empirical findings of the study reveal that BSE broad market indices do not follow a random walk and Indian stock market is as weak-form inefficient.

The findings from this study provide several avenues for future research. One of the research implications is that anomalies in the statistical results by different academicians in the finance area need to be explained by future researchers.

Investment companies need to understand that extraordinary skills are required to beat the market to make abnormal returns. In an inefficient market where securities do not reflect the complete available information, it is challenging for the investment brokers to convince the customers about the portfolios they recommend to the public that the rate of return would be more than expected.

As economic growth is related to the growth in the financial sector, developing countries like India depend on the accuracy of the information. In the presence of asymmetric information, the fluctuations in the stock market would have serious harmful consequences on the economy.

Amid several controversies surrounding the EMH testing, this study is a modest attempt to provide evidence that the Indian stock market is in weak-form inefficient. However, it is essential to link investors' behaviour and trends observed in the financial sector to fully understand the implications of EMH.

The global financial crisis of 2008 emphasized the need for monetary policy authorities to have a more comprehensive view of the conditions prevailing in the economy before deciding their policy stance. The purpose of this paper is to outline the construction of a financial conditions index (FCI) and investigate the possible co-integrating relationship between the economic growth and FCI.

The study employs the PCA methodology, with appropriate augmentations to handle the unbalanced panel data-sets and constructs a FCI for India. It tests the growth-predicting power of FCI by applying the auto regressive distributed lags approach to co-integration and verifies if the FCI is co-integrated with real GDP growth. It also discusses construction of a financial development index (FDI) which tracks the financial markets through M3, market capitalization and credit amount to residents.

The constructed FCI has a quarterly frequency and is available starting 1998q2. The long-run coefficient of FCI while predicting the real GDP growth is significant at 10 percent. The results confirm that a more-broader index FCI outperforms a narrower index FDI in growth prediction.

By showing that FCI is a better growth predictor than FDI, the study establishes the importance of including the foreign exchange markets, bond markets and stock markets while summarizing the conditions in the economy. The authors hope that the FCI would be helpful to the monetary authorities in their policy decisions.

The paper adds to the few existing studies studies dealing with FCI for Indian economy and constructs a more comprehensive index which tracks multiple markets simultaneously. It also fills the gap in literature by evaluating the correlating relationship between FCI and economic growth.

This paper aims to identify various macroeconomic variables that affect the stock market performance of developed and emerging economies. It also investigates the effect of these factors on the stock markets of both economies. The impact of these variables on broad market indices and sectoral indices is investigated and compared too.

The publications for the study were retrieved from databases such as Emerald Insight, EBSCO, ScienceDirect and JSTOR using the keywords “Macroeconomic variables” and “Stock market” or “Stock market performance.” The result demonstrated a growing corpus of scholarly work in the domain of stock market. The study was carried out separately for each macroeconomic indicator. Given a large number of articles under consideration, the authors began by reading the titles and abstracts of all publications to identify those that were relevant. The papers are evaluated in Excel and the articles for review range from 1972 to 2021.

The authors found that gross domestic product (GDP), FDI (Foreign Direct Investment) and FII (Foreign Institutional Investment) have a positive effect on both emerging and developed economies’ stock market while gold price has a negative effect. Interest rates had a negative impact on both economies except for a few developing countries. The relationship with oil prices was positive for oil exporting countries while negative for oil importing countries. Inflation, money supply and GDP are the macroeconomic variables that have the same effect on sectoral indices as they do on broad market indices. The impact was sector-specific for the remaining variables.

This paper gives an overview of relation and effect covering variety of macroeconomic variables and stock market indices. Still, there is a scope for further research to analyze the effect on thematic, strategy and sectoral indices. A longer time horizon with new variables, such as bank deposit growth rate, nonperforming assets of banks, consumer confidence index and investor sentiment, can be studied using high-frequency data. This research may help stakeholders adopt and manage their policies during a crisis or economic slump.

This study will assist investors, researchers and educators in the fields of economics and finance in understanding how macroeconomic factors affect the stock market. Furthermore, this study can guide in portfolio diversification strategy across multiple sectors by examining the impact of macroeconomic factors specific to sectoral indices. This paper provides insight into society and researchers since it integrates a number of macroeconomic variables and their interaction with the stock market. It may also help pension funds and mutual fund firms to hedge their funds and allocate equity portfolios.

With respect to India, this study looked at new macroeconomic variables and sectors. It contrasted the impact of these variables in developed and developing economies. The effect of broad and sectoral stock indexes was also investigated and compared. The authors examined how these variables responded during crisis and economic downturns by using articles from a longer time frame. This research also looked into how changing the frequency of data for the variables altered stock performance. This paper emphasized the need for more research into thematic, strategy and broad market indices, such as small-cap and mid-cap indices.

This study investigates the effects of the COVID-19 outbreak on daily stock returns for the six major affected WHO Regions, namely: Africa, Americas, Eastern Mediterranean, Europe, South-East Asia and Western Pacific.

This study uses an event study method and panel-data regression models to examine the effect of the daily increase in the number of COVID-19 confirmed cases on daily stock returns from 1 March to 1 August 2020 for the leading stock market in major affected countries in the WHO regions.

The results reveal an adverse impact of the daily increasing number of COVID-19 cases on stock returns and stock markets fell quickly in response to the pandemic. The findings also suggest that negative market reaction was strong during the early stage of the outbreak between the 26th and 35th days after the initial confirmed cases. We further find that stock markets in the Western Pacific region experienced more negative abnormal returns as compared to other regions. The results also confirm that feelings of fear among investors turned out to be a mediator and a transmission channel for the effect of COVID-19 outbreak on the stock markets.

This study contributes to financial literature in two ways. First, we contribute to existing literature that has examined the effect of various catastrophes and crises on the stock markets Second, we contribute to the recent emerging literature that examines the impact of COVID-19 on financial markets.

The study may have implications for policymakers to deal with this outbreak without triggering uncertainty in stock markets and reassure investors' confidence. The study may also be of interest to investors, managers, financial analysts by revealing how the stock markets quickly respond to outbreaks.

This study is the first study to examine the impact of the COVID-19 outbreak on the leading stock markets of the WHO regions.

The purpose of this study is to determine and compare the performance of small and medium enterprises (SME) and manufacturing company stock portfolios in the Indonesian, Chinese and Indian capital markets by the Sharpe Index and the significance of differences in average performance in the capital market.

This is comparative research that compared the performances of SME and manufacturing company stock portfolios in Indonesian, Chinese and Indian capital markets. The hypothesis examination of comparative test used one-way ANOVA technique on the performance of SME and manufacturing company stock portfolios in Indonesian, Chinese and Indian capital markets. One-way ANOVA test was used in the analysis to test the average difference of performance indices of SME and manufacturing company stock portfolios is in Indonesian, Chinese and Indian capital markets.

The performance of SME and manufacturing company stock portfolios in Indonesian capital market was not better than the performances of IHSG and LQ45 Index, the performance of SME and manufacturing company stock portfolios in Chinese capital market (SZSE) was better than the performance of Shenzhen Composite Index and the performance of Shenzhen A-Share Stock Price Index. The comparison of the performances of SME and manufacturing company stock portfolios in Indonesian, Chinese and Indian capital markets showed that the performance of SME and manufacturing company stock portfolios in Chinese capital market was the best and the performance of SME and manufacturing company stock portfolios in Indonesian capital market was the lowest.

The implication of this study was that SME and manufacturing company stock portfolios had relatively better performances in China and India, so investors should consider investing in SME and manufacturing company stocks. The performance of SME and manufacturing company stock portfolios in Indonesia was not able to exceed market and LQ45 portfolios, so the authority in Indonesia financial market should consider developing a special market for SME and manufacturing company to support the development of SME and manufacturing company in Indonesia and solve the problem of lack of funding source for SME and manufacturing company.

The originality of the present study is in the measurement of the performance of SME and manufacturing company stock portfolio by risk-adjusted return which returns per risk unit measured by Sharpe Index as a more beneficial measurement in measuring stock portfolio performance than average return. Comparative study of the stock portfolio performances of small medium enterprises and manufacturing company In Indonesian, Chinese and Indian stock markets, and object studies conducted in Indonesia, China and India.