• Energy Research

Wavelet power spectrum (WPS) and wavelet coherence analyses (WCA) are used to examine the co-movements among oil prices, green bonds, and CO2 emissions on daily data from January 2014 to October 2022. The WPS results show that oil returns exhibit significant volatility at low and medium frequencies, particularly in 2014, 2019–2020, and 2022. Also, the Green Bond Index presents significant volatility at the end of 2019–2020 and the beginning of 2022 at low, medium, and high frequencies. Additionally, CO2 futures’ returns present high volatility at low and medium frequencies, expressly in 2015–2016, 2018, the end of 2019–2020, and 2022. WCA’s empirical findings reveal (i) that oil returns have a negative impact on the Green Bond Index in the medium term. (ii) There is a strong interdependence between oil prices and CO2 futures’ returns, in short, medium, and long terms, as inferred from the time–frequency analysis. (iii) There also is evidence of strong short, medium, and long terms co-movements between the Green Bond Index and CO2 futures’ returns, with the Green Bond Index leading.

The analysis of green bonds and the composition of portfolio investments has gained importance in recent research. The current global context of Sustainable Development Goals requires investors to be environmentally, politically, and socially sustainable, in which the financing of green innovations has occupied a central role. Through the Web of Science and Scopus databases, we focused on analyzing recent trends and further research on green bonds into portfolio investments. The study was performed on 102 studies using Tree of Science (ToS), VOSviewer, and Bibliometrix techniques. We recognize the principal authors and sources, the most influential studies, and the bibliography coupling of studies and authors to identify their importance in the topic analysis. In order to expand the green bond market, particularly at the small and medium enterprise level, more policy instruments are needed. Thus, this study provides an extensive understanding of the research status of the analysis of green bonds and portfolio investments research as an essential input for market participants, researchers, policymakers, and decision-makers.

Green bonds play a pivotal role in the financing of sustainable infrastructure systems. Likewise, CO2 emissions and oil prices can cause an impact on the green bonds market. In order to better understand this issue, this study analyzes the relationship among green bonds, CO2 futures’ prices, and oil prices using a daily data set that includes 2,206 observations corresponding to daily information from 1 January 2014 to 15 June 2022. The Granger Causality Test and the Dynamic Conditional Correlation (DCC-Garch) Model were employed to conduct this analysis. Furthermore, a sensitivity analysis was performed to identify crisis periods concerning the sample period and provide an analysis of DCC-Garch results during extreme market conditions like the COVID-19 pandemic and the Russian invasion of Ukraine. The Granger Causality Test results present a unidirectional causality running from the Green Bond Index to the oil price returns. Also, there is a unidirectional causality running from the Green Bond Index to the CO2 futures’ returns. Additionally, a unidirectional causality runs from the oil price returns to the CO2 futures’ returns. The results for the DCC-Garch indicate a positive dynamic correlation between the Brent oil price return and the CO2 futures’ returns. Finally, the Green Bond Index shows a negative dynamic correlation to the oil return and the CO2 futures’ returns presenting a strong correlation in uncertainty periods.

This study examines the current trajectory and future research directions of environmental, social, and governance (ESG) integration within the banking industry. Utilizing bibliometric and scientometric approaches, it highlights trend topics, influential studies, and notable contributors. Drawing from an analysis of 681 studies from Scopus and Web of Science databases, a comprehensive dataset was curated using scientometric networks with VOSviewer and Bibliometrix tools. This study emphasizes the evolving nature of ESG integration within banking, emphasizing an interdisciplinary shift encompassing environmental, social, and governance considerations. Keyword analysis reveals emerging trends, including the influence of ESG factors on banks’ financial performance, regional variations in ESG integration within banking, and risk assessment related to ESG factors and credit risk in banks. By offering insights into the evolving topic of ESG integration within banking and identifying promising avenues for further exploration, such as the fundamental connection between ESG and sustainability, particularly in climate change and green finance, this research contributes to ongoing discussions surrounding ESG integration in the banking industry, guiding future research efforts in this vital financial sector.

