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In this paper, we investigate whether the use of accounting conservatism in India decreases IPO underpricing, which is of attention to stakeholders and supervisors. Furthermore, the study examines how asymmetry information affects the implication of accounting conservatism for IPOs. Based on a regression analysis of 527 firms that went public through IPOs of "A" shares listed on the national stock exchanges between 2000 and 2020, the paper also examines whether the relationship between conservatism and under-pricing is robust to alternative measures of accounting conservatism, mean regressions, sample exclusions, and endogenous treatment models. The research study finds that accounting conservatism is negatively associated with the degree of IPO under-pricing, and the association between accounting conservatism and IPO under-pricing is more perceptible when information asymmetry is high. The paper's originality should shed light on what drives IPO underpricing and how it could be affected by accounting conservatism in an Indian economy, and provide find evidence that legal origin, a factor linked to the practice of conservatism, influences the relationship between under-pricing and conservatism. [ABSTRACT FROM AUTHOR]

In India, post economic liberalisation period starting from early 1990s opened up new vistas for rapid development of Indian stock markets accompanied by high volatility in stock exchanges. The volume of trade increased rapidly with more number of retail investors beginning to invest in equity shares of listed companies in specific industry sectors. This brought to the fore the importance of analysis of business and financial risks associated with such investment decisions. Every rational investor will do well to analyse the risk and return before investing in any stock or security. The investment process must be considered in terms of both risk and return. The present study deals with the estimation of business risk and financial risk of the selected companies in selected industries, based on empirical analysis. For the study, six industries such as Automobile, Cement, Paint, Paper, Pharmaceuticals and Personal Care(FMCG) have been selected from the Indian industries from April 1996 to March 2020. The findings of the study revealed the extent of the relationship between business and financial risk and return in specific sectors of industry in India. [ABSTRACT FROM AUTHOR]

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]

The paper adds to the literature on financialisation with firm‐level evidence from India, an emerging market in the growth phase, when capital accumulation is likely to be important. I use a broader definition of financialisation to add on to the investment function developed by Orhangazi (2008, Cambridge Journal of Economics, 32, 863). Empirically the above specification is tested for two samples of Indian non‐financial firms for the study. The first, Group I, includes firms prominent on the stock market represented by the combined sample of NIFTY non‐financial indices (ninety‐two firms), and the second, Group II, includes a broader group of all non‐financial firms (704 firms). Using the Arellano–Bond dynamic panel model, the paper finds that financialisation has a robust negative impact on capital accumulation. The negative impact of financialisation is reflected in higher financial income for both the samples, underlining a likely trade‐off between income from core activities and real capital accumulation. [ABSTRACT FROM AUTHOR]

India has witnessed substantial increase in capital flows, particularly Foreign institutional Investment in equity as well as derivatives segment since the 1990s. However, Fll flows are sighted as 'hot money'- more volatile than other type of flows, which gets affected by the domestic and global- macro economic factors, thereby raising questions about the need to encourage Fll flows in narrow and shallow (in terms of absorption capacity) capital market such as India. This paper attempts to forecast daily Aggregate Fll flow in Indian Capital market and particularly in Futures Market (Derivative Segment) using Auto Regressive Integrated Moving Averaqe (ARIMA) model.The paper tries to examine Fll flows in India towards futures market along with spot market by tracing which AR terms and/or MA terms influence the current inflow or outflow. [ABSTRACT FROM AUTHOR]

Social Stock Exchange provides access to dedicated investors and businesses seeking to achieve a positive social and environmental impact through their activities. The aim of a social stock exchange is to act as a platform to bring social organizations and investors together whose missions and interests align with each other. Social stock exchanges are already established and functioning in a handful of countries including United Kingdom, Canada, South Africa, and Singapore. As far as India is concerned, SEBI has taken quick action to respond to the implementation of social stock exchange proposed in the Union Budget 2019, by forming a working group to examine and make recommendations for the same. The main objectives of this research paper were to analyse the working of SSEs in different countries using a descriptive study method. On understanding the working of SSEs around the globe, we have suggested certain features that can be implemented in the Indian Social Stock Exchange. We have also brought out the differences in the terms closely related to Social StockExchange like-Impact Investing (II), Socially Responsible Investing (SRI), Environmental, Social and Governance (ESG), and Thematic Investing (T.I.). [ABSTRACT FROM AUTHOR]

Purpose: The behavioural decision-making process of individuals highlights the importance of investors' sentiment and their correlation with the real economy. This paper aims to contribute to the literature of behavioural finance by examining the influence of contextual factors on investment decision-making. Design/methodology/approach: Using a questionnaire, a total of 445 valid responses were collected from March to May 2021 through online sources. The current study uses a technique of Fuzzy-analytical hierarchical process (AHP) to assign relative weights to various contextual factors influencing investment decision-making. Harman's single factor test was used to check common method bias. Findings: Results of the study reveal that accounting information, self-image/firm-image coincidence, and neutral information as the top-ranked factors in influencing investment decisions, whereas advocate recommendation and personal financial needs emerged as less important factors in influencing investment decisions. Research limitations/implications: The current study collects data from Indian stock market investors, which may limit the generalization of the study to India only. Moreover, this study is cross-sectional in nature, and there are numerous factors that are not part of the study but might significantly influence the investors' decision-making process. Practical implications: The research has implications for both academicians working in the area of behavioural finance and practitioners' who are active in stock markets, more specifically dealing with retail investors and in the domain of personal finance. Also, the current study will accommodate different groups, i.e. policy makers, financial advisors, investors, investment professionals, etc. in carrying out their professional work. Originality/value: The current study will provide a comprehensive overview of individual investor behaviour. To the best of the authors' knowledge, the present study is one of its kind to use the Fuzzy-AHP technique for evaluating the relative ranks of contextual factors influencing investment decision-making. [ABSTRACT FROM AUTHOR]

