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Without precedent, green bonds confront, for the first time since their emergence, a twofold crisis context, namely the Covid-19-Russian–Ukrainian crisis period. In this context, this paper aims to investigate the connectedness between the two pioneering bond market classes that are conventional and treasury, with the green bonds market.

In their forecasting target, authors use a Support Vector Regression model on daily S&P 500 Green, Conventional and Treasury Bond Indexes for a year from 2012 to 2022.

Authors argue that conventional bonds could better explain and predict green bonds than treasury bonds for the three studied sub-periods (pre-crisis period, Covid-19 crisis and Covid-19-Russian–Ukrainian crisis period). Furthermore, conventional and treasury bonds lose their forecasting power in crisis framework due to enhancements in market connectedness relationships. This effect makes spillovers in bond markets more sensitive to crisis and less predictable. Furthermore, this research paper indicates that even if the indicators of the COVID-19 crisis have stagnated and the markets have adapted to this rather harsh economic framework, the forecast errors persist higher than in the pre-crisis phase due to the Russian–Ukrainian crisis effect not yet addressed by the literature.

This study has several implications for the field of green bond forecasting. It not only illuminates the market participants to the best market forecasters, but it also contributes to the literature by proposing an unadvanced investigation of green bonds forecasting in Crisis periods that could help market participants and market policymakers to anticipate market evolutions and adapt their strategies to period specificities.

The global economy is growing very fast, and it is also facing environmental challenges. Due to increased economic activities, global warming is rising as a result of greenhouse gas emissions. Concepts like green finance and green investments are emerging to battle climate issues. The present study empirically examines the impact of green bonds on carbon dioxide (CO₂) emissions in developing countries, as these countries are producing 63% of CO₂ emissions around the globe.

To check this impact, pooled ordinary least squares (OLS), fixed effect and generalized method of moments (GMM) techniques are applied using the annual data of 65 developing countries from 2008 through 2021.

The results indicate that the overall effect of green bonds on CO₂ emissions is negative, as more issuance of green bonds reduces CO₂ emissions, confirming results from the existing empirical literature. The study found that more foreign direct investment (FDI) and urbanization lead to more CO₂ emissions, while increase in trade openness helps reduce CO₂ emissions. It was found that promoting green bonds will help to promote environmentally friendly projects that will help to reduce CO₂ emissions. Rapid urbanization has led to more energy demand for various industries like manufacturing, transportation and residential sectors, which leads to more CO₂ emissions.

The policymakers in these countries should make policies that help in reducing carbon emission by increasing green bonds and FDI in supporting projects that are environmentally friendly. Therefore, to mitigate such current and future issues, policymakers in developing countries need to give serious attention to this area to fulfill sustainable development goals.

This study presents a pioneering examination of green bonds and CO₂ emissions in 65 lower- and middle-income countries (developing countries). We have tried to cover all developing countries that are causing more greenhouse gas emissions and need to shift to green finance strategies. It will be a contribution to the body of knowledge regarding the role of green bonds in reducing CO₂ emissions. The present study will help in assessing the importance of green bonds in bringing low-carbon economies.

This paper originally proposed the fuzzy option pricing method for green bonds. Based on the requirements of arbitrage equilibrium, this paper draws on Merton's corporate bond option pricing model.

Describing the asset value behavior of green bond issuing enterprises through diffusion-jump processes to reflect the uncertainty brought by carbon emission reduction policies and technologies, using approximation methods to get the analytical pricing formula and then, using a fuzzification technique of Choquet expectation under  λ-additive fuzzy measures after considering fuzzy factors, the paper provides fuzzy intervals for the parity coupon rates of green bonds with different subjective levels for investors.

The paper proposes and argues the classical and fuzzy option pricing methods in turn for both corporate ordinary bonds and green bonds, considering carbon risk or climate risk. It implements the scenario analysis varying with industry emission standards and discusses the sensitiveness of the related key parameters of the option.

The fuzzy option pricing for the green bonds provides the scope of the variable equilibrium values, operational theoretical supports and some policy implications of carbon reduction and promoting green funding.

The logic of introducing the fuzziness of the option pricing for the green bonds lies with considering the existence of fuzzy information about the project supported by the green bond and the subjectivity of investors and it also responds to changes in technological uncertainty and policy uncertainty in the process of “carbon peaking and carbon neutrality.”

