Ritesh Patel, Mariya Gubareva, Muhammad Zubair Chishti
Using the cross-quantile & wavelet quantile correlation methods, we investigate the connectedness between cryptocurrency environment attention index (ICEA) and green crypto, renewable energy crypto, and green conventional market. The interdependence of ICEA with the considered assets is weak, providing investors with new avenues for reducing systematic risk of their portfolios. The cross-quantile correlations intensity between ICEA and green conventional emerging markets is especially low. ICEA appears as a strong diversifier for the Cardano cryptocurrency and sustainability-conscious industries from the developed economies. The WQC indicates a low level of connectedness of the ICEA with the selected assets. The ICEA does not remain significantly connected with any of the asset. This study provides valuable implications for the investors, portfolio managers and policy markets for the portfolio diversification.
Abstract In this paper, we study the return and volatility connectedness between cryptocurrencies and DeFi Tokens, considering the impact of different uncertainty indices on their connectivity. Initially, we estimate a TVP‐VAR model to obtain the total connectedness between the two markets. We find that returns on the cryptocurrencies transmit significantly larger shocks and, thus, are responsible for most variations in the majority of DeFis' returns. Then, to analyse the impact of uncertainty on total return and volatility connectedness, we use four factors, namely, Economic Policy Uncertainty (EPU), The Chicago Board Options Exchange Volatility Index (VIX), Infectious Disease Equity Market Volatility Tracker (ID‐EMV) and Geopolitical Risks (GPR). We find that except for geopolitical risks, all three measures have a positive impact on return and volatility connectedness, while GPR exerts a negative impact. Finally, we provide implications for researchers, market participants and policymakers.
Carbon dioxide emissions are a major cause of climate change and its negative impacts on the environment and human well-being. To address this problem, a blockchain-based decentralized system for carbon emission trading is proposed, allowing anyone to trade carbon allowances as a commodity. The proposed system leverages the advantages of blockchain technology, such as transparency, immutability, and security, to enable efficient and trustworthy transactions among peers without intermediaries. Additionally, the system provides flexibility by enabling customization of permits, represented as Non-Fungible Tokens, thereby enhancing market accessibility and engagement. A graph neural network for identity inference is introduced to infer the attributes of accounts on the blockchain, such as their type and behavior. This can help detect and prevent illegal or malicious activities on the chain, as well as understand and improve user behavior patterns and preferences. The aim is to increase market inclusiveness and diversity, reduce transaction costs and carbon price volatility, and enhance the traceability and verifiability of carbon emissions.
Bassam A. Ibrahim, Ahmed A. Elamer, Thamir Hamad Alasker, Marwa Ali Mohamed · 5 authors
Abstract The rapid rise of Bitcoin and its increasing global adoption has raised concerns about its impact on traditional markets, particularly in periods of economic turmoil and uncertainty such as the COVID-19 pandemic. This study examines the extent of the volatility contagion from the Bitcoin market to traditional markets, focusing on gold and six major stock markets (Japan, USA, UK, China, Germany, and France) using daily data from January 2, 2011, to June 2, 2022, with 2958 daily observations. We employ DCC-GARCH, wavelet coherence, and cascade-correlation network models to analyze the relationship between Bitcoin and those markets. Our results indicate long-term volatility contagion between Bitcoin and gold and short-term contagion during periods of market turmoil and uncertainty. We also find evidence of long-term contagion between Bitcoin and the six stock markets, with short-term contagion observed in Chinese and Japanese markets during COVID-19. These results suggest a risk of uncontrollable threats from Bitcoin volatility and highlight the need for measures to prevent infection transmission to local stock markets. Hedge funds, mutual funds, and individual and institutional investors can benefit from using our findings in their risk management strategies. Our research confirms the utility of the cascade-correlation network model as an innovative method to investigate intermarket contagion across diverse conditions. It holds significant implications for stock market investors and policymakers, providing evidence for potentially using cryptocurrencies for hedging, for diversification, or as a safe haven.
