Naveed Khan, OlaOluwa S. Yaya, Xuan Vinh Vo, Hassan Zada
In this paper, we examine the volatility and time-frequency connectedness among the financial stress index (FSI), cryptocurrencies namely, Bitcoin , Ethereum, Tether, BNB, Solana, and commodities namely, Gold, Silver, Copper, Platinum, and Brent Oil, using the quantile vector autoregressive (QVAR) frequency connectedness, wavelet coherence, and hedging effectiveness techniques, for the period spanning from June 2020 to December 2023. Findings indicate that the spillover effect among FSI, cryptocurrencies, and commodities substantially varies across different volatility conditions. Also, some cryptocurrencies are net receivers of shocks during normal market conditions, while other cryptocurrencies are net transmitters during extreme market conditions. We also find that, during the bullish market, some commodities (Platinum and Brent oil) are net receivers, while other commodities are net transmitters under extreme market conditions (lower quantiles). Similarly, findings further show that, under extreme volatility conditions (higher quantiles), cryptocurrencies and commodities are net receivers of shocks, while FSI is a net transmitter during these volatility conditions. Using frequency co-movement analysis, we find strong and weak correlations between these series in the short- and long-run for shorter periods. Furthermore, findings provide important implications for policymakers and portfolio managers to pay attention to long-term dynamics and design appropriate policies that mitigate the spillover effects.
Shusheng Ding, Xiangling Wu, Tianxiang Cui, John W. Goodell · 5 authors
Climate change is a highly controversial topic within the socioeconomic context. Climate Policy Uncertainty (CPU) arises from the process of climate policies formulation and implementation. This uncertainty impacts financial market volatilities, including cryptocurrency markets . In this paper, we demonstrate the substantial role of CPU in forecasting volatilities in cryptocurrency markets using Genetic Programming (GP). Our study shows that different cryptocurrency markets respond differently to CPU across time scales. Our paper contributes to the literature by illustrating the impact of CPU on cryptocurrency market volatilities and analyzes it across different time horizons. Second, we build three volatility forecasting models for different cryptocurrency markets by incorporating CPU, which outperform traditional models. Our models can thereby illuminate portfolio construction and hedging strategies, providing valuable insights for investors and policymakers.
Optimizing the tax business environment is of crucial significance for enhancing enterprise innovation efficiency and fostering sustainable development. This study utilizes the dataset of Chinese A-share listed companies from 2013 to 2022. By leveraging the quasi-natural experiment of the “Decentralization, Management and Service” reform pilot in the tax system, it adopts the multi-period difference-in-differences method to empirically investigate the impact of tax business environment optimization on enterprise innovation efficiency. The research reveals that the “Decentralization, Management, and Service” reform in the tax system exerts a significantly positive influence on enterprise innovation efficiency, and this result remains robust after a series of robustness tests. This optimization promotes enterprise innovation efficiency through three main channels: alleviating financing constraints, reducing transaction costs, and enhancing digitalization levels. The promoting effect is more pronounced for enterprises in mid-western regions, non-state-owned enterprises, large-scale enterprises, and those with high innovation endowments. Furthermore, it further contributes to the improvement of enterprise total factor productivity and the expansion of business scale, achieving the coordinated objectives of enhancing enterprise quality and efficiency and strengthening development momentum. These findings deepen our understanding of the economic implications of optimizing the tax business environment and offer empirical evidence for creating a conducive tax environment for the development of market entities.
This paper investigates the diversification, hedging, and safe-haven capabilities of Bitcoin and gold against blue economy and green finance assets using three different MGARCH models (DCC, ADCC, and GO-GARCH) during adverse events such as the COVID-19 health crisis and the 2022 Russia-Ukraine conflict. Blue economy assets, which refer to sectors that sustainably utilize ocean resources, are a key focus alongside green finance assets. The findings reveal that during crises, Bitcoin demonstrates robust safe-haven characteristics, particularly against blue economy assets like BJLE and OCEN. Conversely, gold exhibits pronounced safe-haven properties against specific blue economy and green finance assets such as BJLE and FAN. The GO-GARCH model highlights gold's strong diversification and safe-haven roles, especially against BJLE. Bitcoin, on the other hand, is more effective as a diversifier for PIO. Moreover, the GO-GARCH model consistently outperforms the DCC and ADCC models in terms of hedging effectiveness, showing that gold is the preferred hedging instrument for GNR and TAN, while Bitcoin is more effective for other blue and green assets. The results underscore the distinct roles of Bitcoin and gold in portfolio management strategies, offering insights for investors navigating market uncertainties in the context of sustainable investments.
