This study analyzes the return and volatility spillover between oil-gold and oil-Bitcoin pairs before and after the COVID-19 pandemic using the Dynamic Conditional Correlation Generalized Autoregressive Conditional Heteroskedasticity (DCC-GARCH) model. The data used in this research consists of daily returns of oil, gold, and Bitcoin from January 2018 to December 2021 to understand volatility dynamics. The data period is divided into two phases: before and after theCOVID-19 pandemic. The analysis results show no significant volatility spillover between oil andgold. The relationship between oil and Bitcoin points to volatility spillover, although not following an identical pattern. The absence of volatility spillover indicates that markets or assets are more independent of each other. This reduces the interdependence between markets, making it more challenging to predict market movements based on the behavior of other markets.
This study examines the relations of Bitcoin (BTC) prices and fluctuations with gold, USD, oil, VIX index, hedging, and diversification features in Turkiye. For this purpose, wavelet coherence and dynamic conditional correlations (DCCs) were used in the study. Our research explores whether the bubble behavior patterns in BTC prices during the COVID-19 pandemic can be used in the short term to protect against the bubble behavior in the markets that are the subject of this research and vice versa. However, whether other assets can be used to manage and hedge BTC's downside risk is also being explored. The aim is to understand how and at what level critical financial instruments and indicators are affected by each other in times of crisis and economic recession, such as pandemics, and to present valuable results to decision-makers. The sample for this study includes TĂŒrkiye for the period between 12/31/2019 and 13/07/2022. Wavelet Coherence and DCC-GARCH results indicate significant positive and negative movements of BTC prices with gold, oil, USD prices, and the VIX fear index during the pandemic. We find evidence of volatility persistence, causality, and phase differences between BTC and other financial instruments and indicators.
This study aims to examine the intricate dynamics between BRICS traditional stock assets and the evolving landscape of cryptocurrencies. Using a time-varying parameter vector autoregression model (TVP-VAR), we have analyzed data from the BRICS stock market index, cryptocurrencies, and indicators from January 6, 2015, to June 29, 2023. The results show that three out of the five BRICS stock markets serve as primary sources of shocks that subsequently affect the financial network. The transcontinental (TCI) value derived from the dynamic conditional connectedness using the TVP-VAR model demonstrates a higher explanatory power than the static connectedness observed using the standard VAR model. The discoveries from this study offer valuable insights for corporations, investors, and regulators concerning systematic risk and investment strategies.
Adela BĂąrĂŁ, Irina Georgescu, SimonaâVasilica Oprea, Marian Pompiliu Cristescu
In this paper, we mainly investigate three variables from the price volatility point of view: Brent crude oil, S&P500 and Bitcoin (BTCUSD), aiming to underline the impact of price volatility. Brent crude oil accounts for two-thirds of the oil market. Its price volatility has a significant impact on environmental, transportation, mobility, economic and social aspects that affect sustainability. This paper conducts an extensive examination of the forecasting capabilities of various GARCH (Generalized Autoregressive Conditional Heteroskedasticity) models, identifying the most suitable GARCH model for estimating Value at Risk (VaR) for Brent crude oil price. The assessment of VaR for different GARCH models is carried out using Kupiecâs Probability of Failure (POF) test and Christoffersenâs test. This study leverages Brent crude oil data spanning from 2019 to 2023. Additionally, to prove the robustness of the GARCH models, we further consider the West Texas Intermediate (WTI) and Dubai oil prices that are the dominant in the U.S and Asian market. The investigation identifies the TGARCH(1,1) Skewed Student model as the optimal choice among 9 models considered for VaR estimation. The results show that TGARCH Skewed Student model surpasses the other models in the study, proving its superiority in forecasting Brent crude oil price volatility and facilitating VaR estimation. A VaR of 0.044 with a 95% confidence level means that there is a 95% chance that the portfolio will not lose more than 4.4% of its value. By incorporating skewness in addition to volatility asymmetry, the Skewed GARCH-type models provide a more realistic representation of the underlying return distribution. Furthermore, the most appropriate GARCH-type model for WTI crude oil is EGARCH(1,1) Skewed Student, with a VaR coverage of 0.39. The most appropriate GARCH-type model for Dubai crude oil is TGARCH(1,1) Skewed Student, with a VaR coverage of 0.17. Both WTI oil and Dubai crude oil have a coverage that exceeds 5%, implying a more conservative approach to estimating potential losses. Furthermore, the unidirectional causalities BTCUSDâBRENT and BTCUSDâS&P500 are identified. The results of the current research have practical implications for both importing and exporting countries, policy makers and investors. For companies in the oil sector, VaR informs operational decisions, such as production levels, capital expenditure and inventory management, by providing insights into market risk. Moreover, understanding the risks associated with oil aids in long-term strategic planning.