In the context of the “dual carbon” strategy, how to leverage green finance to promote China's wind power industry is a hot topic. Unlike existing literature, this article uses a nonparametric additive model to investigate the impact and mechanism of green finance on wind power development. Research has found that green finance has an inverted U-shaped nonlinear impact on wind power development, indicating that green finance has a more prominent contribution to the wind power industry in the early stages. Further mechanism research indicates that green finance affects the wind power industry through foreign direct investment and green technology innovation. Specifically, with the relaxation of foreign direct investment conditions in the energy sector, the role of foreign direct investment in promoting the wind power industry more prominent in the later stages. In the early stages, government support was greater, and green technology patents grew rapidly, driving green technology innovation to have a more significant impact on the wind power industry. In addition, the impact of fiscal decentralization, wind power prices, and environmental regulations on the wind power industry also exhibits significant nonlinear characteristics. This article helps to comprehensively understand the mechanism and impact of green finance on wind power development, and provides a reliable basis for optimizing green finance policy and effectively promoting wind power.
Abstract This study investigates the static and dynamic return and volatility spillovers between non-fungible tokens (NFTs) and conventional currencies using the time-varying parameter vector autoregressions approach. We reveal that the total connectedness between these markets is weak, implying that investors may increase the diversification benefits of their multicurrency portfolios by adding NFTs. We also find that NFTs are net transmitters of both return and volatility spillovers; however, in the case of return spillovers, the influence of NFTs on conventional currencies is more pronounced than that of volatility shock transmissions. The dynamic exercise reveals that the returns and volatility spillovers vary over time, largely increasing during the onset of the Covid-19 crisis, which deeply affected the relationship between NFTs and the conventional currencies markets. Our findings are useful for currency traders and NFT investors seeking to build effective cross-currency and cross-asset hedge strategies during systemic crises.
Van Le Thi Thuy, Tran Thi Kim Oanh, Nguyen Thi Hong Ha
Using the GJR-GARCH method, this study examines the safe-haven role of gold, US dollar, and Bitcoin over a period including the global financial crisis, the COVID-19 pandemic and the Russia-Ukraine conflict from 3 April 2006 to 19 May 2023. The study supports the hypothesis that the safe-haven role of assets changes over periods of crisis. Specifically, gold loses its role as a safe-haven asset during the COVID-19 pandemic, but this role has been restored in the Dutch, US and German markets during the Russia-Ukraine conflict. Similarly, Bitcoin is not a safe-haven asset during the COVID-19 pandemic but is a strong safe-haven asset for the stock markets of some European countries, and a weak safe-haven asset for China when the Russia-Ukraine conflict occurred. Only the USD acts as a stable safe-haven asset through periods of crisis. However, this role is weakened in Russia. These results partly help investors and portfolio managers choose a safe haven for their assets, especially during volatile market periods.
Based on China's provincial panel data from 2011 to 2020, this paper empirically analyzes the impact of digital financial inclusion(DFI) on regional energy consumption(ECI) using two-way fixed effects model, panel threshold effects model and instrumental variables regression. The results show that, firstly, DFI`s development has an obvious inhibitory effect on the intensity of regional energy consumption. Meanwhile, the heterogeneity analysis finds that there are obvious regional differences, differences in the degree of financial agglomeration and differences in their own dimensions in the inhibitory effect of DFI on regional energy consumption. Specifically, the energy-saving effect of digital finance is more obvious in the western region of China, in regions with a lower degree of financial agglomeration, and the strongest inhibitory effect is the breadth of digital inclusion coverage. In addition, the threshold effect analysis shows that the energy-saving effect of DFI not only increases with DFI`s development, but also exists in a non-linear pattern of significant "marginal increment" as the degree of economic decentralization increases. To this end, China should make greater efforts to develop DFI and optimize its industrial structure; formulate differentiated development policies that take into account the resource endowment, industrial structure and technological level of each region; and improve its macroeconomic governance system by taking into account the level of DFI`s development in the region, as well as the power of financial decision-making and financial management..
