Green Bonds Research Articles

The spillover effect of green bond issuance on corporate financial performances: evidence from China

The spillover effect of green bond issuance on corporate financial performances: evidence from China

Competitions among sub-financial sectors and growth of green bond markets in ASEAN plus three countries

Competitions among sub-financial sectors and growth of green bond markets in ASEAN plus three countries

GREEN BOND INDEX PRICE FORECASTING: COMPARATIVE ANALYSIS OF MACHINE LEARNING MODELS

Today, green financial products have garnered recognition and are consequently regarded as alternative assets. Green bonds exclusively allocate their funds to environmentally sustainable initiatives. Green bonds facilitate companies in enhancing both their financial and environmental performance by promoting innovations stemming from green initiatives and long-term green investments. This study focused on predicting the price of the green bond index in Japan. The input factors for price prediction in Japan include Nikkei225, USD/JPY, and crude oil price assets, which are seen as alternative investment options for Japanese investors. The study utilized a dataset spanning 693 days, from 06.05.2021 to 02.05.2024. The acquired data is partitioned into two distinct sets: one for training and one for testing. 80% of the data was allocated for training purposes, while the remaining 20% was designated for testing. The study utilized various prediction approaches including RF, MLP, GBR, XGBoost, LSTM, SVR, Catboost, and Linear Regression. The performance of these models was compared using evaluation metrics such as MSE, RMSE, MAE, MAPE, and R2 values. The research revealed that the GBR model exhibited the highest performance on the training data set, whereas the XGBoost and RF models yielded superior prediction results on the test data set.

Interactions between sustainable bonds, renewable energy and other financial markets: A macroprudential perspective

We analyse linkages between sustainable bond markets and a number of key financial markets in Europe, namely corporate bond, sovereign bond, renewable energy, equity and volatility markets. We apply a novel empirical approach using zero-volatility spreads (z-spreads) as a measure of relative bond performance to adjust for the sensitivity of bond prices to changes in interest rates. We model these linkages using a Markov-switching vector autoregressive model and static and dynamic copulas that enable us to test for contagion with conditional value-at-risk measures. We find evidence of bi-directional contagion between the sustainability-linked bond and green bond markets along with contagion between other fixed-income markets and the sustainable bond market. Our results indicate possible diversification benefits that green bonds or sustainability-linked bonds may provide to investors active in the key markets analysed.

CLIMATE RISKS AND FINANCIAL MARKETS: A REVIEW OF THE LITERATURE

This study reviews how climate change could be considered an additional source of financial market risk using a bibliometric methodology. We find that the primary impetus for academics’ research into these concerns has come from significant international climate change events, e.g., the adoption of the Paris Climate Agreement. Ecological Economics, Energy Policy, and Energy Economics emerge as the major journals of the existing research output. The bibliographic coupling analysis of the corpus further reveals the existence of five major themes. The first theme evaluates the climate risk and explores mechanisms by which can financial risks be impacted by climate change. The second theme talks about the losses brought on by climate change. The third theme talks about how climate finance products, such as green bonds, green securities, and green insurance, are created and issued, as well as how they help to address and mitigate climate risks. The fourth theme examines how the current financial policy frameworks and instruments can be optimized and adapted in light of the considerable degree of uncertainty that surrounds climate change. The fifth theme discusses the climate-related financial risk modeling. We provide a summary of the development of these themes as well as the future direction to be explored.

Effects of ESG performance and sustainability disclosure on GSS bonds’ yields and spreads: A global analysis

This study investigates the effects of the issuer's environmental, social, and governance (ESG) performance on both the issue-specific yield and its spread vis-à-vis a sovereign comparable. A sample of 3,960 green, social, and sustainable (GSS) bonds issued in global capital markets was used for this purpose. The findings indicate a negative association between ESG performance and bond spreads, implying that a greater commitment to sustainable transition today is an effective strategy for a company to reduce the cost of debt for future projects. The study includes a two-stage procedure. First, the effect of “fundamentals” (e.g., credit rating) on issue pricing is determined; second, the residuals are regressed against the ESG performance. While the latter's risk-reducing power does not appear to differ based on the divide between advanced economies and emerging markets, we find that the real enabler of curbing the unexplained portion of risk is detailed disclosure of the use of proceeds. This is likely to minimize the likelihood of greenwashing.