The COVID-19 epidemic has brought attention to the vulnerability of new illnesses, and immunization remains a viable option for resuming normal life. This paper examines the influence of COVID-19 vaccination on the death rate and the performance of stock market in India. For this study, COVID-19 vaccination and death rate data is gathered from the Ministry of Health and Family Welfare (MoHFW) portal, and the data for the stock index is taken from the Bombay Stock Exchange (BSE), India. In order to achieve a precise representation of feature significance and distribution, EDA (Exploratory Data Analysis) is utilized in this study. The impact of COVID-19 immunization on the mortality rate and stock market index is investigated using both statistical analysis and Machine Learning Regression-based models. The models are remarkably accurate in reproducing actual result. The empirical study suggests that vaccination has a strong positive impact on the stock market and reducing the death rate. Furthermore, the policies recommended by government and monetary authorities coupled with COVID-19 vaccine supported the stock market recovery in pandemic. [ABSTRACT FROM AUTHOR]

The existence of behavioural bias such as positive feedback trading (PFT) and herding is well researched for advanced economies. This paper explores whether foreign institutional investors (FIIs), a prominent investor group, pursue these strategies in India. The contribution lies in the application of multiple measures of herding. Results indicate that FIIs exhibit PFT behaviour in equity and to some extent, in debt. At the individual stock level, FIIs herd during non-extreme market conditions, but market-level measures indicate absence of herding in extreme market conditions. In the bullish market, they behave more rationally compared to bearish or normal market conditions. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to examine whether investor's awareness, risk perception, and prior investment experience have any effect on the equity investment. The study is based on primary data collected using multistage random sampling method. We apply binomial logistic regression for analysis and observe that both awareness and past experience influence equity investments. We, however, also observe that risk perception plays no role in equity investments. We propose that appropriate policy measures can enhance the awareness level and experience of the investors regarding equity investment. To increase the individual investors' participation in the equity market, in the context of India, we propose that regulators and policy makers focus on making people experienced in this field. Government should nudge individuals by incentivizing equity market investment to increase market participation. Employers can also impart investment education to the employees to make them aware about equity investment and consequently increase equity investment. [ABSTRACT FROM AUTHOR]

Purpose: The preference of firm corporate social responsibility (CSR) spending is shaped by different groups of owners and the institutional environment in which the firm operates. This paper aims to study the heterogeneity among the controlling groups and firms' internationalization in influencing the CSR decision in emerging economy firms. Design Methodology Approach: This paper draws understanding from institutional theory to inspect the propensities of various ownership groups such as lending institutions (LI), domestic mutual funds (MF) and foreign institutional investors (FIIs). The empirical analysis was conducted from a sample of 1,594 unique Bombay stock exchange (BSE)-listed non-financial Indian firms during the 2014–2019 period using Tobit panel regression analysis. Findings: The findings reveal that firms' CSR activities are impacted differently by ownership share of different types of institutional investors after controlling for firm-level resources and capabilities. Lending institutions, FIIs and MF are supportive of CSR investments by firms along with international investments by the firm. Further, the results show that the CSR spend is positively influenced by the business group affiliation of the firm compared to the unaffiliated group of firms. Practical Implications: The analysis has implications for both institutional investors and multinational firms. In the merging market context, managers and owners who target long term strategies such as CSR will benefit from increasing shareholdings of creditors (lending institutions). They can also take steps to improve their transparency and corporate governance structure so as to attract foreign institutional investments, thus, in turn, helping the internationalization process of the firm. Originality Value: This paper considers the role of the diverseness of the ownership institutional investors along with the moderating effect of business group affiliation of the firm and international investments in impacting the CSR spend. This disparity has not been previously studied with the latest data in an emerging economy context. [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]

The present study examines the relevance of Corporate Social Responsibility (CSR) expenditure to the firms in the mandatory regime in India. The paper has its theoretical basis from the instrumental aspect of the Stakeholder theory, which assumes a positive influence of CSR over financial performance. Therefore, the study hypothesizes that the firms which fulfil the CSR expenditure requirement will exhibit higher stock returns and lower systematic risk. Since India mandated CSR in the year 2014, the data of four years (2016-2019) for the sample of 426 National Stock Exchange (NSE) listed Indian firms are taken to employ the OLS regression method. The CSR expenditure in the mandatory regime was not found to be relevant to the firms because of an insignificant positive impact of mandatory CSR expenditure on stock returns. Thus, the instrumental aspect is not supported by the findings. However, the findings indicate a decrease in the systematic risk of the firms. Only a few studies in India investigated this phenomenon in the mandatory regime. Further, the contributions of the study to the CSR literature are fairly useful from the perspective of firms, investors, policy-makers, regulators, scholars, and countries that are planning for legislating CSR. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to investigate the cointegration and volatility spillover dynamics between the USA and South Asian stock markets, namely, India, Pakistan and Sri Lanka. The main objective of this study is to provide the knowledge about integration of financial market and volatility spillovers before, during and after global financial crisis to investors, fund managers and policy-makers. Design/methodology/approach: The Johansen and Juselius cointegration test, Granger Causality test and bivaraite EGARCH model have been applied in this study to examine integration and volatility spillovers between selected stock markets. Findings: The findings show that long-term integration between the USA market and South Asian emerging stock markets. It is found that USA stock market has causal relationship with emerging stock markets in short-term. The findings of EGARCH model reveal that asymmetric volatility spillover effects significant in all selected stock markets in pre, during and post-crisis periods. Furthermore, significant volatility spillover is found from stock markets of USA to all selected South Asian markets during and post-crisis periods. However, volatility spillovers from USA to India and Sri-Lanka markets are significant, while insignificant in case of Pakistani market in pre-crisis period. Overall, we find that returns and volatility spillover effects are higher in financial crisis period as compared to non-financial crisis period. Practical implications: The findings of this paper have important implications for investors, portfolio managers and policy-makers. They can take potential benefits from international portfolio diversification by considering all these facts. The understanding and knowledge of across volatility transmission help them to maximize the gains from diversification and minimize the risk. Policy-makers can develop such strategies which protect the markets of these economies from future financial crisis. Originality/value: Although in finance literature numerous studies have been conducted on integration between different stock markets, most of the studies investigated the integration and volatility spillovers between developed stock markets. However, many studies also analyzed the integration among emerging stock markets in literature review but it is hard to find studies in the context of South Asian stock markets on the effect of global financial crisis on stock markets. The main contribution of this study is to investigate the stock markets integration and volatility transmission between the USA and South Asia by considering the effect of recent 2007 US subprime financial crisis. [ABSTRACT FROM AUTHOR]