In February 2022, the Finance Minister of India in the Union Budget 2022 announced that the government proposed to issue sovereign green bonds to mobilize assets for green infrastructure. These bonds are a sort of fixed-income instrument where the money raised from investors is used exclusively to finance projects having a positive environmental impact. The announcement was in sync with India's commitment to achieving net-zero carbon emissions by 2070. However, many issues come with it such as the complexity of green data, and the lack of uniform standards to measure the impact of green investments leading to allegations of “greenwashing,” among others. Its solution lies in the digital tokenization of green bonds using blockchain technology. Foreign investors scout for green bonds issued by growing markets like India, which have attractive valuations and good growth prospects. Marketing and issuing green bonds properly would have a far greater potential to bring investment to the security markets and the much-needed advancement in the sustainable sector. It is much more likely that green bonds will bring investment to the security markets and much-needed advancement to the sustainable sector if they are marketed and issued through digital tokenization. Financial regulators and policymakers can create a global framework for the application of blockchain technology in sustainable finance. This might entail tokenizing eco-friendly assets, issuing eco-friendly bonds, trading renewable energy and 2-2 carbon credits in a decentralized ecosystem, and decentralizing crowdfunding for eco-friendly enterprises.

This chapter seeks to demonstrate how blockchain technology can help issue green bonds and increase the overall efficiency of green finance in the economy. It also aims to scrutinize how such digital tokenization of green bonds would affect the security market and increase the standards of environmental, social, and governance (ESG) worldwide. While discussing how this process is shaping up and impacting the economies of various countries, it also seeks to provide suggestions to be taken into consideration while adopting the digital tokenization of green bonds.

This study proposes a theoretical model for measuring the greenness factors of a firm. We develop the multifactor utility function and find that the proportion of investment in green bonds is higher if greenness factors account for by a firm and vice versa. Moreover, we further develop the global aspects of greenness measures which identify how much level of greenness is maintained by a firm to make the environment green. In terms of reduction in emissions based on global measures, we report that the proportion of investment in green bonds is higher. This study argues that the difference between firm-related and global measures of greenness refers to distortion in portfolio allocation. Lastly, we compare the results of five Asian countries and report that Japanese firms are appropriately following the greenness measures while the firms operating in developing countries including Indonesia, Malaysia, Pakistan, and Thailand are far behind in implementing the greenness measures.

This paper aims to examine the cross-quantile correlation and causality-in-quantiles between green investments and energy commodities during the outbreak of COVID-19. To be specific, the authors aim to address the following questions: Is there any distributional predictability among green bonds and energy commodities during COVID-19? Is there exist any directional predictability between green investments and energy commodities during the global pandemic? Can green bonds hedge the risk of energy commodities during a period of the financial crisis.

The authors use the nonparametric causality in quantile and cross-quantilogram (CQ) correlation approaches as the estimation techniques to investigate the distributional and directional predictability between green investments and energy commodities respectively using daily spot prices from January 1, 2020, to March 26, 2021. The study uses daily closing price indices S&P Green Bond Index as a representative of the green bond market. In the case of energy commodities, the authors use S&P GSCI Natural Gas Spot, S&P GSCI Biofuel Spot, S&P GSCI Unleaded Gasoline Spot, S&P GSCI Gas Oil Spot, S&P GSCI Brent Crude Spot, S&P GSCI WTI, OPEC Oil Basket Price, Crude Oil Oman, Crude Oil Dubai Cash, S&P GSCI Heating Oil Spot, S&P Global Clean Energy, US Gulf Coast Kerosene and Los Angeles Low Sulfur CARB Diesel Spot.

From the CQ correlation results, there exists an overall negative directional predictability between green bonds and natural gas. The authors find that the directional predictability between green bonds and S&P GSCI Biofuel Spot, S&P GSCI Gas Oil Spot, S&P GSCI Brent Crude Spot, S&P GSCI WTI Spot, OPEC Oil Basket Spot, Crude Oil Oman Spot, Crude Oil Dubai Cash Spot, S&P GSCI Heating Oil Spot, US Gulf Coast Kerosene-Type Jet Fuel Spot Price and Los Angeles Low Sulfur CARB Diesel Spot Price is negative during normal market conditions and positive during extreme market conditions. Results from the non-parametric causality in the quantile approach show strong evidence of asymmetry in causality across quantiles and strong variations across markets.

