This chapter examines the intersection of blockchain technology and its environmental impact, focusing on the energy-intensive validation protocols underlying blockchain systems. It provides a brief overview of blockchain technology and non-fungible tokens (NFTs), highlighting their unique characteristics and growing popularity. The transition from proof of work (PoW) to proof of stake (PoS) is analyzed in terms of their differing environmental footprints. The chapter explores climate change legislation from the United Nations Framework Convention on Climate Change (UNFCCC) to the Paris Agreement and offers an overview of European climate policies. It then assesses emerging legislative trends in the European Union, the United States, and China concerning blockchainâs environmental impact. Finally, it evaluates the legitimacy of PoW and PoS mechanisms within the framework of international and European climate regulations, offering insights into aligning blockchain technology with global sustainability goals.
ChiâWei Su, YuâMei Ding, KaiâHua Wang, Xiaoqing Wang
ABSTRACT In this paper, the safeâhaven attributes of green bonds, gold, and bitcoin are compared to those of traditional bonds under various time periods and quantiles by using the WQC methodology. The results indicate that green bonds exhibited a stable safeâhaven function at longer time horizons during the full sample period, whereas other assets did not have safeâhaven features. During the COVIDâ19 pandemic, bitcoin exhibited safeâhaven attributes at all time horizons, whereas gold demonstrated these characteristics over the short and medium terms. In the sample period during the RussiaâUkraine war, green bonds had strong safeâhaven properties at shorter and middle time horizons, whereas bitcoin had these properties at longer time spans. In this paper, a multivariate network framework that includes green bonds, gold, and bitcoin is constructed, and the theoretical foundations that influence the safeâhaven attributes of assets are detailed. In addition, this study clearly presents the safeâhaven effects of assets under various sample periods, time horizons, and quantiles, thereby bridging the gap of existing studies that ignore time frequency. Thus, this paper provides advice for investors, regulators, and policyâmakers, such as choosing portfolios on the basis of asset characteristics, monitoring asset disclosure, and encouraging the trading of safeâhaven assets.
ABSTRACT Despite the universal acknowledgment of financial profit expectations as an investment driver, environmental concern has been suggested as a factor influencing investors' decisions to purchase cryptocurrency. In this sense, this study investigates the impact of environmental information on investment allocation decisions to purchase different types of cryptocurrencies with different levels of environmental impacts (i.e., cryptocurrencies using ProofâofâWork (Bitcoin) and ProofâofâStake (Ether) consensus algorithms). This study used an online survey involving 199 respondents in experimental groups (receiving environmental information before allocating decision) and control groups (receiving no environmental information before allocating decision) to split an imaginary fund into Bitcoin and Ether. No significant difference in allocating capital was found between the groups regardless of investment horizon, time of affiliation as a cryptocurrency investor, education level of the respondents, and perceived importance of environmental impacts. Possible explanations for this insensitivity are widespread prior knowledge about the environmental impact of Bitcoin, psychological reactance towards environmental information, and the assessed overall low perceived importance of environmental impact for investment decisions in cryptocurrencies. The lack of significant impact found in such an experimental study implies that environmental education alone cannot be sufficient to shift investor preferences. The findings offer initial insights into the impact of environmental awareness on cryptocurrency investment motivations and provide empirical evidence to understand cryptocurrency investment behaviors in the current research scene. The results suggest researchers and policymakers investigate further investors' motives while coming up with more restrictive policy instruments to mitigate the negative environmental impact of cryptocurrencies.