Over the course of the last century, numerous jurisdictions have adopted the principles of free market economics. This has resulted in a global economy that is expanding due to the proliferation of public and private sector enterprises, which are themselves the product of public markets where anyone can invest and trade in securities. Since the performance of these enterprises is a direct function of the public's faith (and investment) in them, it is but a corollary that regulation of such securities has followed in the footsteps of this economic boom. The insider trading regime of these numerous jurisdictions constitutes one such form of securities regulation. This paper discusses the birth and evolution of the insider trading regime in India, weighing the legislative intent behind the insider trading regulations and the far-reaching scope of their application. In order to achieve this aim, the paper looks at the multi-faceted theories of insider trading such as the classical theory and the misappropriation theory, as recognized in the United States, and examines whether India's insider trading regulations cover such theories. Upon such examination, it is seen that the powers accorded to the Securities and Exchange Board of India are comprehensive and, with some assistance from the legislature, the regulator is well posed to tackle future threats to investor confidence, market integrity, and the Indian economy. [ABSTRACT FROM AUTHOR]

This study aims to determine whether a firm's dividends are influenced by the sector to which it belongs. This paper also examines the explanatory factors for dividends across individual sectors in India. This longitudinal study uses balanced data consisting of companies listed on the National Stock Exchange (NSE) of India for 12 years--from 2006 to 2017. Pooled ordinary least squares (POLSs) and fixed effects panel models are used in our estimation. We find that size, profitability, and interest coverage ratios have a significant positive relation to dividend policy. Furthermore, business risk and debt reveal a significantly negative relation with dividends. The findings on profitability support the free cash flow hypothesis for India. However, we also found that Indian companies prefer to follow a stable dividend policy. As a result of this, even firms with higher growth opportunities and lower cash flows continue to pay dividends. We also find evidence that dividend policies vary significantly across industrial sectors in India. The results of this study can be used by financial managers and policymakers in order to make appropriate dividend decisions. They can also help investors make portfolio selection decisions based on sectoral dividend paying behavior. [ABSTRACT FROM AUTHOR]

Purpose: The phenomenon known as financialization of commodities, arising from the speculation in commodity derivatives market, has raised serious concerns in the recent past. This has prompted distortion in agricultural commodity prices driving them away from rational levels of supply and demand shocks. In the backdrop of financialized commodities leading to increase in price of agricultural products and their interaction with equity markets, the authors examine the investment of institutional investors in impacting the agricultural returns. The paper aims to focus on the financial mechanism that drives extreme values and the mean of agricultural returns. Design/methodology/approach: The authors employ the Threshold AutoRegressive Quantile (TQAR) methodology to find evidence of linkages between the Indian agricultural and equity markets from January 2010 to May 2020 consistent with the rise in inflows of institutional investors in agricultural markets. Findings: The results reveal that the investors impact the agricultural commodity markets strongly when the composite commodity index value (COMDEX) is low. Additionally, in the lower extreme quantiles (0.25) of agricultural returns, the integration between the equity index and agricultural returns is found to be highly significant compared to insignificant values in the higher quantiles (0.75 and 0.95) in both the regimes. The results suggest that low values of agricultural commodities are more closely linked to equity indices when composite commodity index value is low. This implies that, at the lower quantiles of COMDEX return (bad day), the investors move to the stock market. In that way, the commodity index returns are seen to be as a strong channel for the financialization of Indian agricultural commodities and suggesting potential involvement of investors during those regime. Research limitations/implications: Regulators need to anticipate the price fluctuations in spot and futures markets. Investors in commodity markets need to strengthen risk awareness to carry out portfolio strategies. Practical implications: From policy perspective, it is of pivotal importance to enhance the understanding of the financialization of agricultural products. The findings provide reference measures to stabilize the commodity markets, alleviate price distortions and carry out further evidence of price discovery and risk management in Indian commodity markets. Originality/value: To the best of the authors' knowledge, this study is the first to highlight the potential influence of financial markets on the financialization of agricultural commodities in an emerging economy like India. [ABSTRACT FROM AUTHOR]

India is on the path of Digital India, FII and DII's in the country boost the country's economy. Both FII and DII have dominant role in capital formation which assists in assets formation along with investments in the stock market form of trading of various securities. FII funds a capital sources in India from foreign countries, affect the financial system and boost the economical growth. During pandemic, covid -19 the Indian economy has faced severe changes which affected the DII and FDI funds too. The research paper points on the changes in the FII and DII funds due to pandemic with reference to increase in covid cases. Design/Methodology/Approach-The paper employs quantitative approach have exploratory research design. The secondary has been collected from authorized government sites i.e. www.moneycontrol.com & www.statista.com for infusion of FII and DII funds in India and data sheet of COVID-19 cases in India(January 2020 to December 2020). Furthermore, for analyze of data SPSS version 20 has been used. Correlation & regression and ANOVA; Statistical techniques have been applied to reach the findings. The findings exhibits that there has been a significant changes in FII and DII during the COVID first wave period as compared to the pre COVID. Being FII and DII are very important for any countries economy, therefore studying the same and especially for the COVID period is highly essential from the Future perspective. This paper is original as till date no study has been conducted in detail to study the pattern and impact of FII and DII during the COVID times. [ABSTRACT FROM AUTHOR]

