Purpose: The 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/approach: The 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.Findings: The 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/implications: The 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 implications: The 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/value: This 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.

The present article empirically estimates the volatility spillover transmission in Indian equity market represented by Sensex from world economies composite index (Euro Stoxx 50) using the dynamic conditional correlation generalized autoregressive conditional heteroscedasticity (DCC-GARCH) model. The study uses secondary data spanning between 1 April 2012 and March 2022 on weekly basis. The DCC-GARCH model is applied to examine the spillover from developed stock markets to Indian stock market (Sensex). The findings of the study revealed that in short run there is a spillover effect from global markets to Indian stock markets. Investors can invest in the Indian stock market for the long period of time as there is no volatility spillover or volatility transmission from Euro and Nasdaq however in short run the investment in the Indian stock market is not safe due to the presence of volatility effect from all developed stock markets.

Purpose: This 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/approach: This 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.Findings: It 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/value: To 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.

Purpose: The 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/approach: A 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.Findings: The 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 implications: Based 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/value: The 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.