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Using the S&P green bond index (RSPGB), this study attempts to unravel the connectedness of the green bond with energy, crypto, and carbon markets. We use MAC global solar energy index (RMGS) and ISE global wind energy index (RIGW) as proxies of the energy market. In addition, we consider Bitcoin and the European energy exchange carbon index (REEX) for the cryptocurrency, and carbon market, respectively. Using the daily data from October 1, 2015, to December 13, 2021, of these constituent markets, we employ Diebold Yilmaz (2012), Barunik and Krehlik (2017), and wavelet coherence. The result reveals that the energy market (RMGS) has the highest connectedness derived from other asset classes, and bitcoin (RBTC) has the least connectedness. In addition, we note that risk transmission is heterogeneous in different scales as the short period has less connectedness than the medium and long run. Hence, the overall diversification opportunity among green bonds, energy stock, Bitcoin, and the carbon market is more in the short-run than in the medium and long-run. Surprisingly, there is no lead-lag relationship among these markets. This study provides insights to investors, policymakers, and portfolio managers.

This paper examines the dynamic connectedness between green bonds and OECD financial markets of European countries. The study is conducted on daily price of green bonds and selected European stock markets from January 27, 2015, to August 4, 2021. Top ten European countries namely Luxembourg, Switzerland, Norway, Denmark, Germany, Netherlands, Iceland, Austria, Sweden, and Belgium are included within the OECD economies. The study uses Diebold and Yilmaz and Barunik & Krehlic tests to examine the connectedness between the economies and green bonds in short, medium, and long term. Result exhibits volatility across all frequency cycles. Brussel Stock Exchange and Euronext Amsterdam are identified as high-risk markets in the OECD European market. Evidence emerging from this study advocate the inclusion of green bonds in these financial markets for shorter time periods only. Results from this study are expected to have practical implications for portfolio managers, investors, and market regulators, suggesting incorporation of green bonds in investor portfolio for efficient diversification of risk.

There are studies available that study the influence of corruption on economic growth, but no existing literature studies the asymmetric relationship in context to BRICS countries. In this study, we try to fill the gap in the literature by studying the symmetric and asymmetric association between corruption, political stability and economic growth in BRICS economies where gross fixed capital formation and final consumption expenditure are considered additional variables. Further, we employ panel non-linear autoregressive distributed lag model from 1996–2018. In the long run, the non-linear estimation results confirm an asymmetric relationship while all variables show the asymmetric relationship in the short run. Additionally, the study has employed Dumitrescu– Hurlin (2012) test to find the direction of causality among the variables. The test confirms the causality in particular variables taking economic growth as dependent variable and the decomposed explanatory variables. The article’s findings provide new insight into the relationship between corruption, political stability and economic growth. JEL Codes: D73, F35

PurposeThis study unravels an attempt to investigate the dynamic connectedness of agri-commodity (wheat) of Russia with 10 financial markets of wheat importing counties during the Russia–Ukraine invasion.Design/methodology/approachThis study took the daily prices of Wheat FOB Black Sea Index (Russia) along with stock indices of 10 major wheat-importing nations of Russia and Ukraine. The time frame for this study ranges from February 24, 2022 to July 31, 2022. This time frame was selected since it fully examines all of the effects of the crisis. The conditional correlations and volatility spillovers of these indices are predicted using the DCC-GARCH model, Diebold and Yilmaz (2012) and Baruník and Křehlík (2018) models.FindingsIt is found that there is dynamic linkage of agri-commodity of with stock markets of Iraq, Pakistan and Tanzania in short run while stock markets of Egypt, Turkey, Bangladesh, Pakistan, Brazil and Iraq are spilled by agri-commodity in long run. In addition, it documents that there is large spillover in short run than medium and long run comparatively. This signifies that investors have more diversification opportunity in short run then long run contemplating to invest in these markets.Originality/valueTo the best of the authors’ understanding this is the first study to undertake the dynamic linkage of agri-commodity (wheat) of Russia with financial market of select importing counties during the Russia–Ukraine invasion.

This paper examines the dynamic linkages of green bond with the energy and crypto market. The S&P green bond index (RSPGB) is used as a proxy for the green bond market; S&P global clean energy index and ISE global wind energy (RIGW) are used as proxies for the renewable energy market, and; Bitcoin and Ethereum (RETHER) are used as the proxies of the crypto market. The daily prices of these constituent series are collected using Bloomberg from October 3, 2016 to February 23, 2021. We undertake an empirical analysis through the application of three key tests, namely: dynamic conditional correlation (DCC), Diebold and Yilmaz (Int J Forecast 28(1):57–66, 2012. 10.1016/j.ijforecast.2011.02.006), Baruník and Křehlík (J Financ Econom 16(2):271–296, 2018. 10.1093/jjfinec/nby001) model. The DCC reveals no dynamic linkages of volatility from the green bond to the energy and crypto market in the short run. Referring to Diebold and Yilmaz (2012), it dictates that the green bond (RSPGB) is a net receiver while the energy market (RIGW) and cryptocurrency (RETHER) are the largest and least contributors to the transmission of the volatility. Additionally, the Baruník and Křehlík (2018) model confirmed that the magnitude of the total spillover is high in more prolonged than shorter periods, suggesting reduced diversification opportunities. Overall, the present study exemplifies the significance of the green bond market as protection against risk.

This study investigates the relationship between the Indian stock market price behaviour and macroeconomic variables. The proxy for the Indian stock market is the BSESENSEX while Foreign Reserve, Exchange Rate (Indian vs. US Dollar) and CPI are proxies for the macroeconomic variables. The Johansen Cointegration Test and the Vector Error Correction Model (VECM) on monthly data collected from websites of Reserve Bank of India and Bombay Stock Exchange within the time period of January 2000 and February 2020 have been applied. We observe a contradiction between the results of trace statistics and the maximal eigenvalue of the Johansen Cointegration. The -trace statistics of cointegration allude to the long-run association between the Indian stock market and its constituent macroeconomic variables. The VECM is then applied to examine the long-run and short-run causalities and the results reveal the same. This study has profound implications for investors to diversify their portfolio, considering the impact of the constituent selected macroeconomic variables in the short run and long run. JEL Codes: B22, J11, R53

The paper aims to analyse the impact of the COVID outbreak on the currency market. The study considers spot rates of seven major currencies (i.e., EUR/USD, USD/JPY, GBP/USD, AUD/USD, USD/CAD, USD/CHF, and CHF/JPY). To capture the impact of the outbreak on returns and the volatility of returns of seven currencies during pandemic, the study has segregated in two window periods (i.e., pre- [1st Jan 2019 to 31st Dec, 2019] and post-outbreak of COVID-19 [1st Jan, 2020 to 22nd Dec, 2020]). The study has applied various methods and models (i.e., econometric-based compounded annual growth rate [CAGR], dummy variable regression, and generalized autoregressive conditional heteroskedasticity [GARCH]). The result of the study captures the negative impact of the COVID-19 pandemic on three currencies-USD/JPY, AUD/USD, and USD/CHF-and positive significant impact on EUR/USD, GBP/USD, USD/CAD, and CHF/JPY. Investors can take short position in these while having long position in other currencies. The inferences drawn from the analysis are providing insight to investors and hedgers. Copyright © 2022, IGI Global.

The present study examines the impact of corporate social responsibility (CSR) on competitive performance of Indian companies. The proxies for the CSR and competitive performance are CSR expenditure and price to book ratio, respectively. The study is based on the 32 companies awarded by CII-ITC Sustainability Awards during 2010–2011 to 2017–2018. After collecting the data of price to book ratio, leverage, CSR expenditure and revenue of entire sample companies, panel data regression has been used to observe the impact of CSR on competitive performance. The results reveal insignificant relationship between CSR and competitive performance. It is noticed that firms do not have a CSR strategy that unifies the diverse range of a company’s philanthropic initiatives under one umbrella. Hence, the present study suggests to embed CSR into the company’s core business strategy.

PurposeSeveral empirical studies have proven that emerging countries are attractive destinations for Foreign Institutional Investors (FIIs) because of high expected returns, weak market efficiency and high growth that make them attractive destination for diversification of funds. But higher expected returns come coupled with high risk arising from political and economic instability. This study aims to compare the linear (symmetric) and non-linear (asymmetric) Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models in forecasting the volatility of top five major emerging countries among E7, that is, China, India, Indonesia, Brazil and Mexico.Design/methodology/approachThe volatility of financial markets of five major emerging countries has been empirically investigated for a period of two decades from January 2000 to December 2019 using univariate volatility models including GARCH 1, 1, Exponential Generalized Autoregressive Conditional Heteroscedasticity (E-GARCH 1, 1) and Threshold Generalized Autoregressive Conditional Heteroscedasticity (T-GARCH-1, 1) models. Further, to examine time-varying volatility, the distinctions of structural break have been captured in view of the global financial crisis of 2008. Thus, the period under the study has been segregated into pre- and post-crisis, that is, January 2001–December 2008 and January 2009–December 2019, respectively.FindingsThe findings indicate that GARCH (1, 1) model is superior to non-linear GARCH models for forecasting volatility because the effect of leverage is insignificant. China has been considered as most volatile, whereas India is volatile but positively skewed and Indonesia is the least volatile country. The results can help investors in better international diversification of their portfolio and identifying best suitable hedging opportunities.Practical implicationsThis study can help investors to construct a more risk-adjusted returns international portfolio. Further, it adds to the scant literature available on the inconclusive debate on the choice of linear versus non-linear models to forecast market volatility.Originality/valueEarlier studies related to univariate volatility models are mostly applications of the models. Only few studies have considered the robustness while applying the models. However, none of the studies to the best of the authors’ searches have considered these models for identifying the diversification opportunity among the emerging countries. Hence, this study is able to derive diversification and hedging opportunities by applying wide ranges of the statistical applications and models, that is, descriptive, correlations and univariate volatility models. It makes the study more rigorous and unique compared to the previous literature.

The digital journey of learning has been of different perceptions to different communities. We study the perception of students regarding online learning during the lockdown period in three different communities of India i.e. rural, urban and metropolitan on the basis of survey of 411 students during lockdown period. Ten problem statements have been considered to be rated at Likert’s Five Scale. To check the reliability, Cronbach's α, to analyze the data- mean & standard deviation and to validate the results t-test and Post Hoc Test have been used. It is concluded that majority of students have smart phones in urban and metropolitan but neutral to learning while rural students prefer the conventional leaning. This study contributes to the new theory of the efficacy of digital learning as mode of learning in and after lock down period that will bring the attention of educational agencies, faculty members as well as policy makers towards the problems faced by the students in digital learning.

We examined the presence of women directors in top-level management and their effect on principal-principal conflict (PP) and principal-agent conflict (PA) on the firms listed on Indian stock exchange using a panel model approach. For analysis purpose, this study covers the sample of 75 companies belonging to various industries and listed in Bombay Stock Exchange Index, has been studied over thirteen financial years, i.e. from year 2006 to year 2019. This study uses panel data analysis, i.e. fixed effect model and random effect model. The proportion and presence (dichotomous) of women directors on top level management board is taken as the independent variable. Principal-principal conflict measured by assets utilization ratio (AUR), and principal-agent conflict is been measured by dividend payout ratio (DPR), are taken as dependent variable in this study. The prime results of this study using panel data analysis, i.e. fixed effect (FE) and random effects (RE) estimation models point towards no significant impact of the female director (proportion and presence) on the firm’s agency cost (PP and PA).

The study is about contributing to the ongoing discussion on the diversification opportunities for emerging markets with non-conventional asset class. The limited literature in the era of fourth industrial revolution motivates us to gauge diversification opportunities. This study is focusing on identifying diversification opportunities with a set of unique asset classes that are the proxies for Green Funds, FinTech and Artificial Intelligence-based index funds. The method and model applied in the study are time and frequency connectedness in a Wavelet Coherence, and for the robustness check—Network analysis has been applied. The originality of the study lies in identifying the impact of the outbreak of COVID-19. The results captured that FinTech-based asset was the most resilient asset class during the pre- and post-outbreak of COVID-19, followed by AI-based fund and finally by Green fund. Henceforth, FinTech provides superior diversification opportunities among all with MSCI Emerging Market. AI and Green funds are captured to be invested in the long term for diversification, whereas FinTech is suitable for both long- and short-term assets. The results are relevant for investors in emerging markets and for policymakers as well.

We examine the spillover effect from the Indian stock market to Mexico, Indonesia, Nigeria and Turkey (MINT) stock markets in order to check if suitable diversification opportunities are available to global portfolio managers investing in India. We apply Granger causality test, vector auto-regression (VAR) and dynamic conditional correlation (DCC)–MGARCH to investigate the level of integration between India and MINT economies. We observe bidirectional causality between India and Nigeria, unidirectional causality in Mexico and Indonesia, while no causality is found between India and Turkey. Our VAR results suggest that none of the MINT economies impact the return of the Indian stock market; rather returns of the Indian stock market are more affected by their own lagged values. Finally, by applying DCC–MGARCH, we observe that there is no volatility spillover from India to any of the MINT economies. We recommend that portfolio managers investing in the Indian economy may explore MINT economies as possible destinations to diversify their risk. Our study has implications for both academia and portfolio managers.