Purpose - The purpose of this paper is to examine the lead-lag relationships between the National Stock Exchange (NSE) Nifty stock market index (in India) and its related futures and options contracts, and also the interrelation between the derivatives markets. Design/methodology/approach - The paper uses serial correlation of return series and autoregressive moving average (ARMA) model for studying the lead-lag relationship between hourly returns on the NSE Nifty index and its derivatives contracts like futures, call and put options. Further, the lead-lag relation between hourly returns of the derivatives contracts among themselves is also studied using ARMA models. Findings - The ARMA analysis shows that the NSE Nifty derivatives markets tend to lead the underlying stock index. The futures market clearly leads the cash market although this lead appears to be eroding slightly over time. Although the options market leads the cash overall, there is some feedback between the two with the underlying index leading at times. Further, it is found that the index call options lead the index futures more strongly than futures lead calls, while the futures lead puts more strongly than the reverse. Practical implications - The results imply that the derivative contracts on NSE Nifty lead the underlying cash market. Thus, the derivative markets are indicative of futures price movements and this will certainly be helpful to potential investors to design their risk-return portfolio while investing in stocks and derivatives contracts. - Originality/value - This paper is an original piece of work towards exploring the lead-lag relation between NSE Nifty and the derivative contracts. The issue of price discovery on futures and spot markets and the lead-lag relationship are topics of interest to traders, financial economists, and analysts. [ABSTRACT FROM AUTHOR]

The purpose of this study is to explore the nature of the association and the possible existence of a shortrun and long-run relationship between the stock-market indices of South Africa, India and the USA. The idea behind this combination is to know how the stock markets of these three prominent countries are related to each other. The study employs monthly data from the stock indices, namely JALSH (South Africa), NIFTY (India) and NASDAQ (USA) composite from April 2004 to March 2014. After testing for the normality of the data distribution and the stationarity of the time series data, this paper discovered a strong correlation between the stock market indices of South Africa, India and the USA. The correlation among the stock markets is high, particularly between South Africa and India. In addition, the paper attempts to discover the presence of any predictive ability among these markets by applying the Granger causality test. The result indicates that the NASDAQ index has no predictive ability as far as the JALSH and NIFTY indices are concerned. However, the JALSH index has a predictive ability on the NIFTY index. After testing the Granger cause relationship, the existence of a long-run and short-run relationship is tested. The long-run relationships among the stock market indices are analysed, following the Johansen and Juselius multivariate cointegration approach. The result suggests the absence of a long-run relationship among the three stock market indices. Short-run relationship is investigated with the Vector Autoregression (VAR) model, and the outcome obtained shows that both the USA and the South African stock markets are predicted only by their own past lags. However, the Indian stock market is seen to be a function of its own past lags and the past lags of the South African stock index. [ABSTRACT FROM AUTHOR]

Purpose – This paper aims to investigate whether the use of conditional and unconditional Fama and French (1993) three-factor and Carhart (1997) four-factor asset pricing models (APMs) captures the role of asset pricing anomalies in the context of emerging stock market like India. Design/methodology/approach – The first step time series regression approach has been used to drive the risk-adjusted returns of individual securities. For examining the predictability of firm characteristics or asset pricing anomalies on the risk-adjusted returns of individual securities, the panel data estimation technique has been used. Findings – Fama and French (1993) three-factor and Carhart (1997) four-factor model in their unconditional specifications capture the impact of book-to-market price and liquidity effects completely. When alternative APMs in their conditional specifications are tested, the importance of medium- and long-term momentum effects has been captured to a greater extent. The size, market leverage and short-term momentum effects still persist even in the case of alternative unconditional and conditional APMs. Research limitations/implications – The empirical analysis does not extend for different market scenarios like high and low volatile market or good and bad macroeconomic environment. Because of the constraint of data availability, the authors could not include certain important anomalies like net operating assets, change in gross profit margin, external equity and debt financing and idiosyncratic risk. Practical implications – Although the active investment approach in stock market shares a common ground of semi-strong form of market efficiency hypothesis which also supports the presence of asset pricing anomalies, less empirical evidence has been explored in this regard to support or repute such belief of practitioners. Our empirical findings make an attempt in this regard to suggest certain anomaly-based trading strategy that can be followed for active portfolio management. Originality/value – From an emerging market perspective, this paper provides out-of-sample empirical evidence toward the use of conditional Fama and French three-factor and Carhart four-factor APMs for the complete explanation of market anomalies. This approach retains its importance with respect to the comprehensiveness of analysis considering alternative APMs for capturing unique effects of market anomalies. [ABSTRACT FROM AUTHOR]

Stock markets around the world experienced a massive collapse during the first wave of COVID-19. Roughly in the month of January 2021, the second wave of COVID-19 struck in India, reaching its peak in May, and by the end of May, the active cases started to decline. A third wave is again predicted by the end of 2021, and as such, the COVID-19 pandemic seems to have become a periodic phenomenon over the last couple of years. Therefore, the study of the behavior of the stock market as well as that of the investors becomes very interesting and crucial in this highly volatile and vulnerable market trend. Motivated by these facts, in the present paper, the researcher develops a model for portfolio management, using curve-fitting techniques and shows that this model can encounter the market volatility efficiently in the context of the Indian stock market. The portfolio is designed based on data taken from the National Stock Exchange (NSE), India, during 1 January 2020 to 31 December 2020. The performance of the portfolio in real-life situation during 1 January 2021 to 21 May 2021 is examined, assuming investments are made according to the proposed model. [ABSTRACT FROM AUTHOR]