The quantile time-varying dependence and predictability results documented in this paper can help market participants with different investment targets and horizons adopt better hedging strategies and portfolio diversification to aid optimal policy measures during volatile market conditions.

The outcome of this study will promote awareness regarding the environment and also increase investor’s participation in the green bond market. Further, it allows corporate institutions to fulfill their social commitment through the issuance of green bonds.

This paper differs from these previous studies in several aspects. First, the authors have included a wide range of energy commodities, comprising three green bond indices and 14 energy commodity indices. Second, the authors have explored the dependency between the two markets, particularly during COVID-19 pandemic. Third, the authors have applied CQ and causality-in-quantile methods on the given data set. Since the market of green and sustainable finance is growing drastically and the world is transmitting toward environment-friendly practices, it is essential and vital to understand the impact of green bonds on other financial markets. In this regard, the study contributes to the literature by documenting an in-depth connectedness between green bonds and crude oil, natural gas, petrol, kerosene, diesel, crude, heating oil, biofuels and other energy commodities.

This paper aims to examine the comovement among green bonds, energy commodities and stock market to determine the advantages of adding green bonds to a diversified portfolio.

Generic 1 Natural Gas and Energy Select SPDR Fund are used as proxies to measure energy commodities, bonds index of S&P Dow Jones and Bloomberg Barclays MSCI are used to represent green bonds and the New York Stock Exchange is considered to measure the stock market. Granger causality test, wavelet analysis and network analysis are applied to daily price for the select markets from August 26, 2014, to March 30, 2021.

Results from the Granger causality test indicate no causality between any pair of variables, while cross wavelet transform and wavelet coherence analysis confirm strong coherence at a high scale during the pandemic, validating comovement among the three asset classes. In addition, network analysis further corroborates this connectedness, implying a strong association of the stock market with the energy commodity market.

This study offers new evidence of the temporal association among the US stock market, energy commodities and green bonds during the COVID-19 crisis. It presents a novel approach that measures and evaluates comovement among the constituent series, simultaneously using both wavelet and network analysis.

This paper aims to providea comprehensive review of the concepts and definitions of green finance, and the importance of “green” impact investments today. The core challenge in combating climate change is reducing and controlling greenhouse gas emissions; therefore, this study explores the solutions green finance provides emphasizing their impact on the environment and firms' financial performance. With increasing attention to the concept of green finance, multiple forms of green financial tools have come to fruition; the most prominent are green bonds.

This paper compiles a comprehensive green bond dataset, presenting a statistical study of the evolution of the green bonds market from its first appearance in 2006 until 2021.

The green bond market has seen massive growth over the years reaching $1651.92bn as of 2021. Findings show that green bonds are working towards shifting from high carbon-emitting energy to renewable energy, which is vital to economic development and growth. In congruence, green bonds are aligned with the United Nation's sustainable development goals (SDGs) amounting to $550bn for 2020, with the five most covered SDGs amounting to over 60%.

With growing worldwide concern for global warming, green finance became the fuel that pushes the world to act in combating and mitigating climate change. Coupled with adopting the Paris Agreement and the SDGs, Green finance became a vital tool in creating a pathway to sustainable development, as it connects the financial world with environmental and societal benefits.

This paper aims to investigate the impacts of green bond issuance on the environment while taking into account the moderating role of issuing countries’ institutional quality.

The analysis is based on a longitudinal data set covering 171 countries and territories during 2007–2018. The authors rigorously account for endogeneity issues using two-stage least squares estimation and a set of instrumental variables for green bond issuance volume.

The overall results confirm the positive environmental impacts of green bonds in reducing carbon dioxide and greenhouse gas emissions, enhancing renewable energy consumption rate and accelerating the progress towards sustainable development goals (SDGs). However, these effects are contingent upon the levels of institutional development of the issuing countries in a way that green bond issuance only benefits the environment when the institutional quality has reached a minimum level.

The results provide important policy implications for countries in their efforts to prevent environmental degradation and achieve SDGs.

This paper contributes to the existing literature by providing a macro-level evaluation of the environmental impact of green bonds, hence, enabling policy implications to be drawn for countries to achieve their SDGs. The analysis is more comprehensive using a wide range of indicators for environmental performance. To the best of the authors’ knowledge, this paper is also one of the first attempts to examine the moderating effect of institutions on the environmental impact of green bonds.