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This paper examines whether the Covid-19 pandemic has had a homogeneous or heterogeneous effect on stock returns in India. We consider panel data by using 1,318 companies that are listed on the National Stock Exchange of India. We find that the daily growth rate in Covid-19 cases and Covid-19 deaths are negatively associated with stock returns. Further, we observe that the average stock returns during Lockdown 2 are positive and highly significant, while the returns during Lockdowns 3 and 4 are negative. Moreover, our results show that the chemical, technology, and food and beverage industries earn higher returns. In contrast, the banking and finance, automotive, services, and cement and construction industries yield lower returns for the overall period. Interestingly, all industry groupings in this study earn a positive return during the lockdown period. In particular, the chemical, technology, automotive, metals and mining, and food and beverage industries provide higher returns during the lockdown period. Finally, this study supports the claim that the Covid-19 pandemic has had a heterogeneous effect in the Indian stock markets. [ABSTRACT FROM AUTHOR]

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

This paper empirically investigates the impact of COVID‐19 on the volatility of stock prices in India with the help of a generalized autoregressive conditional heteroscedasticity model. Daily closing prices of stock indices, Nifty and Sensex from September 3, 2019 to July 10, 2020 has been used for the analysis. Further, the study has been attempted to make a comparison of stock price return in pre‐COVID‐19 and during COVID‐19 situation. Findings reveal that the stock market in India has experienced volatility during the pandemic period. While comparing the result during COVID period with that of the pre‐COVID, we found that the return on the indices is higher in the pre‐COVID‐19 period than during COVID‐19. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to explore the immediate proactive corporate social responsibility (CSR) efforts undertaken by select organizations in India in response to the coronavirus (COVID-19) pandemic and the approach they have adopted toward it. Design/methodology/approach: Semi-structured interviews were conducted with 27 senior managers across top Bombay Stock Exchange indexed organizations from the manufacturing and services sector in India during the national COVID-19 pandemic lockdown between March and June 2020. Manual content analysis and the Gioia method were used to arrive at the insights. Findings: Results of the analysis showcase the spirited immediate CSR measures undertaken by the select organizations in the broader interests of the community at large. The study also highlights the need for a paradox approach toward CSR strategy. Research limitations/implications: Given that the present study adopts an exploratory qualitative research design, the scope for generalization is rather limited. Practical implications: This paper classifies COVID-19 related initiatives undertaken by selected few top organizations in India and attempts to justify the need to opt for a paradox approach toward CSR strategy. Originality/value: To the best of the author's knowledge, this is one of the first few studies to have attempted to put forth a dialog at the intersection of COVID-19 and CSR with rich insights gained from qualitative data collected during India's intense lockdown period and offering a different perspective with the inclusion of paradox theory into the discussion. [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]

A plethora of information on indices of popular bourses across the globe has heisted investors off their mental peace to give them nightmares. Operational nuances and informed interpretations of the movement in the stock market indices of bourses operating at the international level, regional level, and national level and of those of sector specific have always been a daunting task to myriad of investors actively functioning in the market arena. This paper seeks to demystify the modus operandi of developing indices of bourses using pragmatic episodes and thereby aid the investors in comprehending the subtleties associated with it and the niceties involved in its dexterous maneuvering and making robust decisions for triumphant innings in the bourses. This paper provides model of insights in computation of stock market indices with techniques such as market capitalization weighted index, free-float weighted index, price weighted index, equal weighted index, impact cost, and index management. [ABSTRACT FROM AUTHOR]

This paper examines the stock market volatility and FIIs for the period (2004 -- 2010). The volatility of NIFTY index influenced by the investment inflows of FIIs is modeled using a time series ARIMA approach. The empirical results calibrated through these models are analytic in several fronts. The paper further models and forecasts the index using the data set, where Foreign Institutional Investment (FII), Nominal Effective Exchange Rate (NEER) and Call money rate are considered as the exogenous variables. Finally, the empirical findings show that if the net FII flow is auto regressed with FII flow of various lag periods then it does not have significant influence on the monthly-volatility of the index. The paper also proposes the possible reasons supporting the empirical observations. [ABSTRACT FROM AUTHOR]