Wajdi Frikha, Azza Béjaoui, Aurelio F. Bariviera, Ahmed Jeribi
This paper analyzes the connectedness between gold, wheat, and crude oil futures, Bitcoin, carbon emission futures, and international stock markets in the G7, BRICS, and Gulf regions with the outbreak of exogenous and unexpected shocks related to health, banking, and political crises. To this end, we use a wavelet-based method on the returns of different assets during the period 2 January 2019, to 21 April 2023. The empirical findings show that the existence of time-varying linkages between markets is well documented and appears stronger during the COVID-19 pandemic. However, it seems to diminish for some associations with the advent of the Russia-Ukraine War. The empirical results also show that investor risk perceptions measured by the VIX are negatively and substantially linked to stock markets in different regions. Other interesting findings emerge from the connectedness analysis with the outbreak of Silicon Valley bankruptcy. In particular, Bitcoin tends to regain its role as a safe-haven asset against some G7 stock markets during the bank crisis. Such findings can provide valuable insights for investors and policymakers concerning the relationship between different markets during different crises.
Amro Saleem Alamaren, Korhan K. Gökmenoğlu, Nigar Taşpınar
Abstract This study investigates volatility spillovers and network connectedness among four cryptocurrencies (Bitcoin, Ethereum, Tether, and BNB coin), four energy companies (Exxon Mobil, Chevron, ConocoPhillips, and Nextera Energy), and four mega-technology companies (Apple, Microsoft, Alphabet, and Amazon) in the US. We analyze data for the period November 15, 2017–October 28, 2022 using methodologies in Diebold and Yilmaz (Int J Forecast 28(1):57–66, 2012) and Baruník and Křehlík (J Financ Economet 16(2):271–296 2018). Our analysis shows the COVID-19 pandemic amplified volatility spillovers, thereby intensifying the impact of financial contagion between markets. This finding indicates the impact of the pandemic on the US economy heightened risk transmission across markets. Moreover, we show that Bitcoin, Ethereum, Chevron, ConocoPhilips, Apple, and Microsoft are net volatility transmitters, while Tether, BNB, Exxon Mobil, Nextera Energy, Alphabet, and Amazon are net receivers Our results suggest that short-term volatility spillovers outweigh medium- and long-term spillovers, and that investors should be more concerned about short-term repercussions because they do not have enough time to act quickly to protect themselves from market risks when the US market is affected. Furthermore, in contrast to short-term dynamics, longer term patterns display superior hedging efficiency. The net-pairwise directional spillovers show that Alphabet and Amazon are the highest shock transmitters to other companies. The findings in this study have implications for both investors and policymakers.
Muneer Shaik, Mustafa Raza Rabbani, Mohd Atif, Ahmet Faruk Aysan · 6 authors
We investigate the dynamic volatility connectedness of geopolitical risk, stocks, bonds, bitcoin, gold, and oil from January 2018 to April 2022 in this study. We look at connectivity during the Pre-COVID, COVID, and Russian-Ukraine war subsamples. During the COVID-19 and Russian-Ukraine war periods, we find that conventional, Islamic, and sustainable stock indices are net volatility transmitters, whereas gold, US bonds, GPR, oil, and bitcoin are net volatility receivers. During the Russian-Ukraine war, the commodity index (DJCI) shifted from being a net recipient of volatility to a net transmitter of volatility. Furthermore, we discover that bilateral intercorrelations are strong within stock indices (DJWI, DJIM, and DJSI) but weak across all other financial assets. Our study has important implications for policymakers, regulators, investors, and financial market participants who want to improve their existing strategies for avoiding financial losses.