<abstract> <p>In this article, we describe the novel properties of Bitcoin and green financial assets and empirically examine the connectedness between Bitcoin and two green financial assets (i.e., carbon emissions, green bonds) and two representative markets of conventional assets (i.e., oil and emerging stock). This study also analyzes whether Bitcoin, carbon, green bonds, oil, and emerging stock assets can hedge against any market turbulence. From observed findings, Bitcoin was not an effective substitute for green bond assets. Thus, Bitcoin is not a valuable hedge instrument to substitute green bonds to mitigate climate risks. More precisely, the findings of the study show that carbon assets outperform emerging stock assets amidst the COVID-19 crisis, while the stock markets incurred significant losses. Crucially, the innovative findings also played an important role for policymakers interested in decarbonizing the crypto-assets.</p> </abstract>
This study emphasizes the implication of dynamic connection between digital currency and Nigerian economic growth rate by focusing attention on Bitcoin, Ethereum and Litecoin with respect to their returns and volatility from 2010Q4 to 2022Q3. As a way to have a robust estimation, we model our analysis using ARDL model and granger causality test. This model is rather useful to have both short and long run estimations. Importantly the studyâs outcome conforms with the fundamentals. By findings from the study, the trend analysis suggests that the countryâs exchange rate moves in line with digital currency activities while at the same time signifies some implication on the growth rate of the Nigerian economy. While lower returns for Bitcoin and Litecoin increase growth rate, the return for Ethereum rather move in the same direction as the growth rate. This indeed suggest that most Nigerians into digital currency activities often engage in portfolio diversification among available coins. The study further found that low volatility in the market will raise (significantly especially for Ethereum) growth rate of the economy while causal implication run from returns and volatilities of these coins to growth and exchange rates. Indeed, the findings have important policy implication for the Nigerian economy which suggests paying good attention to digital currency activities in the country and formulating necessary policies to improve it.
In order to explore the impact of the application of blockchain technology on enterprise performance, as well as the mechanism of enterprise risk and the information disclosure quality on this impact process, and taking the data of A-share listed companies in Chinaâs manufacturing industry from 2015 to 2022 as a research sample, this paper adopts methods such as multi-period difference-in-differences (DID) modeling to conduct an empirical investigation. Findings: The application of blockchain technology can improve enterprise performance. Enterprise risk plays a partial mediating effect, because blockchain technology can reduce enterprise risk and thereby improve enterprise performance. Information disclosure quality has an inhibitory influence on the process by which blockchain technology affects enterprise risk and a facilitating influence on the process by which enterprise risk affects enterprise performance. The results show that manufacturing enterprises with low information disclosure quality can reduce enterprise risk by combining with blockchain technology in production, management, and other aspects, thus improving enterprise performance and promoting sustainable development of enterprise economy.
An overview of blockchain fundamentals and its potential benefits for sustainability is provided. The role of expertise as an intermediary on the blockchain to drive transparency and accountability is examined. This research examines the potential of blockchain technology in the field of economic management and to drive future sustainable development in emerging companies, which are referred to as hidden champions. This study addresses the need for transparent and responsive practices that promote social stability, economic growth, and environmental sustainability. The goals are to analyze economic functions, investigate the formation of appropriate economic patterns, facilitate equitable distribution, and support environmental protection efforts. The research method includes case studies and theoretical frameworks to collect relevant data. The results emphasize the importance of balancing competing interests, promoting security, and strengthening inclusive decision-making processes. This study emphasizes the intersection between economic development and environmental protection and highlights the role of sustainability criteria in guiding land use practices. The conclusion emphasizes that sustainable economic practices are critical for social, economic and environmental development, especially in emerging economies. Practical recommendations are provided to policymakers and stakeholders to improve economic governance frameworks and help achieve the Sustainable Development Goals.
As a pivotal innovation in digital infrastructure, blockchain ledger technology catalyzes the development of nascent business paradigms and applications globally. