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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.

The purpose of this paper is to provide insights into the profitability of momentum strategies in the Indian stock market. This study further evaluates whether the momentum effect is a manifestation of size, value or an illiquidity effect.

Monthly stock return data of 470 BSE listed stocks over the sample period from January 1997 to March 2013 were used to create extreme portfolios (winner and loser). The returns of extreme portfolios were evaluated using t-statistics and a risk-adjusted measure. Further checks were imposed by controlling for other potential sources of risk including size, value and illiquidity.

The study provides support in favor of momentum profitability in the Indian stock market. In contrast to the literature, momentum profitability is driven by winning stocks, and hence, buying past winning stocks generates higher returns than shorting loosing stocks in the Indian stock market. Strong momentum profits were observed even after controlling for size, value and trading volume of stocks. This suggests that the momentum effect in the Indian stock market is not a manifestation of small size effect, value effect or an illiquidity effect.

From the practitioner’s perspective, the study indicates that a momentum-based investment strategy in the short run is still persistent and can generate potential profits in the Indian stock market.

There is little empirical evidence on the momentum profitability, especially in the Indian stock market. The study contributes toward the literature by analyzing the momentum profitability even after controlling for size, value and an illiquidity effect. Some aspects of the momentum effect were observed to be dissimilar from those observed in literature for the USA and other countries. Such findings justify the need for testing the momentum profitability in stock markets other than the USA.

One of the anxieties of stock market investors is whether the markets operate efficiently, independently and with sound fundamentals. This concern is also held by academics and practitioners for quite some time. However, real market situation tends to exhibit a link as is evident from recent market movements across the world. The purpose of this paper is to examine whether the stock markets in the Indian subcontinent have any link with the major stock markets from China, Singapore, America, and Hong Kong.

The paper uses Engle Granger test of cointegration.

The paper finds that the Indian markets are related to some of the markets around the world.

The paper offers insight into the cointegration of Indian stock markets with other leading stock markets.

Many studies have shown that from a theoretical and empirical point of view, downside risk-based measures of risk are better than the traditional ones. Despite academic appeal and practical implications, downside risk has not been thoroughly examined in markets outside developed country markets. Using downside beta as a measure of downside risk, this study examines the relationship between downside beta and stock returns in Indian equity market, an emerging market with unique investor, asset and market characteristics.

This is an empirical study done by using ranked portfolio return analysis and regression analysis methodologies.

The study results show that downside risk, as measured by downside beta, is distinctly priced in the Indian equity market. There is a direct positive relationship between downside beta and contemporaneous realized returns, indicating a premium for downside risk. Downside risk carries a higher weightage than upside potential in the aggregate return of the stock portfolios. Downside beta is a better measure of systematic risk than conventional market beta and downside coskewness.

The empirical results support the adoption of downside beta in practice and provide a case for replacing traditional beta with downside beta in asset pricing applications, trading and investment strategies, and capital allocation decision-making.

This is one of the first in-depth studies examining downside beta in Indian equity markets using a broad sample of individual stock returns covering a wide time range of 22 years. To the best of our knowledge, this study is the first one to compare downside beta and downside coskewness using individual stock data from the Indian equity market.

The purpose of this paper is to investigate the linkages between Indian stock markets with other Asian stock markets namely, Hong Kong, Indonesia, Japan, South Korea, Malaysia, Taiwan and China. Such a study is particularly important because if the level of integration among the markets is high, then investing in different markets will not generate long term gains from portfolio diversification or reduction in risk.

The paper applies unit root test in the presence of endogenous structural breaks that uses a Lagrange Multiplier (LM) test statistics and the Gregory and Hansen cointegration technique that allows for endogenous determined structural break in the relationship have been applied.

The results suggest that the Indian stock markets are not integrated with any of the Asian markets either individually or collectively, and conclude that Indian markets are not sensitive to the dynamics in these markets in the long run.

Since the level of integration has been studied keeping in mind the different economical phases like recession and boom, the study has incorporated the possibility of existence of structural breaks in the individual stock return series as well as in their relationship. The lack of evidence on interlinkage of Indian stock markets with other Asian markets suggests that the trend of Indian markets is not in sync with other markets, possibly due to difference in macroeconomic structure. Since the level of integration has been studied keeping in mind the different economical phases like recession and boom, the study has incorporated the possibility of existence of structural breaks in the individual stock return series as well as in their relationship. The lack of evidence on interlinkage of Indian stock markets with other Asian markets suggest that the trend of Indian markets is not in sync with other markets, possibly due to difference in macroeconomic structure.

This paper aims to study the weak form of efficiency of Indian capital market during the period of global financial crisis in the form of random walk.

The study considered daily closing prices of S&P CNX Nifty, BSE, CNX100, S&P CNX 500 from April 1, 2005 to March 31, 2010. The data source is the equity market segment of NSE and BSE. Both parametric and nonparametric tests (“ex‐posts” in nature) are applied for the purpose of testing weak‐form efficiency. The parametric tests include Augmented Dickey‐Fuller (ADF) unit root tests and nonparametric tests include Phillips‐Perron (PP) unit root tests and Run test. ADF tests use a parametric autoregressive structure to capture serial correlation and PP tests use non‐parametric corrections based on estimates of the long‐run variance of ΔY_t.

The results suggested that the Indian stock market was efficient in its weak form during the period of recession. It means that investors should not be able to consistently earn abnormal gains by analysing the historical prices. Hence one should not be able to make a profit from using something that everybody else knows.

The study reports that all the stocks in these selected indices are fundamentally strong and their prices are not influenced largely by historical prices and other relevant factors which came from industry and any other information that is publically available. Thus it can be concluded that the Indian stock market was informationally efficient and no investor can usurp any privileged information to make abnormal profits.

Where past studies have examined the weak‐form of efficiency of various markets and the effect of globalisation and global financial crisis on the various sectors of developing and emerging economies, this paper attempts to study the weak form of efficiency of the Indian capital market in the period of recession in the form of random walk.

The purpose of the study is to investigate the long-run and short-run dynamic relationship between crude oil prices and the movement of Sensex for the period of 2000–2018.

The study uses the augmented Dickey–Fuller test for the presence of unit root, Johansen cointegration test for estimating the cointegration among the variables. Further, in the case of no cointegration found, the study employed the vector autoregression (VAR) model to estimate the long-run relationship and the Granger causality/Wald test for short-run relationship. The study also conducted tests for the prerequisites of the model: serial correlation, heteroskedasticity and normality of data.

The study found that both the variables, crude oil prices and Sensex are integrated of order 1, that is, I (1), and there is no cointegration between them. Further, the results proliferated from the VAR model unfold the marked effect of previous month crude oil prices (lag 1) on the movement of Indian stock market represented by Sensex considered as the benchmark index. Furthermore, VAR–Granger causality/block exogeneity Wald tests results indicated that there is a causal relationship between the crude oil prices and Sensex under the VAR environment. The model does not have any serial correlation and heteroskedasticity indicating toward the unbiased and robust estimates.

The study is conducted till the year 2018, and data for the present period (post-2018) is excluded due to ongoing trade issues between the USA and oil-exporting countries such as Iran. The current COVID-19 outbreak has also put serious issues. Due to limited time and availability of standardized data, researchers have considered Sensex as equity index only, but for more generalized research outcome few other equity indexes could have been taken for study.

The study is completely original in nature and is an extensive study of the relationship between the crude oil price and Indian stock market with reference to causality between the variables.

Supply chain structure, characteristics, and applicable policies differ between developing and developed countries. While most supply chain management research is directed toward supply chains in developed countries, the authors wish to explore the financial impact of disruptions on supply chains in a developing country. The purpose of this paper is to highlight the importance of effective supply chain management practices that could help avoid or mitigate disruptions in Indian companies. The authors study the stock market impact of supply chain disruptions in Indian companies. The authors also aim to understand the difference in financial implications from disruptions between companies in India and the USA.

Event study methodology is applied on supply chain disruptions data from Indian companies. The data are compiled from public news release in Indian press. A data set of 301 disruptions for a ten-year period from 2003-2012 is analyzed. Stock valuation of a company is used to assess the financial impact.

The results show that Indian companies on average lose −2.88 percent of shareholder wealth in an 11-day window covering the event day and five days pre- and post-disruption announcement. A significant stock decline was observed as early as three days prior to announcement, indicating possibility of insider trading and information differentials between investors. Irrespective of the location and responsibility of a disruption, companies experience significant negative returns. Company size, book-to-market ratio, and debt-to-equity ratio were found to be insignificant in affecting the stock market reactions to disruptions. The authors also compiled supply chain disruptions data for US companies. When compared to the US companies, Indian companies register a significantly higher stock decline in the event of a disruption.

Supply chain disruptions data from India and the USA are analyzed. Broad applicability of results across countries may require studying other developing countries. The research demonstrates potential effectiveness of investment in supply chain management initiatives. It also motivates research focussed specifically on supply chains in developing countries.

Supply chain decision makers in India could benefit from investment in disruptions management and mitigation practices. The results provide a valuation of effective supply chain management. The findings provide guidance for investors in making decisions when supply chains face disruptions.

The paper studies the financial consequences of supply chain disruptions in a developing country. The study is valuable because of increasing globalization, outsourcing, and the economic role of developing countries.

The purpose of this paper is to examine the direction of causality between foreign institutional investment (FII) trading volume and stock market returns in the Indian context. There is evidence of uni‐directional causalities from stock returns to FII flows across various sample periods. The paper attempts to establish whether net FII trading volume causes variations in stock market returns or vice versa.

Using daily data on three different measures of FII trading volume as proxy for FII trading behaviour and S&P CNX Nifty returns, Granger‐causality approach is applied to investigate the bi‐directional causality between net FII trades and returns.

Bi‐directional causality between net FII investment and Indian stock market return is observed. In general, the FIIs seem to be chasing the Indian stock market returns. It is found that FII trading behaviour resulting in heavy trading volumes may cause variations in stock market returns only in the very short‐term, but afterwards, it is the stock market returns which cause changes in FII trading behaviour.

Since foreign equity investors monitor the movement of stock prices, and furthermore, the role of FIIs' exerting impact on Indian stock markets tends to be growing, the authorities will have to develop an environment where FIIs would maintain their positions with confidence, thereby making the markets, as well as investments, more stable. This research considered only stock market returns to test its relationship with three measures of FII trading volume; more macroeconomic as well as microeconomic variables may further be considered for the purpose.

The paper contributes some empirical evidence using three different measures of FII trading volume as proxy of FII trading behaviour, and its bi‐directional relationship with Indian stock market returns.

This study aims to explore the impact of systematic liquidity risk on the averaged cross-sectional equity return of the Indian equity market. It also examines the effects of illiquidity and decomposed illiquidity on the conditional volatility of the equity market.

The present study employs the Liquidity Adjusted Capital Asset Pricing Model (LCAPM) for pricing systematic liquidity risk using the Fama & MacBeth cross-sectional regression model in the Indian stock market from January 1, 2012, to March 31, 2021. Further, the study employed an exponential generalized autoregressive conditional heteroscedastic (1,1) model to observe the impact of decomposed illiquidity on the equity market’s conditional volatility. The study also uses the Ordinary Least Square (OLS) model to illuminate the return-volatility-liquidity relationship.

The study’s findings indicate that the commonality between individual security liquidity and aggregate liquidity is positive, and the covariance of individual security liquidity and the market return negatively affects the expected return. The study’s outcome specifies that illiquidity time series analysis exhibits the asymmetric effect of directional change in return on illiquidity. Further, the study indicates a significant impact of illiquidity and decomposed illiquidity on conditional volatility. This suggests an asymmetric effect of illiquidity shocks on conditional volatility in the Indian stock market.

This study is one of the few studies that used the World Uncertainty Index (WUI) to measure liquidity and market risks as specified in the LCAPM. Further, the findings of the reverse impact of illiquidity and decomposed higher and lower illiquidity on conditional volatility confirm the presence of price informativeness and its immediate effects on illiquidity in the Indian stock market. The study strengthens earlier studies and offers new insights into stock market liquidity to clarify the association between liquidity and stock return for effective policy and strategy formulation that can benefit investors.