This article investigates the Ethereum Merge, which occurred on 15 September 2022, and we employ the time-series difference in differences (DiD) model and vector autoregression (VAR) models and analyse how the protocol change from proof-of-work to proof-of-stake (PoS) affects the dynamic relationship between cryptocurrency returns and network factors. The results show that the Merge caused a structural change between Ethereum and Bitcoin networks. The network factors of Ethereum show a significant increase compared to Bitcoin, the cointegration has been strengthened and the lag length is shortened after the Merge. The spillover effect on the Bitcoin network can be seen from both DiD and VAR, indicating the increasing impact of the Ethereum network on Bitcoin. The concern of losing the number of participants due to the implantation of PoS on cryptocurrency is not apparent on Ethereum Merge, and it increases the investors’ attention and involvement.
Abstract Non-fungible tokens (NFTs) are one-of-a-kind digital assets that are stored on a blockchain. Examples of NFTs include art (e.g., image, video, animation), collectables (e.g., autographs), and objects from games (e.g., weapons and poisons). NFTs provide content creators and artists a way to promote and sell their unique digital material online. NFT coins underpin the ecosystems that support NFTs and are a new and emerging asset class and, as a new and emerging asset class, NFT coins are not immune to economic uncertainty. This research seeks to address the following questions. What is the time and frequency relationship between economic uncertainty and NFT coins? Is the relationship similar across different NFT coins? As an emerging asset, do NFT coins exhibit explosive behavior and if so, what role does economic uncertainty play in their formation? Using a new Twitter-based economic uncertainty index and a related equity market uncertainty index it is found that wavelet coherence between NFT coin prices (ENJ, MANA, THETA, XTZ) and economic uncertainty or market uncertainty is strongest during the periods January 2020 to July 2020 and January 2022 to July 2022. Periods of high significance are centered around the 64-day scale. During periods of high coherence, economic and market uncertainty exhibit an out of phase relationship with NFT coin prices. Network connectedness shows that the highest connectedness occurred during 2020 and 2022 which is consistent with the findings from wavelet analysis. Infectious disease outbreaks (COVID-19), NFT coin price volatility, and Twitter-based economic uncertainty determine bubbles in NFT coin prices.
Ahmed Bossman, Mariya Gubareva, Samuel Kwaku Agyei, Xuan Vinh Vo
The growth of digital assets in recent periods are accompanied by negative externalities which raise concerns over sustainability. This has influenced the news content on both conventional and social media outlets, leading to the creation of the index of cryptocurrency environmental attention (ICEA). Given the pivotal role of social and conventional media in forming investors’ attitudes and behavior in financial markets, we address this issue from the perspective of Islamic stocks, which by their nature represent a class of Shariah-compliant sustainable assets. With the dataset spanning from 2014 onwards up to July 2022, we analyze how the ICEA induces the market dynamics in Islamic stocks covering diverse economic sectors. By applying the bi-wavelet-based time-frequency econometric framework, our empirical findings reveal time-varying levels of coherence between the ICEA and Islamic sectoral stocks, implying that the pricing and returns-generating dynamics across various economic sectors in Islamic markets are led by media coverage on environmental attention vis-à-vis the mining and trade of cryptocurrencies. Notwithstanding, our results indicate that the real “brick-and-mortar” categories of faith-based stocks, which contains the basic materials, consumer goods, industrials, and oil & gas sectors, provide attractive diversification attributes. Our findings are important for risk, portfolio, and policy management.