Delving into the Exchange-Traded Funds (ETFs) Market: Understanding Market Efficiency

Exchange-traded funds (ETFs) are the most popular products in the financial sector today. There is extensive literature on the multifractal analysis of some stock markets, but not about the multifractal behaviour of the ETF market. This study examines the efficiency of stock index ETFs worldwide from an Efficient Market Hypothesis (EMH) perspective, using the ETFs: Ishares Msci World ETF (URTH), Ishares Russell 1000 ETF (IWB), SPDR S&P 500 ETF TRUST (SPY), Ishares Global Clean En. ETF (ICLN), Ishares USD Green Bond ETF (BGRN), from 1 January 2021 to 24 May 2024. It analyses a pre-conflict and a geopolitical conflict to uncover distinct patterns of behaviour reflecting significant changes in market conditions. Before the conflict, the Ishares MSCI World, Ishares Russell 1000, SPDR S&P 500 and Ishares USD Green Bond ETFs showed signs of anti-persistence in returns, indicating a lack of strong relationship or predictability between short-term price movements. The Ishares Global Clean Energy ETF did not reject the random walk hypothesis, suggesting that returns follow a pattern closer to random, where market prices already efficiently reflect all available information. During the conflict, there was a transition in the ETFs' behaviour patterns, as evidenced by the increases in slope values for Ishares MSCI World, Ishares Russell 1000, SPDR S&P 500, Ishares Global Clean Energy and Ishares USD Green Bond. Thus, the possible transition from anti-persistence to long-term memories in ETF returns during the conflict. For portfolio managers, these findings highlight the need to continually adapt investment strategies to manage risks better and take advantage of opportunities in a dynamic and complex investment environment.

A fuzzy approach to environmental scanning (ES) of multi-factor bottlenecks to renewable rural energy sustainability in Nepal

ABSTRACT Due to the prevalence of traditional fuels and the increasing awareness of their negative effects on sustainability, policymakers and government authorities in Nepal have been compelled to transition towards promoting the adoption of clean energy. Nevertheless, as a result of numerous obstacles, the rate of renewable energy utilization has remained sluggish. Therefore, the country’s policymakers must become acquainted with the factors that impede the progress of renewable energy. The objective is to pinpoint the constraints, restrictions, and barriers that hinder the advancement of renewable energy access to rural communities in Nepal. The current study used the Delphi Technique of Environmental Scanning to identify the barriers impeding the adoption of renewable energy. In addition, an Exploratory Factor Analysis (EFA) was performed to redefine categories of bottlenecks depending on the direction of the factors in the context of Nepal. Ultimately, the Fuzzy Analytical Hierarchical Process (FAHP) has been employed to determine the priority of distinct bottlenecks of clean energy development. The study suggests that Nepal’s advancement in sustainable energy is hindered by financial obstacles, primarily due to the significant initial investment, which accounts for 19% of the challenges, and the lack of effective fiscal incentives provided by the government to developers and users, which accounts for 10.6% of the challenges. The research identified many contributory reasons, including the function of regulatory organizations (6.4%), inadequate political commitments (6%), inefficient existing energy policy (5%), and poor public knowledge (5%). To promote the development of sustainable energy sources in rural areas, it is crucial to implement economic incentives, provide financial support, establish partnerships between the public and private sectors, and utilize innovative financing methods such as green bonds, crowdfunding, and carbon financing. Additionally, it is necessary to increase political commitments to amend existing renewable energy policies in the country.

