PurposeThe purpose of the study is to investigate the long-run and short-run dynamic relationship between crude oil prices and the movement of Sensex for the period of 2000–2018.Design/methodology/approachThe study uses the augmented Dickey–Fuller test for the presence of unit root, Johansen cointegration test for estimating the cointegration among the variables. Further, in the case of no cointegration found, the study employed the vector autoregression (VAR) model to estimate the long-run relationship and the Granger causality/Wald test for short-run relationship. The study also conducted tests for the prerequisites of the model: serial correlation, heteroskedasticity and normality of data.FindingsThe study found that both the variables, crude oil prices and Sensex are integrated of order 1, that is, I (1), and there is no cointegration between them. Further, the results proliferated from the VAR model unfold the marked effect of previous month crude oil prices (lag 1) on the movement of Indian stock market represented by Sensex considered as the benchmark index. Furthermore, VAR–Granger causality/block exogeneity Wald tests results indicated that there is a causal relationship between the crude oil prices and Sensex under the VAR environment. The model does not have any serial correlation and heteroskedasticity indicating toward the unbiased and robust estimates.Research limitations/implicationsThe study is conducted till the year 2018, and data for the present period (post-2018) is excluded due to ongoing trade issues between the USA and oil-exporting countries such as Iran. The current COVID-19 outbreak has also put serious issues. Due to limited time and availability of standardized data, researchers have considered Sensex as equity index only, but for more generalized research outcome few other equity indexes could have been taken for study.Originality/valueThe study is completely original in nature and is an extensive study of the relationship between the crude oil price and Indian stock market with reference to causality between the variables.

PurposeThe present study tries to examine the relationship between financial inclusion and environmental quality as proxied by carbon emissions in India covering the period from 2008 to 2018.Design/methodology/approachA financial inclusion index has been composed using principal component analysis (PCA) based on three dimensions: access, penetration and usage. After testing for stationarity of the data, the authors adopted the autoregressive distributive lag model (ARDL) methodology.FindingsThe study found that financial inclusion and growth lead to increased carbon emissions in India and the government must resort to greener policies, whereas empirical results support that globalization reduced the pollutants emissions in both the long term and short period in India.Practical implicationsBased on the results, several policy prescriptions are rendered for policymakers: (1) need to move toward greener energy policies and (2) enhance the awareness of green financing instruments such as green bonds in India. Therefore, policymakers should be more proactive in accepting green and sustainable financial alternatives.Originality/valueThe present study contributes to the scant literature on the financial inclusion–emission nexus in India. This study considers three inclusion parameters that are not present in previous studies.

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PurposeThe present study tries to explore the various fund attributes that influence the mutual fund performance. Further, study examined the effect of mutual fund attributes namely, Net Asset Value (NAV), Portfolio turnover ratio (PTR), fund size (AUM), expense ratio (ExpR) and fund age (Age) on mutual fund's performance using gross return and risk-adjusted performance measures.Design/methodology/approachThe study evaluated balanced panel data (short panel) comprising 81 Indian equity mutual fund schemes for the period of 2013–2019. The study estimated relationship between fund attributes (Net asset value, Portfolio turnover ratio, Fund age, fund size and Expense ratio) and fund performance (using gross return and risk-adjusted performance measures), through panel data regression using fixed-effects model as suggested by Hausman specification test on transformed data (due to high multicollinearity), with cluster-robust estimators due to the presence of heteroskedasticity in the model.FindingsThe findings of the study suggested that using gross return as fund performance measure, PTR, NAV, AUM, Age exhibit significant relationship with the fund performance whereas using risk-adjusted performance measures (Treynor ratio and Jensen alpha) NAV and ExpR significantly influences the fund performance. Identification of the significant relationship between fund characteristics and fund performance offers valuable insights to the investors and fund managers for rationally managing their portfolio with the ultimate objective of the wealth maximization.Research limitations/implicationsThe study considered only 81 equity mutual fund schemes. Some of the data were not available at the time of the study due to the policy of the company. The present study contributes significantly in examining the expected association between fund attributes and fund performance in the context of Indian mutual fund industry where this relationship were explored less.Practical implicationsThe findings of the present study will help the investors to take the rational investment decision with the ultimate objective of maximum return with minimal risk. The findings also offer significant germane to the stakeholders in making rational decision-making process.Originality/valueThere is dearth of study concerning the relationship between mutual fund characteristics and fund performance with respect to Indian mutual fund industry. Therefore, study provides valuable insights to the area of the portfolio selection and management with respect to Indian mutual funds.

PurposeThe purpose of this study is to investigate the influence of mobile applications on investment decisions by retail investors in stocks and mutual funds. This study focuses on how mobile technologies are applied on mobile apps by retail investors for e-trading in emerging financial markets.Design/methodology/approachThe study explored predictive relevance for the adoption behavior of retail investors under the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. Further, goal contagion theory was applied to investigate the adoption behavior of investors towards e-trading. An adapted questionnaire was used to collect the date from April to June 2021 and data analysis was performed on 507 usable responses. The methodology adopted in this study is variance based partial least square structural equational modelling (PLS-SEM). Additionally, the study explains important and performing constructs based on the response of retail investors towards mobile app usage for investment decisions.FindingsThe study shows that effort expectancy, performance expectancy followed by perceived return were the primary determinants of behavioral intentions to use mobile applications by retail investors for e-trading. Further, habit of investors determined the adoption behavior of investors towards mobile apps. Additionally, the study revealed that perceived risk is not an important aspect for retail investors in comparison to perceived return.Research limitations/implicationsThe study in future can address to the aspect of personality traits of retail investors for technology adoption for investment decisions. Further investigation is required on addressing unobserved heterogeneity of retail investors towards technology adoption process in emerging financial markets.Practical implicationsThe study provides theoretical and practical implications for retail investors, financial advisors and technology companies to understand the behavioral pattern and mobile apps adoption behavior of retail investors in emerging financial market. The findings in the study will help broking firms to sensitize their clients for effective use of their respective mobile apps for e-trading purposes. The study will strengthen the knowledge of financial advisors to understand investment behavior of retail investors in emerging financial markets.Originality/valueThis study unfolds a novel framework of research to understand the technology adoption pattern of retail investors for e-trading by mobile applications in emerging financial markets. The present study provides significant understanding in the domain of technology adoption by retail investors under behavioral finance environment.

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.

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