<p class="MsoNormal" style="margin-top: 12pt; text-align: justify;"><span lang="EN-US" style="font-family: 'times new roman', times, serif; font-size: 14pt;">This paper examines the efficiency, in its weak form, of the clean energy stock indices, Clean Coal Technologies, Clean Energy Fuels, and Wilderhill, as well as the cryptocurrencies classified as "dirty", due to their excessive energy consumption, such as Bitcoin (BTC), Ethereum (ETH), Ethereum Classic (ETH Classic), and Litecoin (LTC), from January 2020 to May 30, 2023. In order to meet the research objectives, the aim is to answer the following research question, namely whether: i) the events of 2020 and 2022 accentuated the persistence in the clean energy and dirty energy indices? The results show that clean energy indices such as digital currencies classified as "dirty" show autocorrelation in their returns; the prices are not independent and identically distributed (i.i.d). In conclusion, arbitrage strategies can be used to obtain abnormal returns, but caution is needed as prices can rise above their real market value and reduce trading profitability. This study contributes to the knowledge base on sustainable finance by teaching investors how to use forecasting strategies on the future values of their investments.</span></p>
This paper investigates the safe haven property of Bitcoin and the main precious metals in a state of crisis. This study focuses mainly on two critical periods, namely the COVID-19 health crisis and the Russian-Ukraine conflict. To achieve this objective, we first use the DCC-GARCH model to study the dynamic correlation between the returns of oil and the main precious metals. Then, we use a bivariate specification and a Bayesian specification to estimate the TVC-VAR model. The results of this study indicate the existence of similarity between Gold and Bitcoin in hedging capabilities. In fact, both have been weak havens during the COVID-19 health crisis and strong havens during the Russian-Ukrainian war period. On the other hand, the results suggest that ruthenium and iridium yields are uncorrelated or negatively correlated with Brent yields. In this respect, investors are called upon to keep their treasury in the form of iridium and ruthenium during this period of war. Similarly, investors were required to invest in these two assets during the COVID-19 period.
This paper investigates the long-run interaction between Bitcoin and Nasdaq, U.S. Dollar Index and commodities by applying weekly data from 1 January 2017 until 21 May 2023. This study uses FMOLS, DOLS and CCR methods to examine the long-run association between the variables. The results reveal a positive and significant relationship between Bitcoin and Nasdaq, as well as a similar positive association between Bitcoin and Oil prices. Notably, the U.S. Dollar Index exhibits a negative and significant impact on Bitcoin. However, results show that Gold does not have significant impact on Bitcoin. Finally, the results show that there are significant Granger causality from Nasdaq, oil and gold to Bitcoin.
Background and Aim: The advent of blockchain technology has brought about a significant transformation in the realms of finance and international trade, primarily through the implementation of a decentralized ledger system for conducting transactions. The present study aims to assess the efficacy and economic advantages of employing blockchain technology in the context of international trade financing. Specifically, it focuses on the potential decrease in transaction time and cost savings that Chinese domestic banks may experience as a result of adopting this technology. Materials and Methods: This research employs a quantitative methodology to assess the efficacy of blockchain technology in the context of international trade, with a specific emphasis on banking professionals. The study utilizes a cost-benefit analysis approach to maximize advantages and minimize drawbacks. Results: The research revealed that the implementation of blockchain technology has the potential to improve operational efficiency and mitigate transaction risks. However, it is important to note that this comes at the expense of increased costs, rendering it unsuitable for widespread adoption due to its unfavorable net benefit. Conclusion: The findings of the study indicate that the use of blockchain technology leads to enhanced operational efficiency and decreased transactional risks. However, it is important to note that this implementation also entails elevated costs, rendering it impractical for widespread adoption due to its unfavorable net benefit. The report posits that the advantages of operational efficiency offered by blockchain technology are overshadowed by the accompanying expenses, thereby advocating for a prudent approach to its implementation in the realm of international trade. The recommendations encompass many strategies such as the implementation of trial projects, conducting thorough cost-benefit analyses, using hybrid techniques, ensuring ongoing monitoring, and maintaining strict adherence to legal regulations.