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The epidemic of COVID-19 has impacted the entire global stock market in an unforeseen manner. Due to the uncertainties that occurred in the global economy; the financial market of India also responded to the pandemic and experienced significant volatility. This study empirically explores the effect of COVID-19 on the Indian stock market, considering the COVID-19 scenario. This research explores, employing the regular closing prices of indices like Nifty, the volatility of these indices over the period from 3 September 2019 to 10 July 2020. In addition, the report sought to make a quantitative review of the stock market return in the pre-COVID-19 and COVID-19 situations. The volatility of the indexes is captured using the GARCH model. The results indicate that the Indian stock market has encountered uncertainty during the pandemic era. When c the findings are compared with those of the pre-COVID-19 phase, the author found that before the COVID-19 phase, the returns were higher than during COVID-19.During the first lockout period, from 24 March to 6 April, the returns of both stock markets touched the bottom line. [ABSTRACT FROM AUTHOR]

In this paper, we explore mutual information based stock networks to build regular vine copula structure on high frequency log returns of stocks and use it for the estimation of Value at Risk (VaR) of a portfolio of stocks. Our model is a data driven model that learns from a high frequency time series data of log returns of top 50 stocks listed on the National Stock Exchange (NSE) in India for the year 2014. The Ljung-Box test revealed the presence of Autocorrelation as well as Heteroscedasticity in the underlying time series data. Analysing the goodness of fit of a number of variants of the GARCH model on each working day of the year 2014, that is, 229 days in all, it was observed that ARMA(1,1)-EGARCH(1,1) demonstrated the best fit. The joint probability distribution of the portfolio is computed by constructed an R-Vine copula structure on the data with the mutual information guided minimum spanning tree as the key building block. The joint PDF is then fed into the Monte-Carlo simulation procedure to compute the VaR. If we replace the mutual information by the Kendall's Tau in the construction of the R-Vine copula structure, the resulting VaR estimations were found to be inferior suggesting the presence of non-linear relationships among stock returns. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the forecasting performance of ex-post an ex-ante volatility forecasts against realized return volatility of various time horizon. The competing volatility forecasts are implied volatility, RiskMetrics and GJR-GARCH; the empirical results uncover that implied volatility dominates the other volatility forecast in the prediction of future realized return volatility. The in-sample forecast suggests that ex-ante volatility best explains the future market volatility. The non-overlapping sampling procedure gives the more robust estimate of volatility forecasts, the results reveals that implied volatility forecasts of all horizon appears positive unbiased forecaster of realized volatility. Moreover, the instrumental variable estimation in the presence of error-in-variable clears that implied volatility is free from measurement error; OLS estimates remains more consistent than the 2SLS estimates. The information content of implied volatility encourages the exchanges to construct the implied volatility indices and volatility products on underlying volatility index. [ABSTRACT FROM AUTHOR]

Background: Gold exchange-traded funds, since introduction, are primarily aimed at tracking the price of physical gold in the financial market. This, a category of exchange-traded funds, whose units represent physical gold, is traded on exchanges like any other financial instrument. In the Indian financial market, gold exchange traded funds were introduced a decade ago to facilitate ordinary households' participation in the bullion market. They were also designed to assist in the price discovery mechanism of the bullion market. Presentation of the hypothesis: In this paper, it is attempted to check if one of the constituents of price discovery mechanism, informational efficiency, has been achieved in gold exchange-traded funds' market. Information efficiency becomes evident only when all available information is reflected in the market price of the instrument. Testing the hypothesis: Therefore, in order to assess the weak-form efficiency of the gold exchange-traded funds market, the daily returns of five gold exchange-traded funds traded on the Indian Stock Exchange over the period March 22, 2010, to August 28, 2015, were used. The non-parametric runs test, the parametric serial correlation test, and the augmented Dickey-Fuller unit root test are employed. Implications of the hypothesis: The test results provide evidence that the efficient market hypothesis does not hold for the gold exchange-traded funds' market in India. Further, the test results address several underlying issues with respect to price discovery in the market under study and suggest that the Indian market for this derivative is not weak-form efficient. Hence, the factors affecting gold exchange traded-funds' market warrant the attention of the country's regulatory bodies, as appropriate legislation in support of market efficiency is needed. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has become major problem for financial markets and world economy. In this paper we investigated the extreme tail behavior of NIFTY 50 index during the COVID-19 pandemic. The extreme behavior of the stock market is examined through GPD model by suing high frequency data (5-min interval) of log returns ranging from 11th March 2020 to 30th Sept 2020 which provide more precise description of NIFTY 50 tail distribution in the pandemic period. The result indicates GPD give a real picture of uncertainties associated with COVID-19. The finding of study will assist in decision making to monitor COVID-19 impact on financial markets. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to study the pattern of long-run performance of small and medium enterprises (SMEs) initial public offerings (IPOs) and examine the firm- and issue-related determinants of long-run performance of SME IPOs in India. Design/methodology/approach: The 3 6, 9 and 12 months share returns of Indian SME IPOs is studied using event time methodologies, i.e. buy and hold returns, cumulative abnormal returns and wealth relatives on a sample of 375 SME IPOs issued during February 2012 to May 2018. Additionally, ordinary least square regression has been used to investigate the determinants of long-run performance of SME IPOs on a reduced sample of 104 because of non-availability of price observations. Findings: The findings reveal that Indian SME IPOs exhibit long-run overperformance contradicting the international evidences of underperformance, and this overperformance is significantly evident using buy and hold abnormal return (BHAR). Furthermore, based on the divergence of opinion hypothesis, fads theory and windows of opportunity hypothesis, the results reveal that on one hand, issue size and oversubscription negatively affect BHAR, while on the other hand, auditor reputation, underwriter reputation, hot market, underpricing, inverse of issue price, profits prior to listing positively affect long-run performance. However, firm age, firm size, debt equity ratio, volatility and long-run performance computed through BHAR lacks significant relationship. Research limitations/implications: The study relied on event time methodology of measuring aftermarket performance of one year because of the limited availability of price offerings. Hence, the study could be extended to analyze aftermarket returns over a period of three to five years to enable reaching the vivid conclusions. Calendar time methodology may also be used to compute abnormal returns. Practical implications: The results based on the study provides an implication to the investors by providing them an opportunity to bank higher long-run returns by engaging in active and timely trading strategies. Nevertheless, the results also show that investors should be cautioned while taking investment decisions. Originality/value: The study contributes to rising body of international literature by analyzing the larger and recent sample of IPOs issued from 2012 to 2018 listed on SME exchange. [ABSTRACT FROM AUTHOR]