Digital Green Finance Architecture in the Context of Green Deal Implementation: Modern Fintech Tools and Solutions Under the Sustainable Development Concept

Objective: The purpose of the article is to develop a scientific and applied toolkit, which is a set of a logically informationally and algorithmically interconnected means of the information-analytical support of green financing within the Green Deal under the sustainable development concept. Theoretical Framework: The study is based on the Paris Climate Agreement, the European Green Agreement, and the concept of sustainable development. Method: To achieve the defined goal and solve the set tasks, a system of general scientific and special research methods was used. Results and Discussion: The author’s vision of the ecosystem model of the green financing is presented. The main trends of the global green bond market are identified; the parameters of the digital financing markets are estimated. The management decisions on accelerating the capital attraction and activation of green financing, ensuring the balance of the regional financing opportunities in the face of the global challenges are systematized. Research Implications: The important role of the state impact on the creation of the favourable conditions for the climate finance expansion by reducing the political, regulatory, control, macroeconomic and business risks has been established. It was established that the political stability, the consistent and clear regulatory framework, the agreed green financing policy and the openness to the international investors create the attractive conditions for the climate finance conditions. Originality/Value: Applying the author’s developments will create a basis for making the substantiated managerial decisions to the accelerated involvement of the capital in the green financing under the sustainable development concept.

Exploring interconnections and risk evaluation of green equities and bonds: fresh perspectives from TVP-VAR model and wavelet-based VaR analysis

PurposeThis study attempts to examine the time-varying volatility spillovers between environmentally sustainable assets and quantify the value-at-risk of the portfolios across various frequencies.Design/methodology/approachTo accomplish these objectives, this paper utilizes a connectedness index-based TVP-VAR model and applies the wavelet-based VaR ratio to daily data spanning from January 2018 to September 2023.FindingsThe empirical findings reveal a notable increase in the connectedness index between green stocks and green bonds during the COVID-19 crisis, signifying evidence of a contagion effect. The portfolio’s risk ratio also exhibited a sharp rise amid the pandemic, particularly over medium and long-term horizons, driven by increased spillover among green assets. Notably, our analysis indicates that green bonds influence the connectedness system between green stocks and the value-at-risk ratio, reducing volatility spillover and portfolio risk ratios across various investment horizons. These results highlight the role of green bonds as an effective diversification asset against the risks associated with green equities.Originality/valueThis research investigates the dynamic connectedness and value-at-risk ratio between eight green sectoral renewable energy and non-energy equities and green bonds. We put forward some portfolio implications for green investors with an environmental consciousness who desire to decarbonize their portfolios and mitigate environmental issues.

Research on the Mechanisms by Which Green Finance Policies Promote Low-Carbon Economic Development

This paper explores the mechanisms by which green finance policies promote low-carbon economic development, analyzing their implementation effects and challenges in China, and proposing corresponding policy recommendations. Green finance, defined as financial activities supporting environmental protection and sustainable development, aims to direct funds towards environmentally friendly and low-carbon projects. It includes green credit, green bonds, green investment funds, and green insurance, and involves providing preferential loans, issuing green bonds, establishing investment funds, and developing insurance products to support green projects and reduce environmental risks. Additional policies such as green incentives, environmental information disclosure, green ratings, and international cooperation further enhance the effectiveness of green finance. The mechanisms by which green finance policies promote low-carbon development include guiding funds to low-carbon industries, optimizing resource allocation, promoting technological innovation, supporting industrial structure transformation, enhancing market competitiveness, and promoting socially responsible investment. Despite significant progress, challenges such as insufficient supply of green finance resources, regional disparities in policy implementation, limited innovation in green finance products, and imperfect information disclosure and regulatory systems remain. The paper concludes with policy recommendations to increase policy support, improve information disclosure and regulatory systems, promote product innovation, strengthen regional coordinated development, and enhance international cooperation.