Chengying He, Yong Li, Tianqi Wang, Salman Ali Shah
Abstract In light of the increasing investor interest in cryptocurrencies (CR) as alternative financial assets in financial markets, we sought to examine the connection between economic policy uncertainty (EPU) and cryptocurrencies. To do so, monthly data for Bitcoin (BTC), Ethereum (ETH), and Tether (THT) from January 2021 to April 2023 were employed. We utilized quantile regression and Granger causality analysis to investigate the relationship between EPU and cryptocurrencies. The initial results of this study suggest that EPU has little effect on the cryptocurrency market in the short-term. To enhance the strength and validity of these findings, we performed separate evaluations tailored to the unique contexts of the United States and China. The results revealed that the effects of EPU were adverse and statistically insignificant for China, while the situation differed slightly for the United States. Given that the United States has the most developed economy, its policies have a significant influence globally. As a result, cryptocurrencies have the potential to serve as efficient hedging tools. Furthermore, we incorporated nonlinear autoregressive distributed lag (NARDL) analysis to assess the asymmetric impact of EPU on cryptocurrencies by adopting both short-term and long-term perspectives. The outcomes demonstrated that both Bitcoin and Ethereum can serve as hedging tools in the short-term, although this utility diminishes in the long-term. Conversely, Tether displayed a positive association with EPU in the long-term. The findings of this study hold significance for policy-makers, offering valuable insights related to structuring efficient policies. The recommendations include fostering a rational framework for active participation from various stakeholders, including investors, governmental bodies, central banks, stock exchanges, and financial institutions. This collaborative effort aims to mitigate irrational fluctuations and enhance the acceptability of cryptocurrencies. In essence, this research underscores the potential of cryptocurrencies as a secure hedge against short-term EPU. However, we caution against assuming that any single cryptocurrency can consistently serve as a dependable investment haven.
Abstract This study seeks to identify the determinants of economic and environmental sustainability through green supply chain management (GSCM) and explore the moderating role of blockchain adoption in the relationships between GSCM and economic and environmental sustainability. The theoretical model was developed based on a natural‐resource‐based view and stakeholder theory. The structural equation modeling‐fuzzy set qualitative comparative analysis (SEM‐fsQCA) was used to analyze the data, which were gathered from 179 organizations in Malaysia. The SEM results showed that green technology, green marketing, and customer pressure are the factors that affect GSCM and enhance economic and environmental sustainability. The fsQCA findings supported SEM results by indicating that a combination of customer pressure, green technology, green marketing, and GSCM was necessary to achieve the highest level of an organization's economic and environmental sustainability. Moreover, the assessment of the moderating effect highlighted that blockchain adoption strengthened the association between GSCM and organization economic and environmental sustainability. The findings of this study help managers and organizations understand how blockchain adoption can enhance economic and environmental sustainability.
Purpose : It can be stated that in today’s competitive conditions, where portfolio management is very important, it has become necessary to examine the relationship between global financial assets and major cryptocurrencies, such as Bitcoin and Ethereum. This paper aims to investigate the cointegration and causalityrelationships between Bitcoin, Ethereum, and global financial assets such as gold, oil, the S&amp;P Global 100, the Dow Jones Commodity, and the US Dollar Indices, and to determine the diversification role of Bitcoin and Ethereum comparatively for the period between April 2016 and January 2024. Methodology: The ADF Unit Root, Johansen Cointegration, Granger Causality, Rolling Window Causality tests, and Variance Decomposition Analysis methods were used in the analysis process. Results: Based on the findings obtained from the paper, it was determined that Bitcoin and Ethereum have no cointegration with selected financial asset classes. Granger causality analysis results indicated that there were unidirectional causalities from Bitcoin and Ethereum prices to Dow Jones Commodity Index prices. In addition to the results of the Rolling Window causality tests, it was also determined that there are some causalities between Bitcoin, Ethereum, and other variables, especially after the 2021-2022 period. Conclusion: It can be concluded that Bitcoin and Ethereum are effective portfolio diversifiers throughout the entire period; however, the diversification effects of Bitcoin and Ethereum weakened towards the end of the review period. Therefore, it can be said that Bitcoin and Ethereum act similarly in the global investment portfolio.