This study examines the impact of domestic and foreign shocks on the real and financial sector of BRIC countries. For this purpose, we use a structural vector autoregressive (SVAR) model over the extended period of 1997 to 2016. We conclude that domestic policy shocks have a more substantial impact on Brazilian, Indian, and Russian economy than foreign shocks, while foreign shocks have more contribution in the case of China. Interestingly, results show the negative impact of policy shocks on bank credit provided, implying its role in multiplying the impact of shocks on real variables. Surprisingly EPU of USA has a positive impact on stock markets of India and China, implying capital flight phenomenon, where investor transfer investment from risky to safer places. [ABSTRACT FROM AUTHOR]

This paper explores the importance of central banking policies in financial market performance, using the case of India. For this purpose, the paper comparatively analyzes the performance of financial markets during the regimes of last three governors of the Reserve Bank of India—Y V Reddy, D Subbarao, and Raghuram Rajan. The paper discusses the central banking policies in these periods with respect to monetary stability, inflation, and growth challenges. The paper presents an analysis of returns and volatility in stock markets and currency markets in their tenures in comparison with those from other selected emerging markets (Brazil, Russia, China, South Africa) and developed markets (USA and UK). The paper also brings out the leverage effect by applying the exponential generalized autoregressive conditional heteroskedasticity (EGARCH) model in addition to comparatively analyzing the performance of financial markets. Further, the paper assesses the impact of central banking policies on financial markets by using the fixed effect model on the reference countries for the period under reference. [ABSTRACT FROM AUTHOR]

Purpose - The purpose of this paper is to examine the long-run relationship between the Indian capital markets and key macroeconomic variables such as interest rates, inflation rate, exchange rates and gross domestic savings (GDS) of Indian economy. Design/methodology/approach - Quarterly time series data spanning the period from January 1995 to December 2008 has been used. The unit root test, the co-integration test and error correction mechanism (ECM) have been applied to derive the long run and short-term statistical dynamics. Findings - The findings of the study establish that there is co-integration between macroeconomic variables and Indian stock indices which is indicative of a long-run relationship. The ECM shows that the rate of inflation has a significant impact on both the BSE Sensex and the S&P CNX Nifty. Interest rates on the other hand, have a significant impact on S&P CNX Nifty only. However, in case of foreign exchange rate, significant impact is seen only on BSE Sensex. The changing GDS is observed as insignificantly associated with both the BSE Sensex and the S&P CNX Nifty. The paper, on the whole, conclusively establishes that the capital markets indices are dependent on macroeconomic variables even though the same may not be statistically significant in all the cases. Originality/value - This study emphasises on the impact of macroeconomic variables on the stock market performance of a developing economy, whose performance is measured by these variables. [ABSTRACT FROM AUTHOR]

Foreign institutional investors (FIIs) play a vital role in the stock market of a country and Indian stock markets are no exception to this. FIIs bring liquidity, buoyancy and growth in stock markets but at the same time they also enhance the level of volatility and instability. Over past few years the stock markets in India have shown an impressive growth. The stock market indices are making new strides and increasing number of shares are making new highs. Following India's impressive growth story, increasing corporate profitability and competitiveness, and better integration with the world economy, the investment by foreign institutional investors (FIIs) in the stock markets of India has gone up tremendously. Investment decisions of foreign institutional investors in India are affected by so many factors. Investment behavior of domestic institutional investors (DIIs) is one such important factor. This research paper is an attempt to analyze the impact of domestic institutional investors on the investment decision of foreign institutional investors in India. In other words, this study explores whether Domestic Institutional Investors affect the investment decisions of Foreign Institutional Investors in India or not. For this purpose, researchers have used regression analysis. Mutual fund investments have been taken as proxy for investment by DIIs. Investment patterns of FIIs and DIIs have been divided into eight variables i.e. FII Equity Purchases, FII Equity Sales, FII Debt Purchases, FII Debt Sales, MF Equity Purchases, MF Equity Sales, MF Debt Purchases and MF Debt Sales respectively. The study reveals that investment decisions of DIIs affect the investment decisions of FIIs. [ABSTRACT FROM AUTHOR]

In prior literature it was conjectured that the Indian stock market responses on domestic macroeconomic surprises are expected to be significantly influenced by global surprises. In this paper we empirically established that hypothesis. We used both the Event Analysis and VAR model. We found that global surprises consistently dominate Indian stock market and the influence of domestic macroeconomic surprises on it is relatively less. The understanding of stock market dynamics against domestic macroeconomic surprises and global factors can provide assistance to the policy makers for augmenting policy effectiveness and the corporate finance professionals for enhancing decision making. [ABSTRACT FROM AUTHOR]