The objective of this paper is to determine the relationship between inflation rate and stock price indices (NSE Nifty). The duration of the study is from January 1, 2008 to March 31, 2019. The data is analyzed for cointegration and causality by using Johansen cointegration test, Vector Error Correction Model (VECM) and Granger causality test. For determining the relationship between the variables, Pearson correlation test has been used. The ADF test results show that the variables are non-stationary at level and are integrated of order one. The correlation results show a negative relationship between stock market indices and inflation rate in India. Johansen cointegration test results indicate cointegration between the variables. The Granger causality test shows that inflation rate does not affect the stock market indices, and stock market indices are not affected by the inflation rate. The VECM model and Wald test results show that there is no long run and short run causality between the variables. [ABSTRACT FROM AUTHOR]

The paper examines the presence of herd behavior in the S&P CNX Nifty 50 index of the National Stock Exchange of India, which arises out of the informational asymmetries found in the emerging markets around the globe. A price-based model with logarithmic cross-sectional deviation employing Kalman filter is used to measure the presence of herding. This study exposes the severe effects of herd behavior on the Nifty index. We have found highly significant herding in the Nifty index on a market-wide level during the period of 1997-2008. We also state that this type of behavior is decidedly exhibited by the market participants of the Nifty index, during the bull runs in the market and correspondingly less exhibited during the bear runs. Our work also examines the various events that took place during our sample period (May 1997-December 2008) and relates it to the course of herding in the Nifty index. [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]

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While most traditional science deals with supposedly predictable phenomena like gravity, electricity, or chemical reactions, Chaos Theory deals with nonlinear things that are effectively impossible to predict or control, like turbulence, weather, the stock market, our brain states, and so on. Hence, such processes focus on non-randomness, nonlinearity and chaotic characteristics. In recent times, such nonlinear dynamics and chaotic dynamics have augmented in the field of financial analysis. This paper studies the extent to which the daily return data from the Indian Stock Exchange indices (Nifty and Sensex) exhibit these nonlinear, non-random characteristics. The Hurst exponent in rescaled range analysis rejects the hypothesis that the index return series are random, independent and identically distributed. The BDS test provides evidence for nonlinearity. The results confirm the existence of fractal structure (i.e., selfsimilarity across different scales) in Nifty and Sensex. Basing on these results, technical analysis theory, i.e., Elliot Wave Theory, can also be justifiable. [ABSTRACT FROM AUTHOR]

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

This paper studies hedging effectiveness in Indian stock index futures market. The main focus is on various procedures to estimate time-varying and static optimal hedge ratios. For the S&P CNX Nifty futures contract 5 different econometric models that are employed. The data set used is from 2001-2008. Traditional OLS regressions, modified OLS viz. LTS, error correction model (ECM), vector error correction model (VECM) and multivariate generalized autoregressive heteroscedastic (M-GARCH) models are used to estimate hedge ratios, not only for mirror index underlying the futures contract but also for mutual funds. It is the first exhaustive study of its kind on the Indian stock index futures market and reveals that mutual funds tend to be a good proxy for market portfolios. Simple OLS seems to provide the best hedging effectiveness in terms of risk reduction for the Indian futures market. However, the use of more complex models like VECM cannot be sublimed as they provide more or less same hedging effectiveness. [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]

Indian capital market saw the launching of index futures and options on NSE on June 12, 2000 and June 4, 2001 respectively. This launching of derivatives in Indian stock markets was perceived to increase volatility in the stock market by some researchers, at the same time some other researchers anticipated decline in volatility. This paper tries to study whether the Indian stock markets show some significant change in the volatility after the introduction of derivatives trading. The study has been undertaken with a comprehensive daily data set from January 1, 1996 to March 31, 2007. To measure the volatility GARCH (1, 1) model has been used. The results show that the presence of derivatives markets on S&P CNX Nifty have declined the volatility marginally, and less reduction of volatility in spot market seems that presence of uninformed traders' activities in derivatives market. Marginal volatility reduction in spot market is associated with the increase in market efficiency and improved market depth in post derivatives period. This identification rejects "destabilizing forces hypothesis and supports "market completion" hypothesis on derivatives. [ABSTRACT FROM AUTHOR]