Quantitative Easing and Climate Change: A Case Study

In the context of increasing global climate change, this article takes an in-depth look at how central banks can use quantitative easing to help address this issue. Based on three research methods: Green Bond, SDGs Bond, Carbon Trading Market and Carbon Reduction Project, this paper analyzes the pros and cons of specific measures of quantitative easing in dealing with climate change. The study found that the above three types of quantitative easing policies can effectively guide funds to green industries, promote green economy and sustainable development, and thus mitigate the economic impact of climate change. This research not only provides a new perspective for central bank policy making, but also provides investors with new opportunities for green investment. This paper suggests that the central bank should increase its support for green projects when formulating quantitative easing policies, and encourage investors to actively participate in green investment to jointly promote the response to climate change.

Blockchain and sustainable finance: Enhancing transparency and efficiency in green investments

The study aimed to analyse the possibilities of using blockchain technology to increase transparency and efficiency in sustainable finance. The application of blockchain technologies and environmental and social practices in the context of sustainable finance was analysed, emphasising implementation and prospects in Kyrgyzstan. Blockchain, as an innovative decentralised data recording technology, provides a high level of security, transparency and immutability, which renders it particularly valuable for the financial sector. The study highlighted how blockchain can improve international transfer processes, increase the transparency of financial transactions and simplify the management of smart contracts, and noted existing challenges such as scalability and legal issues. The role of blockchain technologies in sustainable finance, especially in the field of green investments, was highlighted as an important aspect of the study. The introduction of blockchain in areas such as green project financing and social initiative management can help increase investor confidence and improve investment performance. Financial technology is also central in shaping new approaches to finance and investment, facilitating access to capital through crowdfunding and person-to-person (P2P) lending platforms. The introduction of environmental and social practices in financial institutions of the Kyrgyz Republic demonstrates the growing attention to corporate responsibility and sustainable development, despite the initial stage of their implementation. On international stage, successful projects such as the use of blockchain to track supply chains, green bonds and carbon credit management demonstrate the potential of technology to improve the transparency and efficiency of sustainable finance. These examples can be used by Kyrgyzstan in developing and implementing domestic blockchain and environmental and social initiatives, contributing to more sustainable economic growth and attracting international investment

Mitigating digital market risk with conventional, green, and Islamic bonds: Fresh insights from new hybrid deep learning models

We examine the impact of conventional, green, and Islamic bonds on the long-term memory of cryptocurrency market risk. Utilizing a time-varying parameter vector autoregressive deep learning model, we integrate time-varying parameter vector autoregressive methods with advanced deep learning sequence modeling architectures, including temporal convolutional network, gated recurrent unit, and long short-term memory for December 18, 2017, to April 19, 2024. Results indicate that incorporating all fixed-income securities reduces digital market risk. However, conventional and green bonds have a particularly strong impact on improving the long-term memory of digital market risk, while this is not the case for Sukuk.

Complex non-linear relationship between conventional and green bonds: Insights amidst COVID-19 and the RU–UA conflict

In times of crisis, such as global pandemics or conflicts, investors’ preference between green and conventional bonds may lean towards the latter due to increased risk aversion and a focus on short-term stability. However, some investors motivated by increased awareness of sustainability issues may maintain or increase their allocation to green bonds, seeing them as an opportunity for long-term resilience and sustainable investing. We use multifractal detrended cross-correlation analysis, wavelet coherence, and copula-based dependence analysis to examine the complex relationship between the S&P Green Bond Index and the S&P 500 Bond Index. The results indicate the presence of multifractal cross-correlations, the strength of which is most pronounced in times of crisis, especially in the post-COVID-19 period. The wavelet-based analysis also detects the COVID-19 break and shows significant interdependence at all frequency levels after the RU–UA conflict. The copula-based correlation values exhibit a distinct oscillating pattern over time, characterized by an initial break coinciding with the impact of COVID-19. In light of these findings on the impact of COVID-19 and the RU–UA conflict, we have included the Geopolitical Risk Index in our analysis to better understand how geopolitical tensions and conflicts influence the observed interdependence and to gain insight into how changes in the global risk environment affect both bond market dynamics. Overall, the results of this study provide insights into the interconnectedness between conventional and green bond markets and highlight potential spillover effects and systemic risks in an increasingly complex financial landscape.