Although issuances of sustainable debt are growing worldwide, there is a lack of studies that allow a better understanding the social bond issuances, particularly those with a gender focus, which are directly related to the achievement of the Sustainable Development Goals 5, 8, 9, and 10. This study addresses the identified knowledge gap by examining the overall state of the gender social bonds in the Latin American market between 2019 and 2022. The results revealed that a total of USD 1 billion was issued by 12 issuers conducting 14 issuances across six countries. Also, most issuances were financial corporations (58.4%) and supranational banks had a pivotal role in this market by being buyers and/or lead managers. As the first study conducted on this topic, this represents a milestone in sustainable finance research. Finally, this study will allow policy makers, regulators, and researchers to promote the issuance of gender social bonds.

This scientometric study analyzes the evolving landscape and outlook of green finance as a driver of economic innovation and growth, highlighting key trends and influential research within this critical field. A dataset of 371 publications was compiled from the Scopus and Web of Science databases and analyzed using VOSviewer, Bibliometrix, and Voyant tools to map the research landscape. By systematically reviewing the scientific literature, this research tracks the development of green finance’s role as a catalyst for economic innovation and growth, identifying trending topics, key studies, and major contributors through bibliometric and scientometric methods. The analysis reveals a growing interdisciplinary approach, integrating environmental, social, and political dimensions into green finance research. Keyword analysis identified three primary thematic clusters: (1) green finance and innovation, (2) economic growth, carbon neutrality, and fintech, and (3) renewable energy and urbanization. This study provides a comprehensive overview of the field and aims to guide future research while contributing to ongoing debates on the role of green finance in fostering economic innovation and sustainable growth.

In this study, we examined the extant literature on the dynamic association between oil prices and financial assets with special emphasis on the methodologies for measuring the dependence among oil prices, exchange rates, stock prices, energy markets, and assets related to sustainable finance. We performed a scientometric review of the structure and global trends of the dynamic association among oil prices and financial assets, based on research from 1982 to 2022 (September) using techniques such as the analysis of (i) sources, (ii) authors, (iii) documents, and (iv) cluster analysis. A total of 746 bibliographic records from Scopus and Web of Science databases were analyzed to generate the study’s research data through scientometric networks. The findings indicate that the most promising areas for further research in this field are represented by co-movement, copula, wavelet, dynamic correlation, and volatility analysis. Furthermore, energy markets and assets related to sustainable finance emerge as crucial trends in investigating dynamic co-movements with oil prices. They also suggest a research gap in analyzing by means of machine learning, deep learning, big data, and artificial intelligence for measuring dynamic co-movements among oil prices and assets in financial and energy markets, especially in emerging countries. Thus, these methodologies can be implemented in further research because these methods could more robustly quantify the association among such variables. The analysis provides researchers and practitioners with a comprehensive understanding of the existing literature and research trends on the dynamic association among oil prices and financial assets. It also promotes further studies in this domain. The identification of these relations presents benefits in risk diversification, hedges, speculation, and inflation targeting.

This study investigates the interconnected dynamics among the Dow Jones Sustainability World Index and two volatility indexes, the Cboe Volatility Index and ICE BofA MOVE Index. It examines their relationships and causalities within daily data spanning from January 2014 to July 2023. The research employs wavelet power spectrum (WPS) and wavelet coherence analyses (WCA) to delve into these interconnections. The wavelet power spectrum reveals noteworthy volatility spikes in the indexes during specific periods linked to geopolitical occurrences, the COVID-19 pandemic, and global uncertainties. A wavelet coherence analysis unveils how the DJ Sustainability World Index significantly influences the Cboe Volatility Index and ICE BofA MOVE Index across short, medium, and long-term perspectives, albeit with variations in certain periods. The empirical findings underscore the intricate relationships between sustainability and volatility indexes, shedding light on their nuanced causal interplay over time. The insights from this study hold paramount implications for policy-makers, investors, and financial institutions navigating a complex and uncertain landscape. The identified relationships between sustainability and market volatility can aid in making informed decisions. This research adds original value by uncovering the time-varying relationships between sustainability and volatility indexes, revealing their interdependencies across diverse temporal scales. Given the observed causal relationships, policy-makers and investors are recommended to consider sustainability-related developments when assessing market volatility. This proactive approach can lead to more informed decision making and effective risk management strategies.