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

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

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

This paper presents an empirical study on predictability in the Indian stock market, based on cointegration analysis involving a stock price index and relevant macro and financial variables. This exercise has been done separately for each of the three most important stock indices viz., BSE SENSEX, BSE 100 and NIFTY. Following essentially Johansen's approach, our findings based on the trace and maximum eigenvalue tests indicate that there exist cointegrating relations involving a stock index and the following macro variables viz., domestic industrial production, consumer price index, nominal exchange rate, foreign direct investment and long-term interest rate. Further, the cointegrating relations corresponding to each of the three stock indices involve the same set of macroeconomic variables as stated above. None of the other variables considered in this study viz., and the financial ratios has been found to be significantly involved in the cointegrating regressions. [ABSTRACT FROM AUTHOR]

This paper analyses the profitability of moving average based trading rules in the Indian stock market using four stock index series. The study finds that most technical trading rules are able to capture the direction of market movements reasonably well and give significant positive returns both in long and short positions. But these returns cannot be exploited fully due to real world transaction costs. Although the transaction cost has come down over the years, various components of transaction costs due to the bid-ask spread, brokerage, etc. will never be zero. The trading rules based on short term moving averages may be able to detect trends in financial series very quickly, but those rules also generate a large number of trades causing higher transaction costs. Thus technical traders have to pay more attention to minimizing transaction costs while choosing a trading rule. Nevertheless, profit opportunities from technical analysis continue to remain an interesting and debatable issue in the Indian stock market. [ABSTRACT FROM AUTHOR]

The segmentation scales derived from the systematic risk contributions of the countries to the world market index indicate, some degrees of segmentation in global equity markets. However, there is an increased trend toward integration. The beta coefficients and cross correlations of dollar returns verify these findings, We observe a contagion effect in 1990s and cointegration effect for developed countries and emerging markets within their own subsets. The degree of integration for emerging markets is much less than that of developed countries. Emerging markets still keep their importance for the global equity portfolios. The paper show that the degree of segmentation in the global equity markets across countries and cross developed continues vs. emerging markets are not the same and benefits of global diversification still continue. [ABSTRACT FROM AUTHOR]

This paper suggests a systematic approach to studying predictability and nonlinear dependence in the context of the Indian stock market, one of the most important emerging stock markets in the world. The proposed approach considers nonlinear dependence in returns and envisages appropriate specification of both the conditional first- and second-order moments, so that final conclusions are free from any probable statistical consequences of misspecification. To this end, a number of rigorous tests are applied on the returns, based on four major daily indices of the Indian stock market. It is found that the Indian stock market is predictable, and this observed lack of efficiency is due to serial correlation, nonlinear dependence, day-of-the week effects, parameter instability, conditional heteroskedasticity (GARCH), daily-level seasonality in volatility, the short-term interest rate (in some subperiods of some indices), and some dynamics in the higher-order moments. [ABSTRACT FROM AUTHOR]

This paper investigates the properties of realized volatility and correlation series in the Indian stock market by employing daily data converting to monthly frequency of five different stock indices from January 2, 2006 to November 30, 2014. Using non-parametric estimation technique the properties examined include normality, long-memory, asymmetries, jumps, and heterogeneity. The realized volatility is a useful technique which provides a relatively accurate measure of volatility based on the actual variance which is beneficial for asset management in particular for non-speculative funds. The results show that realized volatility and correlation series are not normally distributed, with some evidence of persistence. Asymmetries are also evident in both volatilities and correlations. Both jumps and heterogeneity properties are significant; whereas, the former is more significant than the latter. The findings show that properties of volatilities and correlations in Indian stock market have similarities as that show in the stock markets in developed countries such as the stock market in the United States which is more prevalent for speculative business traders. [ABSTRACT FROM AUTHOR]

This paper seeks to analyze the dynamical structure of the Indian stock market by considering two major Indian stock market indices, namely, BSE Sensex and CNX Nifty. The recurrence quantification analysis (RQA) is applied on the daily closing data of the two series during the period from January 2,2002, to October 10,2013. A Rolling Window of 100 and step size 21 are applied in order to see how both the series behave over time. The analysis based on three RQA measures, namely, % determinism (DET), laminarity (LAM), and trapping time (TT), provides conclusive evidence that the Indian equity market is chaotic in nature. Evidences for phase transition in the Indian equity market around the time of financial crisis are also found. [ABSTRACT FROM AUTHOR]