Hanan Haider Ali, Sumathi Kumaraswamy, Sara Al Balooshi, Yomna Abdulla
This study examines the news impact, persistence and asymmetric effects of stock, oil and cryptocurrency markets in Gulf Cooperation Council (GCC) countries. The diagonal BEKK method is applied to the daily trading prices of three major cryptocurrencies, crude oil and four stock market indices from January 2018 to February 2024. The empirical results indicate a strong, significant volatility spillover between cryptocurrencies, oil and stock prices, but no return spillover effect among these asset classes. A negative news shock in cryptocurrency markets generates more volatility in GCC stock prices than positive news. The study suggests that cryptocurrency price movements are independent of other asset classes, providing portfolio diversification opportunities for investors in GCC countries.
Mark Ng, Monica Law, Brian Wong Chi Bo, Michael Liang
Purpose This study explores key factors influencing individuals' intentions to invest in NFTs, focusing on personal innovativeness, reward sensitivity, knowledge, subjective norms, perceived value and perceived risk. The aim is to provide insights into what motivates investors within this emerging market, addressing a gap in the understanding of NFT adoption from an investor perspective. Design/methodology/approach An online survey collected data from 272 participants in China and Hong Kong. The research employs partial least squares-structural equation modeling (PLS-SEM) to assess the relationships between various individual, social and market factors and NFT investment intentions. Findings The results suggest that personal innovativeness, reward sensitivity, NFT knowledge, subjective norms and perceived value positively impact NFT investment intentions. Additionally, age and income moderate the effects of subjective norms and perceived value on investment intentions, highlighting demographic influences. Practical implications For practitioners, insights into investor motivators can inform strategies to promote NFT investments, such as promoting the high reward potential, enhancing investor knowledge, leveraging social proof and emphasizing NFTs' perceived value. For academics, the findings open pathways for further research into investor psychology and the evolving dynamics of NFT and traditional investment markets. Originality/value This study advances NFT literature by identifying determinants of NFT investment behavior, a relatively uncharted area. By incorporating theories from investment behavior and technology adoption, it provides a new framework to understand the psychological and social drivers specific to NFT investments.
Yongsheng Guo, Ezaddin Yousef, Mirza Muhammad Naseer
This study investigates the key drivers and the economic and social impacts of cryptocurrency adoption. Based on panel data across 37 countries from 2020 to 2023, this research examines the interplay between cryptocurrency adoption and technology development, monetary policies, and economic and social development. Employing a mixed-methods approach, the research incorporates panel data analysis across multiple countries to explore correlations and causal relationships between these variables. The study found that technology development, measured by the Network Readiness Index (NRI) enables cryptocurrency adoption. Economic conditions measured by higher national inflation rates and monetary policy indicators, including lower interest and exchange rates are the key drivers for cryptocurrency adoption. The empirical findings reveal that cryptocurrency adoption has negative relationships with economic development measured by the GDP growth rate, unemployment rate, and social development represented by the governance quality corruption index. It implies that cryptocurrency is used as a virtual anchor (digital gold) for national inflation. Findings reveal how network readiness, economic conditions, and monetary policies contribute to fostering cryptocurrency adoption, while resulting in impacts on economic growth, labour markets, and governance. The research contributes to the literature by integrating technological, economic, and governance perspectives to elucidate the role of cryptocurrency in reshaping the global economic and social systems.
(1) Background: Cryptocurrencies have a substantial environmental impact. In particular, the mining procedure that is employed to produce and finalize the transaction is energy-intensive and generates carbon emissions. Consequently, the objective of the present investigation is to investigate the function of cryptocurrencies in a sustainable development. This research specifically investigates the function of stablecoins, a novel subject in finance and academia that has the potential to foster a sustainable business environment. (2) Methods: A bibliometric analysis was performed using the R statistical programming language together with the bibliometric tools Biblioshiny and VOSviewer to fulfill the research objective. Data were obtained from the Scopus database, and their selection was completed using the PRISMA methodology. (3) Results: The results of the current research highlight the crucial role of stablecoins in promoting an alternative decentralized financial sector, offering a unique opportunity for the market to create a more inclusive and environmentally friendly financial ecosystem. Moreover, research indicates that stablecoins might convert Ethereum into a stable currency and enhance their ecologically friendly path. (4) Conclusions: Stablecoins have become a crucial tool in the unpredictable bitcoin environment, offering stability in a tumultuous market. The research indicates that users need to acknowledge the sustainability of asset collateral, and so far, only the regulation of stablecoins is progressing in this area.