In this paper, we explore the problem of establishing a network among the stocks of a market at high frequency level and give an application to program trading. Our work uses high frequency data from the National Stock Exchange, India, for the year 2014. To begin, we analyse the spectrum of the correlation matrix to establish the presence of linear relations amongst the stock returns. A comparison of correlations with pairwise mutual information shows the further existence of non-linear relations which are not captured by correlation. We also see that the non-linear relations are more pronounced at the high frequency level in comparison to the daily returns used in earlier work. We provide two applications of this approach. First, we construct minimal spanning trees for the stock network based on mutual information and study their topology. The year 2014 saw the conduct of general elections in India and the data allows us to explore their impact on aspects of the network, such as the scale-free property and sectorial clusters. Second, having established the presence of non-linear relations, we would like to be able to exploit them. Previous authors have suggested that peripheral stocks in the network would make good proxies for the Markowitz portfolio but with a much smaller number of stocks. We show that peripheral stocks selected using mutual information perform significantly better than ones selected using correlation. [ABSTRACT FROM AUTHOR]

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Initial public offerings (IPOs) have a special place in finance, probably because they are the first opportunity to value a number of financial assets of company by variousparticipants of capital market. In India, initial public offerings (IPOs) have attracted many investors. Because companies coming out with IPOs are new and have no historical data to analyze. The success of IPO is critical for stockholders, companies, and the economy. Objectives: 1. To Study different IPOs during 2020-22 2. To analyze performance of Indian IPOs in short Run time frame. Research Approach The work in this research paper is carried out on the basis of empirical evidence. The study encompasses 33 IPOs which got listed on NSE of India for the period between 2020-2022. Thework is based on data collected from sources which are secondary in nature. The data required for research work is taken from website of National stock Exchange of India in the form of price quotes of shares and Nifty values. Themarket adjusted short term performance model, wealth relative index model along with other statistical measures is used for the study. Scope of work- The research work is restricted to companies which came out with public issues during the above specified period and got listed on NSE of India. Period -Year 2020-2022 Limitations of Study-The study covers external factors which affects the IPO performance. Originality-This research work is original and examines stock's listing profit or loss and its performance after the listing on recognized stock exchange. [ABSTRACT FROM AUTHOR]

A significant boom occurred in the Indian financial market and growth in the post-liberalization era. This motivates us to analyze the impact of stock market and credit market (two components of financial market) for the growth of financial market. This paper attempts to show the linkage between stock and credit markets and their impact on the Indian economy taking the period after post-liberalization. The period of analysis is from 1994 to 2010; we identify the three variables as stationary and find a relationship between the financial market and gross domestic product (GDP) and a long-run effect of lagged differences in credit market on GDP. It has been inferred that stock market development has larger and more significant long-run mutual effects on economic growth than credit market development in India. [ABSTRACT FROM AUTHOR]

The paper has discussed momentum in stock index and empirically examined various factors contributing in generation of momentum. The relative importance of momentum as a factor in the CAPM asset pricing model is also discussed. Momentum return is estimated from the National Stock Exchange of India. The empirical findings of the paper indicate inverse relationship of Price-Earnings Ratio, Dividend Yield, Index of Industrial Production and Terms Spread with momentum returns. Using Vector Autoregressive (VAR) methodology, it is also observed that momentum is an inherent factor in the pricing of capital asset. The methodology also used the Impulse Response Function (IRF) to articulate the response of momentum to any change in the macroeconomic and firm-specific factors. Along with Price-Earnings Ratio, Price-Book Ratio and Dividend Yield, Momentum Payoffs is added as a fourth factor to test the Fama-French unconditional CAPM. The present study included momentum as an additional factor to empirically test the Chordia and Shivakumar (2002) 4-Factor model in the Indian context. The study also estimated the ARCH effect to understand the "Momentum Clustering" in the obtained momentum series. [ABSTRACT FROM AUTHOR]

While there has been a rapid growth of business and management schools in India since 1990, the curricula, teaching methods and the mode of delivery largely remain an instructor-led approach overlooking the needs of learners and potential employers. This paper presents a learner-centric investment management course known as Student-Managed Investment Course (hereafter, SMIC). It elucidates the structure, design and implementation of SMIC based on the principles of experiential learning. SMIC has been organised to create a conducive environment for the emergence of varied experiences and encourage reflections among students on the theory and practice of investment finance. The unique feature of the course is real-time exposure to investment activity in the Bombay Stock exchange/National Stock exchange, which helps students observe and grasp the nuances of capital market functioning and to acquire requisite skills for financial decision-making. This document on SMIC has a value in being a useful guide for other business schools in India for adopting a learner-centric approach to investment management. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to examine the behavior of the stock market returns in the different days of the week and different months of the year in accordance with the Islamic calendar. Further, the study estimates the risk-adjusted returns to test the performance of the indices during the Ramadan and non-Ramadan days. Finally, the study investigates the impact of Ramadan on the returns and the volatility of the stock market indices in India.Design/methodology/approach Initially, the study applies the Ordinary Least Square method to test the day-of-the-week and the month-of-the-year effect of the common and Shariah indices. Next, the study employs the risk-adjusted measurement to examine the underperformance and over-performance of the indices for both the periods. Finally, the study estimates the GARCH (1,1) and GJR-GARCH (1,1) models to observe the impact of Ramadan on the returns and the volatility of the Shariah indices in India.Findings The study finds that an average return of the indices during the Ramadan days are higher than non-Ramadan days. Further, the average returns of the Shariah indices are significantly higher on Wednesday than other days of the week. In addition, the highest and significant mean returns and mean risk-adjusted returns of the indices during the Ramadan days are observed. Finally, the study finds an evidence of the Ramadan effect on the returns and volatility of the indices in India.Originality/value The study observes evidence that the Ramadan effect influences the Shariah indices, but not the common indices in the stock market of the non-Muslim countries. It indicates that the Ramadan creates the positive mood and emotions in the investors buying and selling activities. The study suggests that investors can buy the shares before Ramadan period and sell them during the Ramadan days to get an abnormal return in the emerging markets. [ABSTRACT FROM AUTHOR]