Financial literacy is an ability of individual to take considerable decisions in respect of the effective and efficient utilization of money. In present study, authors have presented an association of financial knowledge, financial behaviour and financial attitude towards the financial literacy level among working women in Delhi, India. The sample size of 394 working women from various public and private organizations of Delhi has been incorporated for the research. A structured questionnaire designed on a 5-point Likert scale has been used based on purposive sampling, and the goodness of fit is determined by analysis of moments structures (AMOS) by applying structural equation modeling approach (SEM). The association between three independent variables is investigated applying path analysis for hypothesis testing. The findings revealed that financial attitude and financial behaviour have strong association with financial literacy of working women than financial knowledge.

COVID-19 quickly spread all over the world and dramatically affected the financial markets in almost everycountry. Its spread created havoc in the market, and investors fearing risk suffereda significant amount of financialloss in a very short time. This article aims to analyze the impact of COVID-19 on stock markets in the top six affected countries based on the total number of cases confirmed. In addition, it also analyzes the stock market volatility caused by the virus and the abnormal returns generated by the markets during the pandemic. We employevent study methodology in different sub-periods to examine the most volatile event periods with the daily rise in the Covid cases and subsequent returns generated by the markets during these sub-periodsin relation to the daily rise in the case. The increase in volatility and the presence of significant abnormal returns among the sample indices show the impact of COVID-19 on stock markets. The result reveals that Brazilian stock indices show the highest decline among the selected countries, with a fall of more than 50% during the pandemic, while Mexican indices show the lowest fall of around 30% during the same period.

The rational investors want to maximise their invested amount. It will happen only if one knows the possibility of arbitrage opportunity in market. If stock market is efficient, one cannot generate abnormal profit. The objective of the present study is to test the weak market efficiency of Indian Stock Market. The stock indices are Sensex and Nifty. The daily adjusted closing price of these two companies is collected from October 8, 2012 to October 5, 2018. The variance ratio test was employed to test the weak market efficiency. The result revealed that Indian market is not efficient. It is found that technical analysts can generate excess return in Indian Stock Market both in Sensex and Nifty.

All human beings are virtue by God as they get controlling mind and an attitude towards something with the help of which they can experience spirituality. People have different psychological thoughts and beliefs relating to god. Some people feel the immense pleasure in performing religious activities while some believe in the thought "Ahem Brahmasmi" i.e I am part of the divine and they feel pleasure in activities which motivate them to achieve peace. Religion in psychology is considered as a specific fundamental set of beliefs, thoughts and practices generally agreed and controlled by a number of person. It is the psychology of a person which commands their mind in deciding at which path they can attain the eternal feelings of the universe and accordingly they will develop their behavior towards religion and spirituality. Keeping the same in mind, the present study is based much on literature and a brief analysis of 50 teachers in Delhi and NCR collegesandmakes an attempt to study the relationship of spiritual quotient and effective teaching and suggest spiritual quotient as a considerablepredictor to make the workplace accessible.

Empowerment of women is considered as a very important issue for an emerging economy like India. As women form an integral part of our society, their participation in economic activities and decision making activities till date is very low. Over the years, Government and Non-Government agencies have made various efforts to improve the socio-economic status of women in India. One such tool for empowering women is Microfinance. Microfinance is treated as a banking service that is provided to the unemployed, low-income individuals or groups who would otherwise have no other means of gaining financial services. Micro finance in association with Self Help Group (SHG) has been recognized internationally as the modern tool to combat poverty thereby leading to women empowerment. This paper focuses on the role played by microfinance in empowering women of India in the capital Delhi. The main objective of the study is to analyze the impact of micro financing through SHG's on social and economic status of women in Delhi. A structured questionnaire was designed for the purpose of the survey. The researchers have used Structural equation Model to analyze the data collected through survey. The findings of the study show that micro-finance plays an important role in improving the socio-economic status of women in India. Through micro financing they have become independent, confident and courageous. In addition to this they have developed certain skills which have helped them in earning money, but women wanted some more NGOs should come forward and provide them training sessions for their skill development which will help them in income generating activities.

The present study is conducted to know the role of banks to the women empowerment and to suggest measures for uplifting women empowerment. structured questionnaire, based on 5 points LIKERT scale is used for the study. ANOVA, t-test and Chi-square test are used to test the hypotheses and validate the results. The analysis is in conformation with the objectives of the study and the hypotheses formulated. The collected data is analyzed through SPSS. Findings include banks should charge less processing fees, should introduce subsidy and grants to women entrepreneurs. It is also suggested that providing educational loans to girls students at lower rates may be a solution to women empowerment. Banks can play a dominant role in women empowerment by providing special schemes for the housewives for domestic upliftment of the women. Loans and facilities like Bank assurance will be more helpful for the purpose. It has been recommended that special schemes should be introduced for women education about knowledge of bank accounts and different facilities should also be provided by banks.