Samar S. Alharbi, Muhammad Naveed, Shoaib Ali, Faten Moussa
Using the TVP-VAR model, this study examines the connectedness between green cryptocurrencies and the individual components of the ESG (Environmental, Social, and Governance) stocks. Our sample period runs from November 10, 2017, to September 12, 2023. Our results indicate a moderate level of return and volatility transmission between green cryptocurrencies and ESG stocks. In line with theoretical argumentation, cryptocurrencies act as receivers of both return and volatility spillovers from the system, while stocks are the main transmitters. Our dynamic results show a substantial rise in total return and volatility connectedness of the system during the outset of the COVID-19 and Russia-Ukraine conflict, suggesting that global event amplifies the system connectedness. Moreover, the time-varying net results also exhibit a similar pattern, where the role of each asset changes during the turmoil period. Finally, our portfolio analysis suggests that green cryptocurrencies provide diversification to green stocks during both normal and turbulent periods. Additionally, they also emerge as effective hedges against ESG stocks across all market conditions. However, the hedge ratio increased during the COVID-19 pandemic, suggesting hedging becomes more expensive during turbulent periods. Our findings provide valuable insights for portfolio managers and policymakers regarding asset allocation, risk management, and the evolving dynamics between green cryptocurrencies and ESG stocks in an increasingly interconnected financial landscape.
Abstract This study examines the return connectedness between decentralized finance (DeFi)’s and the Association of Southeast Asian Nations (ASEAN) stock markets using the quantile vector autoregressive framework, which allows us to investigate the connectedness at conditional quantiles. Our sample includes four major DeFi’s and six ASEAN stock markets, spanning from March 2018 to December 2022. The static results indicate a moderate level of return transmission between the system at mean and median quantile. This propagation increases substantially under extreme market conditions, establishing an asymmetric transmission across quantiles. Despite being a relatively new asset class, DeFi dominates the equity market and acts as the primary shock transmitter to the system in most instances. The dynamic analysis reveals that total system connectedness fluctuates over time and quantiles. The total system connectedness peaked during the COVID-19 and the Russia–Ukraine conflict period, indicating the impact of global events on system transmission. The optimal weight and hedge ratio estimated using the DCC-GARCH model indicate that DeFi is beneficial for portfolio construction and risk management. The rising trend in dynamic optimal weight and hedge ratio during the COVID-19 pandemic demonstrates that investors should decrease their investments in DeFi and increase hedging costs. Therefore, portfolio managers and investors should readjust their portfolio allocation in a timely manner according to different market states to build additional effective hedging and diversification strategies to avoid large losses and to reduce portfolio risk exposure.
B J Santiyano, V F Tanty, J Hariwinarta, Shinta Amalina Hazrati Havidz
Abstract This study investigated the effects of macroeconomic and environmental factors on Bitcoin return. The analysis included 31 lower-income countries selected based on their GDP rankings from 2012 to 2022. Using 341 observations, we applied Feasible Generalized Least Squares (FGLS) and One-step System Generalized Method of Moments (GMM) to evaluate the effects of Gross Domestic Product (GDP), Inflation Rate (INF), CO2 Emissions (CO2E), Climate Policy Uncertainty (CPU), Global Price Energy Index (GPEI), and Cambridge Bitcoin Electricity Consumption Index (CBECI) on Bitcoin return. The findings revealed a significant negative relationship between CO2E and Bitcoin return, reflecting investor concerns about Bitcoin’s environmental impact. CBECI showed a significant positive effect, suggesting that higher electricity consumption associated with mining activities led to increased Bitcoin return. CPU was positively associated with Bitcoin return, indicating that investors might have viewed Bitcoin as a hedge against climate policy uncertainties. GPEI had a significant negative effect, demonstrating Bitcoin’s sensitivity to global energy price fluctuations. GDP and INF showed no significant effect on Bitcoin return, suggesting that macroeconomic indicators did not significantly impact Bitcoin’s value in emerging markets. These results offered essential guidance for investors and policymakers in emerging markets.