The impact of collateral-based monetary policy on green financing cost: an analysis of the People's Bank of China’s approach

ABSTRACT This paper examines the effects of the collateral-based monetary policy, implemented by the People’s Bank of China, on green financing costs. Employing a Difference-in-Differences (DID) method to examine credit spreads of financial bond in primary and secondary markets from 2017 to 2019, our findings highlight a significant decrease of 26 basis points (bps) in the financing costs of green financial bonds in the primary market, with a 12-bps decline in the secondary market post-policy. Our study underscores the crucial role of implicit credit enhancement provided by the People’s Bank of China's collateral endorsement. Interestingly, the liquidity provision mechanism, where investors pay premiums to secure liquidity support, does not find empirical backing in the specific context of China's bond market. These findings illuminate the effectiveness of collateral-based monetary policies in reducing green financing costs, offering valuable insights for using collateral strategies to green monetary policies.

Green municipal bonds in the energy transition process

Green municipal bonds in the energy transition process

Short-term impacts vs. long-term contributions: The role of clean energy and ESG investments in China

This paper is the first in the literature on Environmental, Social, and Governance (ESG) investments and clean energy markets to employ a time-frequency-quantile framework, exploring the interrelations among energy commodities (such as oil, coal, and coke), clean energy equities, and ESG investments in China. The main findings reveal that, in the short term, clean energy equities are substantial net contributors, while commodity markets primarily act as recipients. Over a long horizon, ESG investments emerge as the foremost contributors, followed by coke and solar investments, while clean energy equities diminish in significance. Oil, nuclear equities, and green bonds are significant recipients in this dynamic. Furthermore, our analysis highlights the dominance of short-term shocks over long-term shocks in influencing these markets. Quantile analysis underscores unique behaviors under extreme market conditions. Notably, strong connections between oil and coke with other financial markets are observed during extreme periods, such as bull or bear phases, contrasting with their interactions under normal conditions. Conversely, coal exhibits strong interdependencies across various market scenarios, distinguishing it from the patterns observed for oil commodities.

Mobilizing Firms for Climate Action: Paris Climate Agreement and Corporate Green Bond Issuance

Mobilizing Firms for Climate Action: Paris Climate Agreement and Corporate Green Bond Issuance

The investment of renewable energy: Is green bond a safe-haven to hedge U.S. monetary policy uncertainty?

This paper uses the bootstrap rolling-window Granger causality test to investigate the relationship between U.S. monetary policy uncertainty and green bond. The method addresses the limitations of ignoring the instability of coefficients and the time-varying relationship between the variables in previous literature. The results find both insignificant and significant relationship in the full period. One explanation of the insignificant relationship is that the changes of investor sentiment influence their judgment regarding to the monetary policy uncertainty and green bond, and thus the significance of the relationship between the variables. Besides, this paper finds the significant inter-relationship is time-varying. Specifically, in the sub-period when the market sentiment is low, the rising monetary policy uncertainty influences green bond price negatively. Meanwhile, the unexpected changes of green bond may also have both positive and negative effects on monetary policy uncertainty in different sub-periods. Thus, this paper proposes that the impact mechanism between the variables is effective when the investors are irrational. Furthermore, the findings may provide valuable implications for investors and governments, including adjusting investment strategy when the monetary policy is unclear, increasing monetary policy transparency, and monitoring speculative activity in green bond market. In addition, it is necessary to emphasize that the validity of the findings is limited to the U.S. and the period when investors’ sentiment experience large fluctuations. Finally, future research may consider expand the analysis to the green stock, as it is another important channel for renewable energy investment.