Purpose The purpose of this study is to examine the response of various cryptocurrency market classes to the Federal Reserveâs quantitative easing (QE) announcements. Design/methodology/approach We used the time-varying parameter vector autoregressive model to analyze the price spillover and interconnectedness between the US market assets/indices, and cryptocurrencies, explicitly focusing on Layer 1 tokens, DeFi tokens, Exchange-Based Tokens, Smart Contracts and Stablecoins. Findings The findings reveal that most cryptocurrency classes exhibit notable price spillovers from US assets/indices. However, the analysis suggests that only high-return tokens show significant responses during the Federal Reserve QE announcements and receive price spillover. In contrast, leading tokens remain unaffected by such spillovers, which suggests that during QE periods investors tend to seek higher returns and are more likely to invest in high return assets. It reflects a preference for assets that could offer greater returns when monetary policy is easing while more stable cryptocurrencies are less impacted by policy changes, implying that investors may adjust their strategies by shifting toward high return cryptocurrencies during periods of QE to capitalize on these market movements. Research limitations/implications This study focuses on a limited selection of cryptocurrency classes and specific QE events, which may not fully capture all market dynamics or incorporate newer cryptocurrency assets due to insufficient historical data. Another key limitation of this study is the inclusion of the COVID-19 pandemic period, which represents an extraordinary macroeconomic environment that may not be representative of normal market conditions. Future research could explore a broader range of crypto assets over an extended timeframe and sub-period analysis excluding the pandemic years or incorporate regime-switching models to account for structural breaks. Practical implications Understanding the response of different cryptocurrency assets to QE announcements can significantly assist investors in making informed decisions regarding asset allocation during these periods, guiding them in identifying the most profitable cryptocurrencies as alternatives to traditional assets. Originality/value In contrast to prior research, which primarily concentrates on the impact of QE on financial markets or confines its analysis to major and prominent crypto assets, this study provides a comprehensive examination of how specific cryptocurrency classes respond to macroeconomic policy changes.
With the global emphasis on sustainable development, green finance has emerged as a critical driver for balancing economic growth and environmental protection. Decentralized financial instruments (DeFi), leveraging unique technological advantages and operational mechanisms, are reshaping the traditional risk transfer logic of banks in the green finance sector. This paper explores the core characteristics of decentralized green financial instruments and their applications in green bonds, carbon trading, and other domains. Through a combination of theoretical analysis and case studies, it details how these instruments reconstruct traditional risk transfer pathways, alter risk-sharing models, and influence banks' risk management systems and financial market stability. By providing insights for banks to optimize risk management strategies in the new financial ecosystem, this study highlights the transformative role of decentralized green financial instruments in reshaping the landscape of financial risk management and their promising future developments.
Amid growing global urgency for climate action, innovative financial mechanisms are critical for advancing renewable energy transitions in developing economies. This study investigates the role of financial technology (fintech), with a focus on foreign portfolio investment (FPI), in influencing renewable energy investment (REINV) across 54 developing countries in Africa, Asia, and Latin America from 2010 to 2023. Employing a multi-method empirical approach, comprising Spatial Durbin Models (SDM), Quantile Regression (QR), Stochastic Frontier Analysis (SFA), and Spatial Quantile Regression (SQR), the research captures spatial dependencies, distributional heterogeneity, and efficiency dynamics. The SDM results indicate that FPI significantly increases REINV both directly (1.112) and indirectly through spillover effects (0.445), supported by significant spatial autocorrelation (0.334). Economic development and institutional quality also play key roles, with GDP per capita and institutional quality exerting positive and significant direct effects. Quantile regression reveals that FPI has a stronger influence at higher quantiles of REINV, with coefficients rising from 0.745 to 1.445, highlighting distributional inequality in fintech impact. SFA results show that FPI also enhances technical efficiency (0.912), though diminishing marginal returns are evident. Greater financial depth and electricity access reduce inefficiency, while inflation worsens it. Spatial quantile regression further confirms that regional spillovers are more pronounced among high-investment countries, underscoring the role of spatial dynamics in clean energy financing. The findings suggest that fintech can be a catalyst for renewable energy growth, especially in countries with higher institutional and financial capacity. Policy recommendations include strengthening digital infrastructure, enhancing regulatory coordination, and ensuring macroeconomic stability to fully leverage fintech's potential. Future research should explore emerging fintech tools such as decentralized finance and blockchain-based green bonds.
This study investigates the relationship between gas consumption and value transferred in Ethereum smart contracts, offering insights into resource utilization and efficiency within the blockchain ecosystem. Analyzing a dataset of 1,000 smart contracts, a moderate positive correlation r=0.45,p<0.05 was observed, indicating that higher gas consumption generally corresponds to larger financial transactions. The average gas consumption per contract was found to be 58,451,329.47 units, with a standard deviation of 20,123,456.89, highlighting significant variability in computational resource usage. Similarly, the average value transferred was 7,851.47 ETH, ranging from 0.001 ETH to over 100,000 ETH, showcasing the diverse financial applications of smart contracts. Efficiency analysis, measured as the ratio of value transferred to gas consumed, revealed an average efficiency of 0.00013 ETH per unit of gas, with some contracts achieving up to 0.01 ETH per unit of gas and others as low as 0.000007 ETH per unit of gas, reflecting varying levels of optimization. Outliers with disproportionately high gas consumption relative to value transferred were identified, suggesting inefficiencies or unique use cases. These findings underscore the importance of optimizing smart contract design to minimize gas costs and improve performance. Future research directions include functionality-specific analyses, anomaly detection, comparative studies across blockchain platforms, and exploring the economic implications of gas consumption. This work provides actionable insights for developers, researchers, and policymakers aiming to enhance the efficiency and sustainability of decentralized systems.