This research is an extension of our previous work [Debnath and Srivastava (2021)]. In that paper, we designed a portfolio based on data taken from National Stock Exchange (NSE), India, during 1 January 2020 to 31 December 2020 and performance of that portfolio in real-life situation was examined during 1 January 2021 to 21 May 2021 assuming investments were made according to the proposed model. We observed that our proposed portfolio was efficient enough in that period to beat the performance of most of the in-demand mutual funds. It was also conjectured that this portfolio would be sustainable post the second wave of COVID-19 in India. In the present paper, our aim is to validate this conjecture. Here, we examine the performance of this portfolio during the period 1 January 2021 to 18 October 2021 using the same previous data set. We also investigate the performance of this portfolio if it was blindly adopted without applying the stock selection methodology during 1 January 2019 to 31 December 2019. Using paired t-test between the difference of means of the performances in the year 2019 and the year 2021, we show that the performance in 2021 was significantly enhanced because of selecting the stocks applying our proposed model. [ABSTRACT FROM AUTHOR]

The Markowitz portfolio optimization model, popularly known as the Mean-Variance model, assumes that stockreturns follow normal distribution. But when stock returns do not follow normal distribution, this model wouldbe inadequate as it would prescribe sub-optimal portfolios. Stock market literature often deliberates that stock returns are non-normal. In such context the Markowitz model would not be sufficient to estimate the portfolio risks. The purpose of this paper is to expand the original Markowitz portfolio theory (mean-variance) via adding the higher order moments like skewness (third moment about the mean) and kurtosis (fourth moment about the mean) in the return characteristics. The research paper investigates the impact of including higher moments using multi-objective programming model for portfolio stock selection and optimization. The empirical results indicate that the inclusion of higher moments had a considerable impact in estimating the returns behavior of portfolios. The portfolios optimized using all the four moments, generated higher returns for the given level of risk in comparison to the returns of the Markowitz model during the study period 2000-2011. The results of this study would be immensely useful to fund managers, portfolio managers and investors as it would help them in understanding the Indian stock market behavior better and also in selecting alternative portfolio selection models. [ABSTRACT FROM AUTHOR]

Venture capitalists (VCs) flourish on the ability to add funds to their kitty across nations. Consequently, VCs' ability to convince Limited Partners (LP), who are their primary source of financing, plays a critical role in the venture capital investment growth in any economy. However, it is not easy to rake in capital from an investor. LPs assess the market conditions carefully before making their capital available to the VCs. This paper examines the macro-economic variables that influence the supply of money to venture capital funds in emerging economies such as India from an LPs perspective. The empirical analysis using Autoregressive-Distributed Lag (ARDL) approach reveals that supply of capital to the VC funds in India is influenced by macro variables as well as past investment behaviours. Macro-variables such as GDP growth, interest rate spread, global liquidity, and inflation rate significantly influence the supply of capital to the VC funds in India. However, stock market liquidity does not influence the supply side of the venture capital investment. Our analysis reveals that VCs' fund raising in India is highly influenced by their past investment relation with the LPs. [ABSTRACT FROM AUTHOR]

Fluctuations in the stock market can have an intense economic impact on the economy. This paper studies the inter-linkages between select stock markets. Daily closing levels of the benchmark indices are taken for a period of 15 years. The stationarity of the series has checked by applying line charts and unit-root test. Granger's causality model and Vector Auto Regression (VAR) model are performed to identify the integration among the markets chosen for study. The series was found to be stationary. Granger's causality indicated that there is a causation effect by some of the markets uni-directionally. The results of Granger Causality test indicate a unidirectional causality from the Indian Market to Canada and China. In the reverse direction, Korea causes movements in the Indian markets. [ABSTRACT FROM AUTHOR]

Purpose - The purpose of this paper is to estimate time-varying conditional volatility, and examine the extent to which trading volume, as a proxy for information arrival, explain the persistence of futures market volatility using National Stock Exchange S&P CRISIL NSE Index Nifty index futures. Design/methodology/approach - To estimate the volatility and capture the stylized facts of fat-tail distribution, volatility clustering, leverage effect, and mean-reversion in futures returns, appropriate ARMA-generalized autoregressive conditional heteroscedastic (GARCH) and ARMA-EGARCH models with generalized error distribution have been used. The ARMA-EGARCH model is augmented by including contemporaneous and lagged trading volume to determine their contribution to time-varying conditional volatility. Findings - The paper finds evidence of leverage effect, which indicates that negative shocks increase the futures market volatility more than positive shocks of the same magnitude. In addition, the results indicate that inclusion of both contemporaneous and lagged trading volume in the GARCH model reduces the persistence in volatility, but contemporaneous volume provides a greater reduction than lagged volume. Nevertheless, the GARCH effect does not completely vanish. Practical implications - Research findings have important implications for the traders, regulatory bodies, and practitioners. A positive volume-price volatility relationship implies that a new futures contract will be successful only to the extent that there is enough price uncertainty associated with the underlying asset. Higher trading volume causes higher volatility; so, it suggests the need for greater regulatory restrictions. Originality/value - Equity derivatives are relatively new phenomena in Indian capital market. This paper extends and updates the existing empirical research on the relationship between futures price volatility and volume in the emerging Indian capital market using improved methodology and recent data set. [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]

This paper examines if the Indian stock market moves with other markets in Asia and the United States in an era of capital market reforms and the sustained interest of foreign investors in that market. By using techniques of cointegration, vector autoregression, vector error-correction models, and Granger causality, we find that, though there is definite information leadership from the U.S. market to all Asian markets, the U.S. indexes do not uniquely influence the integration of Asian markets, while Japan is found to play a unique role in the integration of Asian markets. The U.S. market is seen not only to influence, but also to be influenced by information from most of the major Asian markets. The Indian stock return in recent times is definitely led by major stock index returns in the United States, Japan, as well as other Asian markets, such as Hong Kong, South Korea, and Singapore. More important, returns on the Indian market are also seen to exert considerable influence on stock returns in major Asian markets. [ABSTRACT FROM AUTHOR]