The increasing importance of emerging digital assets has created a multifaceted environmental challenge and opportunity. This paper explores one form of emerging digital asset, cryptocurrency (crypto), and the causal factors that drive its environmental impact. While cryptocurrency makes up a relatively small proportion of overall global electricity consumption (0.6 percent) and carbon dioxide equivalent emissions (0.2 percent), the electricity demand associated with its mining operations is growing rapidly. Its emissions profile surpasses that of traditional banking by a wide margin and, when compared on a climate damages per unit price basis, also exceeds that of gold mining by an order of magnitude. A scenario analysis reveals that cryptocurrency is set on an unsustainable path. The paper concludes with recommendations that include efforts to improve cryptocurrency's environmental performance and enable migration toward greater adoption of efficient algorithmic approaches; increased transparency of cryptocurrency mining operations through monitoring and reporting frameworks to promote grid stability and decarbonization; and investment that prioritizes the use of cryptocurrency for everyone's benefit.
This study explores how disruptive technologies, and financial innovations can strengthen climate and sustainable finance by addressing persistent structural, institutional, and social barriers. Using a systematic literature review, the research analyzes academic and policy sources to explore the integration of tools such as blockchain, artificial intelligence, and decentralized finance into climate finance frameworks. The central hypothesis is that these innovations enhance the transparency, accessibility, and effectiveness of climate finance, particularly in developing economies. Findings suggest that innovation can improve fund traceability, stakeholder inclusion, and project evaluation, contributing to more equitable and resilient financing mechanisms. However, technological adoption faces limitations related to regulatory gaps, technical capacity, and institutional resistance. The article’s originality lies in linking disruptive innovation to climate justice and proposing a framework for more just and efficient financial architecture. It contributes to climate policy, finance, and development debates by bridging technological potential with sustainability goals.
Abstract In recent decades, the rising challenges posed by climate change have prompted investors to take a keen interest in green assets and incorporate them into their portfolios to achieve optimal returns. Therefore, this article explores the static and dynamic connectedness between renewable energy stocks (solar, wind, and geothermal), green cryptocurrencies (Stellar, Nano, Cardona, and IOTA), and agricultural commodities (wheat, cocoa, coffee, corn, cotton, sugar, and soybean) using the TVP-VAR (time-varying parameter vector autoregression) framework offering novel empirical evidence for investors and portfolio managers. The connectedness is examined across two distinct sub-samples: during COVID-19 and post-COVID-19 times. Because the relevant connectedness can have implications for diversification benefits, we proceed with the computation of optimal weights, hedge ratios, and hedge effectiveness using the DCC-GARCH model. The main findings are as follows: We first find that green cryptocurrencies particularly Cardona and Stellar exhibit the highest spillovers to the network and wind energy stock has the least connectedness with the other markets. Second, the dynamic NET spillover indices reveal that cotton, cocoa, and coffee are consistently net receivers over the entire period except in the beginning of the pandemic. Third, renewable energy stocks exhibit diverse positions implying that the impact of the pandemic has varied significantly across the sectors. Finally, agricultural commodity depicts greater weights in the pandemic period under scoring the benefit of a diversified portfolio consisting of agriculture and green assets.
This study aims to explore the dynamic relationships among economic policy uncertainty (EPU), Bitcoin trading activity, and the NASDAQ index over the period from January 2, 2014, to March 21, 2023. Employing the dynamic conditional correlation–generalized autoregressive conditional heteroskedasticity (DCC‐GARCH) model, this research reveals significant time‐varying interdependencies between EPU and financial markets, with a specific focus on the Bitcoin sector. This paper extends the literature by examining EPU’s influence on trading volume and volatility spillovers during different market regimes and crisis events, including the COVID‐19 pandemic. The results demonstrate that the correlations between EPU and both Bitcoin and the NASDAQ index are dynamic and sensitive to market phases, with stronger effects observed during bull markets and heightened volatility during the pandemic. The findings provide new empirical evidence on the evolving role of EPU in shaping investor behavior and financial asset comovement. This study offers practical implications for investors, regulators, and policymakers, especially in designing risk management strategies under uncertainty.