This paper examines the interconnection and wavelet coherence between the green cryptocurrency market and the green conventional market, utilizing daily data. The research period covers 1 July 2020 to 30 September 2024. Employing the time-varying parametric vector autoregression (TVP-VAR) model and wavelet coherence analysis, we capture both short- and long-term spillovers across markets. The results show that cryptocurrencies, particularly Binance and Litecoin, act as dominant transmitters of volatility and return shocks, while green conventional indices function mainly as receivers with strong self-dependence. Spillover intensity is highly time-varying, with peaks during periods of systemic stress, particularly during the COVID-19 pandemic, and troughs indicating diversification opportunities. These findings advance the literature on systemic risk and portfolio design by showing that crypto assets can simultaneously amplify vulnerabilities and enhance diversification when combined with green finance instruments. For policy, the results highlight the need for regulatory frameworks that integrate sustainability taxonomies, mandate environmental disclosures for digital assets, and incentivize energy-efficient blockchain adoption to align crypto markets with sustainable finance objectives. This research enhances our understanding of the interrelationship between green investments and cryptocurrencies, providing valuable insights for investors and policymakers on risk management and diversification strategies in an increasingly sustainable financial landscape.
Emma VerĂłnica Ramos Farroñån, Gary Christiam FarfĂĄn Chilicaus, LuĂs Edgardo Cruz Salinas, Liliana Correa Rojas · 8 authors
This systematic review synthesizes evidence on economic instruments that mobilize renewable-energy investment in emerging economies, analyzing 50 peer-reviewed studies published between 2015 and 2025 under PRISMA 2020. We advance an Institutional Capacity Integration Framework that ties instrument efficacy to regulatory, market, and coordination capabilities. Green bonds have mobilized roughly USD 500 billion yet work only where robust oversight and liquid markets exist, offering limited gains for decentralized access. Direct subsidies cut renewable electricity costs by 30â50% and connect 45 million people across varied contexts, but pose fiscalâsustainability risks. Carbon pricing schemes remain rare given their administrative complexity, while multilateral climate funds show moderate effectiveness (coefficients 0.3â0.8) dependent on national coordination strength. Bibliometric mapping with Bibliometrix reveals three fragmented paradigmsâmarket efficiency, state intervention, and international cooperationâand highlights geographic gaps: sub-Saharan Africa represents just 16% of studies despite acute financing barriers. Sixty-eight percent of articles employ descriptive designs, constraining causal inference and reflecting tensions between SDG 7 (affordable energy) and SDG 13 (climate action). Our framework rejects one-size-fits-all prescriptions, recommending phased, context-aligned pathways that progressively build capacity. Policymakers should tailor instrument mixes to institutional realities, and researchers must prioritize causal methods and underrepresented regions through focused initiatives for equitable global progress.
CÄtÄlin Gheorghe, Oana Panazan, Hind Alnafisah, Ahmed Jeribi
This study investigates the asymmetric responses of AI and ESG Exchange Traded Funds (ETFs) to geopolitical and financial uncertainty, with a focus on resilience across market regimes. The NASDAQ-100 and MSCI ESG Leaders indices are used as proxies for thematic ETFs, and their dynamic interlinkages are examined in relation to volatility indicators (VIX, GPR), alternative assets (Bitcoin, Ethereum, gold, oil, natural gas), and safe-haven currencies (CHF, JPY). A daily dataset spanning the 2016â2025 period is analyzed using Quantile-on-Quantile Regression (QQR) and Wavelet Coherence (WCO), enabling a granular assessment of nonlinear, regime-dependent behaviors across quantiles. Results reveal that ESG ETFs demonstrate stronger downside resilience under extreme uncertainty, maintaining stability even during periods of elevated geopolitical and financial risk. In contrast, AI-themed ETFs tend to outperform under moderate-risk conditions but exhibit greater vulnerability during systemic stress, reflecting differences in asset composition and investor risk perception. The findings contribute to the literature on ETF resilience and cross-asset contagion by highlighting differential behavior patterns under varying uncertainty regimes. Practical implications emerge for investors and policymakers seeking to enhance portfolio robustness through thematic diversification during market turbulence.