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

The onset of the COVID-19 pandemic and lockdown announcements by governments have created uncertainty in business operations globally. For the first time, a health shock has impacted the stock markets forcefully. India, one of the major emerging markets, has witnessed a massive fall of around 40% in its major stock indices' value. Therefore, we examined the short-term impact of the pandemic on the Indian stock market's major index (NIFTY50) and its constituent sectors. For our analysis, we used three different models (constant return model, market model, and market-adjusted model) of event study methodology. Our results are heterogeneous and largely depend on the sectors. All the sectors were impacted temporarily, yet the financial sector faced the worst. Sectors like pharma, consumer goods, and IT had positive or limited impacts. We discuss the potential explanations for the same. These results may be useful for investors in safeguarding equity portfolios from unforeseen shocks and making better investment decisions to avoid large, unexpected losses. [ABSTRACT FROM AUTHOR]

The foreign exchange market and the stock markets in India are among the most important financial markets that are constantly being monitored by the investors, regulators, and the policy-makers. The present study makes an attempt to investigate whether any causal relationship exists between the foreign exchange market and the stock markets in India. The BSE and the NSE annual returns have been used as a substitute for the stock prices, while the currency rate of Indian Rupee against the US Dollar (INR/USD) has been considered as a substitute for the exchange rate exposure covering a time-period of 20 years, from 1 January 2000 to 31 December 2019. The applications of the unit root or Augmented Dickey-Fuller test, Johansen cointegration, and Granger causality tests, as employed in the present study, examined the relationship between the USD/INR exchange rates and Indian stock market indices (SENSEX and NIFTY-50). The Granger causality test indicated that both the BSE and NSE stock indices granger cause INR/USD exchange rates. However, the INR/USD rates do not granger cause the BSE and NSE stock returns. The study has portrayed a unidirectional relation between the stock indices and INR/USD rates, but a bi-directional relation between the BSE and NSE stock returns. [ABSTRACT FROM AUTHOR]

We analyze daily prices of 42 stocks listed in the Nifty50 index of National Stock Exchange of India from 2006 to 2019. The Nifty50 is one of the leading indexes of Indian the stock market which comprises 50 dominant companies. We use well established techniques such as random matrix theory, complex network analysis, hierarchical clustering, diffusion entropy, and conditional entropy to study the correlation among stocks and topological properties of the Indian stock market. We perform the static and dynamic analysis of the Nifty50 stocks to extract useful information from them. In the static period analysis, we consider three sub periods i.e. before, during and the subprime crisis of 2008. In dynamic period analysis, we consider overlapped and non-overlapped time windows of one year with varying shifts. We study the effect of 'global events' (such as the sub-prime crisis of 2008 and the Chinese crisis) and 'local events' (such as General elections 2009, Assembly elections in 7 states, General elections 2014 and Demonetization in India). We find that global and local extreme events affect the correlations among Nifty50 stocks of the Indian stock market. The analysis performed in this paper may be helpful in the development of different indicators of systemic risks in India. • We study 42 companies of the Nifty50 index of Indian stock market from 2006 to 2019. • Correlations and complexity of this market is explored by using different techniques. • Network theory has been used to study changes in the networks in response to crisis. • We observe bull market effects before and after crisis in diffusion entropy analysis. • Global and local extreme events significantly change the correlations and networks. [ABSTRACT FROM AUTHOR]

A robust small and medium enterprise (SME) sustainability disclosure index (SSDI) is developed to explore sustainability reporting (SR) practices across manufacturing SMEs listed in Bombay Stock Exchange, India. Content analysis is used to analyse the SR disclosures of twenty-nine manufacturing SMEs. The results indicate dearth SR practices particularly in the environmental and social dimension. A dimensional imbalance is identified where environmental and social disclosures are limited to purely descriptive narrations without any quantified information. The study tries to bridge the gap by providing SSDI as a mechanism to discharge and evaluate sustainability practices in SMEs. The authors recommend improving SR practices in SMEs (manufacturing) through strong policies and regulations. [ABSTRACT FROM AUTHOR]

