Journal Articles
Permanent URI for this collectionhttp://10.0.100.92:4000/handle/123456789/21
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Item Analyzing the static and dynamic dependence among green investments, carbon markets, financial markets and commodity markets(International Journal of Managerial Finance, 2025-01-17) Abakah, Emmanuel Joel Aikins; Tiwari, Aviral Kumar; Oliyide, Johnson Ayobami; Appiah, Kingsley OpokuPurpose This paper investigates the static and dynamic directional return spillovers and dependence among green investments, carbon markets, financial markets and commodity markets from January 2013 to September 2020. Design/methodology/approach This study employed both the quantile vector autoregression (QVAR) and time-varying parameter VAR (TVP-VAR) technique to examine the magnitude of static and dynamic directional spillovers and dependence of markets. Findings Results show that the magnitude of connectedness is extremely higher at quantile levels (q = 0.05 and q = 0.95) compared to those in the mean of the conditional distribution. This connotes that connectedness between green bonds and other assets increases with shock size for both negative and positive shocks. This further indicates that return shocks spread at a higher magnitude during extreme market conditions relative to normal periods. Additional analyses show the behavior of return transmission between green bond and other assets is asymmetric. Practical implications The findings of this study offer significant implications for portfolio investors, policymakers, regulatory authorities and investment community in terms of carefully assessing the unique characteristics offered by each markets in terms of return spillovers and dependence and diversifying the portfolios. Originality/value The study, first, uses a relatively new statistical technique, the QVAR advanced by Ando et al. (2018), to capture upper and lower tails’ quantile price connectedness and directional spillover. Therefore, the results possess adequate power against departure from mean-based conditional connectedness. Second, using a portfolio of green investments, carbon markets, financial markets and commodity markets, the uniqueness of this study lies in the examination of the static and dynamic dependence of the markets examined.Item Environmental, social and governance-type investing: a multi-stakeholder machine learning analysis(Management Decision, 2025-03-26) Jaiswal, Rachana; Gupta, Shashank; Tiwari, Aviral KumarPurpose This research delves into the determinants influencing the adoption of environmental, social and governance (ESG) investing through an analysis of social media dialogs using the uses and gratification theory. Design/methodology/approach This study employs a mixed-methods approach, integrating sentiment analysis, topic modeling, clustering, causal loop analysis and ethnography to examine ESG-related content on social media. Analyzing social media data, study identified key themes and derived ten propositions about ESG investing. Industry professionals, financial advisors and investors further validated these findings through expert interviews. Combining data-driven analysis and qualitative insights provides a comprehensive understanding of how social media shapes investor preferences and decision-making in the ESG domain. Findings Environmental aspects, such as conservation, preservation of natural resources, renewable and clean energy, biodiversity, restoration and eco-friendly products and technologies, shape attitudes toward ESG investing. Social considerations, including inclusivity, diversity, social justice, human rights, stakeholder engagement, transparency, community development and philanthropy, significantly influence ESG investing sentiments. Governance elements such as transparency, accountability, ethical governance, compliance, risk management, regulatory compliance and responsible leadership also play a pivotal role in shaping ESG investing opinions. Practical implications This study presents actionable insights for policymakers and organizations by identifying key constructs in ESG investing and proposing an integrated framework that includes mediating factors like resource efficiency and stakeholder engagement alongside moderating elements such as regulatory environment and investor preferences. Policymakers should establish standardized ESG reporting frameworks, incentivize sustainable practices and use social media data for regulatory purposes. For businesses, integrating social media insights into decision-making can enhance ESG communication strategies and accountability. These measures will foster greater transparency, strengthen investor relations and contribute to a more sustainable and inclusive global economy. Originality/value To the authors' best knowledge, this is the first study to investigate improving ESG investing preferences based on big data mined from social media platforms.