The integration of blockchain technology in carbon credit markets has emerged as a transformative solution to address inefficiencies in traditional trading mechanisms. This paper explores the role of tokenized carbon credits, decentralized trading platforms, and smart contracts in enhancing transparency, trust, and efficiency within voluntary and compliance-based carbon markets. By analyzing various blockchain-enabled carbon credit projects, including KlimaDAO, AirCarbon Exchange, and other decentralized initiatives, this research highlights the advantages of digital s regulatory uncertainty, scalability issues, and market adoption barriers are also examined. The findings suggest that blockchain-based carbon credit systems can significantly reduce fraud, increase liquidity, and support global sustainability goals. However, the success of these innovations depends on the development of standardized frameworks, cross-sector collaboration, and regulatory integration. This study provides insights into the evolving landscape of blockchain-driven carbon markets and proposes strategies for enhancing their effectiveness in combating climate change. tokenization, automated verification and decentralised governance models.
ABSTRACT This study aims to conduct an inâdepth analysis of the complex nonlinear dependence relationships between cryptocurrencies and gold within the stocks of BRICS countries. The study employs a GARCHâEVTâVineâCopula and wavelet coherence models to evaluate the interconnectedness, tail risk and Coâmovement pattern of these assets before and after the outbreak of COVIDâ19. The findings reveal that, prior to COVIDâ19, significant tail dependence existed between China's stock market, the cryptocurrency index, and the indices of India and Russia, while other indices exhibited only weak dependence. However, after the outbreak of COVIDâ19, the tail dependence among variables became more pronounced. The South African stock market appears to have emerged as the center of extreme lowerâtail risk spillovers among the studied variables. During the COVIDâ19 outbreak, cryptocurrency markets demonstrated stronger coherence with global stock markets than gold, especially in the US market, potentially compromising their diversification effectiveness. Furthermore, our empirical results were validated by the Kupiec test and the Christoffersen test. The results of this study not only enhance the theoretical understanding of risk management in emerging markets during periods of extreme market crises but also provide valuable insights for policymakers in formulating strategies to ensure financial market stability.
Yasir Habib, Noor Raida Abd Rahman, Shujahat Haider Hashmi, Minhaj Ali
Carbon neutrality and sustainable development goals have become globally imperative, as evidenced by the Paris Agreement, and the Nationally Determined Contributions mechanism. At the recently ended COP28 climate summit, the majority of the participating countries encountered these challenges through financial commitments to attain their objectives of carbon neutrality for sustainable development. Green finance and environmental decentralization play key roles in realizing these targets. The core focus of this study is to demystify the impacts of green finance and environmental decentralization on sustainable development by employing a panel dataset comprising 44 OECD countries, spanning 1995-2022. Ecological footprint serves as an indicator of sustainable development. Financial investment directed towards climate change mitigation and climate change adaptation technologies with alternative output-input green finance indicators are used as measures for green finance. A new index was devised that incorporates multiple indicators of environmental decentralization to gauge its influence on sustainable development. Using OLS, Oster coefficient stability, Lewbel 2SLS, and Kiviet instrumental variable techniques, our findings demonstrate that green finance significantly enhances sustainable development across countries. The empirical findings reveal that green finance and environmental decentralization exhibit a positive, statistically significant influence on sustainable development in OECD countries, while also playing a mitigating role in the reduction of environmental degradation. Considering these findings, it is imperative that OECD countries formulate and implement policies that foster green financing and empower local governments. This formulation and authorization are crucial for reducing pollution through the stimulation of innovation in climate change mitigation and adaptation technologies. In doing so, these policies will substantially reinforce the achievement of the United Nations' Sustainable Development Goals 9 and 12.
Blockchain is seen as an unusual innovative technology. Regardless of the fact that numerous educators have recognized the significance of blockchain, blockchain exploration is still in its infancy stage. As a result, the study looks at the latest research on blockchain, in reference to business and the economy. By in-depth analysis of the literature, we find that blockchain is the most recent phenomenon. The emergence of a paradigm shift in not just the way we think about financial matters but also how we can impact our planetâs future is being driven by the spread of green finance and blockchain technologies. Green finance is a financial system that supports sustainability by funding the power generation sector and encouraging the expansion of clean energy sources. Blockchain is a decentralized database that can be accessed by anyone.