In this paper, we apply the methods, Multifractal Detrended Fluctuation Analysis (MF-DFA) and Multifractal Detrended Cross-Correlation Analysis (MF-DXA) to study the auto correlation/cross-correlation behaviour and multifractal characteristics on twenty three stock market indices of Department of Public Enterprises (DPE), India. The auto correlation and cross-correlation have been measured from the Hurst scaling exponents and the singularity spectrum quantitatively. From the calculated power law scaling exponents we observe the volume and price-volume change time series possess strong anti-persistent behaviour. The price change of different time series shows persistent, stochastic and anti-persistent behaviour. We also observe the existence of multifractal characteristics in all price, volume and price-volume change time series. The price changes in the time series shows high complexity compared to volume and cross correlated price-volume. • We have studied the auto-correlation and cross-correlation on DPE, India. • The MF-DFA and MF-DXA methods applied on price and volume change time series. • We found the existence of multifractal behaviour in all time series. • Complexity parameters were used to find the strength of the multifractality. [ABSTRACT FROM AUTHOR]

Market liquidity ensures the marketability of security and is an indispensable feature of stock markets. Previous studies have emphasized the role of stock market liquidity in empirical finance. However, they have inadequately explored its multidimensional nature. This study eliminates the ambiguities related to market liquidity by precisely measuring it by using popular and proven liquidity measures. As such, the present study aims to evaluate market liquidity in terms of depth, breadth, tightness, and immediacy in the Indian equity market and also identifies crucial interdependencies between liquidity dimensions. The study selects 500 stocks constituting the NIFTY 500 index of the National Stock Exchange, India, as of 26th May 2019. The data on trading volume, bid price, ask price, the number of shares outstanding, closing share prices were retrieved for the period from 1st April 2009 to 31st March 2019. The study employs Share Turnover, Amihud Illiquidity Ratio, Relative Quoted Spreads, and Coefficient of Elasticity of Trading for liquidity measurement. The Vector Auto-Regressive (VAR) model is used to establish the simultaneous relationships between liquidity dimensions. The analysis is conducted at the aggregate market level as well as across turnover based stock groups divided based on their rankings in terms of stock specific share turnover. The empirical results evidenced the presence of consistent depth, strong breadth, and immediacy but lower tightness in the Indian equity market. The market depth and tightness appear to be relevant in determining dimensional interdependencies. Also, less frequently traded stocks exhibit higher illiquidity in the wake of lower tightness. The findings of this study will assist the investors to wisely understand the multifaceted nature of market liquidity and base their trading decisions accordingly. Moreover, the regulators of the stock exchange can devise liquidity enhancing policies based on the directional movements among liquidity dimensions. [ABSTRACT FROM AUTHOR]

The present study investigates dynamics of contagion and spillover of volatility amongst stock markets of five economies ; US, UK and Japan and two Asian emerging economies viz. India and China. The period of study is eleven years; January 1, 2009-December 31, 2019 and the data is daily closing prices of their stock market indices. The study makes a distinction between contagion and spillover whereby a shock is considered spillover if its impact is seen with a lag of one period only, while contagion is a residual transmission (Masson, P (1998); Dungey, M and Martin, V L (2007)). The results revealed substantial contagion and information flows from one market to another, be it developed or emerging. Further although US markets still decides the direction of markets, the importance of other markets has increased over the years. Further, US market on its own now appears to look for clues from both developed and emerging markets including India and China. The two emerging markets of Asia, India and China observe a lot of co-movement in returns with spillovers being linked to the developed markets. The study also tested for pre-conditions of stationarity, autocorrelation and heteroscedasticity. [ABSTRACT FROM AUTHOR]

As far as individual stock market investors are concerned, majority of them invest in blue chip and top companies in both the major stock exchanges namely BSE and NSE. As a result normally companies with small capitalization remain less traded due to less investors' attraction. Thus, the present study especially focused on the analysis of stock price performance, market capitalisation, and trading values with respect to the selected companies from S&P small cap index. The study is aimed at exploring the concept of market capitalisation, analyzing the comparative position of selected companies from S&P small cap index and offer gross interpretations based on the analysis of comparatively bigger companies from the said sector. The present study indicates the trend in the share prices of small cap companies in the given period. It is observed that even though the market has fallen substantially, surprisingly shares of many small cap companies have moved upwards. Some companies have posted very decent return in the volatile market may be due the profitability, good future prospects, etc. Depending upon their unique position, the small cap companies have potential to transform themselves into tomorrow's mid or large cap. As far as the information about share prices, market capitalisation, and trading values of the selected companies is concerned, all the companies have shown fabulous increase over a period of ten years as well as shown their strength and sustainability by reporting increase in share price, market capitalisation and trading values in spite of great fall in SENSEX on 24th August 2015. Thus, it can be very much concluded that comparatively bigger companies from small cap sections/index have shown good performance on stock exchange over a period of time and also shown their capacity to progress towards mid cap section in coming years and towards large cap section in long term. [ABSTRACT FROM AUTHOR]