This paper explores the causal relationship between the U.S. trade policy uncertainty and cryptocurrency returns using the quantile Granger causality test. Unlike traditional approaches that focus on average effects, this method captures asymmetric causal dynamics across the entire conditional distribution. The analysis employs two established indices of trade policy uncertainty developed by Caldara et al. (2020) and by Baker et al. (2016), ensuring robustness and mitigating potential biases from relying on a single measure. The empirical results indicate that changes in cryptocurrency prices consistently Granger cause movements in trade policy uncertainty across most quantiles, suggesting that cryptocurrencies may serve as early indicators of shifts in economic policy sentiment. In contrast, the effect of trade policy uncertainty on cryptocurrency returns is most pronounced in the tails of the distribution, highlighting a stronger influence during periods of extreme market conditions. These findings highlight the importance of accounting for nonlinear and asymmetric effects in assessing the interaction between economic policy uncertainty and cryptocurrency markets.
Green bonds have rapidly emerged as a transformative financial instrument within sustainable finance, channelling capital toward projects with explicit environmental benefits such as renewable energy, clean infrastructure, and climate adaptation. This paper provides a comprehensive investigation into the growth trajectory and impact of green bonds on sustainable finance, synthesizing evidence from empirical studies, systematic literature reviews, and industry analyses. The findings reveal that green bonds significantly enhance access to funding for environmentally friendly investments and contribute to market stability and transparency by requiring clear reporting and third-party verification of environmental outcomes. The issuance of green bonds is positively associated with factors such as renewable energy capacity and economic growth, while higher interest rates and market saturation in emission reductions can temper issuance growth. Sovereign green bonds, in particular, act as catalysts, fostering the expansion and quality of private green bond markets by setting benchmarks and improving green verification standards. Despite their promise, challenges persist, including risks of green washing and the lack of globally consistent certification standards. The integration of green bonds with innovative technologies such as decentralized finance (DeFi) is also explored as a means to further democratize and enhance the efficiency of sustainable finance. This research offers actionable insights for investors, policymakers, and academics seeking to leverage green bonds for the global transition to a green economy
This research examines the dynamic interaction between conventional financial assets, namely the US dollar, the S&P 500 index, gold and crude oil, and ten major green cryptocurrencies, focusing on their spillover linkages and hedging capacities during major global economic and geopolitical shocks. The study analyses daily data to uncover spillover effects using the innovative Quantile-Vector Autoregressive methodology developed by Cunado et al. (2023) . Results indicate that green cryptocurrencies significantly interact with other examined instruments. Algorand, Cardano, IOTA, TRON and Powerledger demonstrate the largest interactive effects, with the latter standing out as a consistent transmitter of influence across both crises, demonstrating that this sub-class of cryptocurrency is exhibiting elevated maturity. Traditional assets predominantly act as receivers of such risk dynamics from more speculative asset classes, with gold identified as an effective absorber of spillovers, especially in bear markets. Conversely, the US dollar and crude oil are identified as large transmitters of spillover impacts, a result found to be particularly influential in periods of geopolitical conflict. The study further reveals that green cryptocurrencies promoting trust, innovation, and renewable energy are more effectively connected with traditional investments than those focusing on financial services or business accessibility, presenting diversification opportunities during crises.
This study investigates the heterogeneous responses of Bitcoin (BTC), gold (GOLD), and green bonds (GBOND) to geopolitical risk (GPR) shocks across different market regimes and investment horizons. Using a triadic empirical framework that encompasses wavelet quantile-on-quantile regression (QQR), wavelet cross-quantilogram (WCQ), and advanced portfolio optimization strategies, our analysis captures asymmetric dependence, tail risks, and time-frequency dynamics from January 2015 to December 2024. Our results show that BTC consistently has strong hedging potential at lower quantiles, particularly during short-term stress, whereas GOLD and GBOND offer greater stability over medium- and long-term horizons. Conditional expected shortfall (CES) and extreme downside correlation (EDC) analyses highlight BTCâs resilience to extreme downside risks, whereas GOLD and GBOND serve primarily as long-term defensive assets. Portfolio optimization confirms BTCâs critical role in diversification under minimum correlation and connectedness strategies, and GBOND dominates variance-minimizing portfolios. These findings offer practical guidance for constructing robust, adaptive portfolios under geopolitical uncertainty.