We test the random-walk hypothesis for the Indian stock market by applying three unit root tests with two structural breaks. We find that unit root tests that allow for two structural breaks alone are not able to reject the unit root null; however, a recently developed unit root test that simultaneously accounts for heteroskedasticity and structural breaks finds that the stock indexes are mean reverting. Our results point to the importance of addressing heteroskedasticity when testing for a random walk with high-frequency financial data. [ABSTRACT FROM AUTHOR]

The study investigates the relationships between exchange rate and stock price over the period January 2007 to March 2014. Index National Stock Exchange, namely, NIFTY is used as indicator of stock price. Johansen's co-integration and Granger causality test have been applied to explore the long-run and short-run equilibrium relationship between exchange rate and stock price. The analysis reveals that exchange rate and stock price are co-integrated and, hence, a long-run equilibrium relationship exists between them. It is observed that the exchange rate and NIFTY as indicators of stock price are positively related to each other. The exchange rate is found to be significant in determining stock price and stock price significantly affects exchange rate. In the Granger-causality sense, exchange rate Granger-causes stock price and stock price Granger-causes exchange rate, or there is bi-directional causality between exchange rate and stock price in both long run and short run. [ABSTRACT FROM AUTHOR]

Investing activities that adheres to Islamic restrictions of not investing in socially harmful businesses is known as Islamic investments. Islam also puts a check on human behavior and manners that are harmful for society such as gambling, short-selling, cheating etc. It should be noted that there is nothing 'Islamic' about Shari'ah compliant indexes, as most of the underlying companies are not from the Muslim countries. These compliant companies just happen to pass primary business screens (akin to social-ethical indexes) and financial screens (eliminates companies with high debt, high account receivable translating sales into earnings, and too much non-operating interest income). Today Shari'ah compliant indexes are operating in seventy four countries around the world including India, of these only thirteen countries are Islamic countries. In most of the cases in comparison to conventional indexes they outperform. In India the BSE in late 2010, launched the BSE Shari'ah Index and subsequently NSE too, has its Shari'ah Index, the S&P CNX Nifty Shari'ah. [ABSTRACT FROM AUTHOR]

A simple option pricing model is suggested based on correlation of underlying stock with actual market behavior as reflected by market index, thereby market factor coefficient to enable the traders to quote the prices. The simplicity and ease of the proposed model may appeal to the traders, operators and other market participants. Daily option Prices at different strike prices for the underlying stocks are calculated by applying daily Market Factor coefficient, exercise price, strike price and time to maturity. Model is tested with call option prices of select underlying stocks which constitute Nifty index of the National Stock Exchange of India. Option prices produced by the proposed model are close to the actual price for varied range of strike prices. The Model works perfectly to call in-the-money, at-the-money, and near out-of-money. Pricing difference is tested through tools such as Mean Error, percentage mean error, Root Mean Square, Thiel's U statistic. Regression analysis is also explored with traded prices on Call option prices obtained by the model. The simplicity and workability of the proposed model are its main advantages over the existing models. [ABSTRACT FROM AUTHOR]

The present study attempts to examine the random movements in stock indices in the Indian equity market. It tests the random walk hypotheses in daily, weekly and monthly returns of six Indian stock market indices from January 2000 to October 2009. The indices considered for the purpose of the study include Nifty, CNX Nifty Junior, NSE 500, SENSEX, BSE 100 and BSE 500. The study uses Jarque-Bera (JB) Test for testing normality in return series. It also applies Box Pierce Q-Statistics and Ljung-Box (LB) statistics, and Augmented Dickey-Fuller (ADF) test to test whether return series follow random walk or not. The results indicate that there are no random movements in share indices. However, when we apply Lo and MacKinlay (1988) variance ratio test under the assumptions of both homoskedasticity and heteroskedasticity, we observe contradictory results. It is also found that sometimes heteroskedasticity is the source of non-random behavior in share indices. [ABSTRACT FROM AUTHOR]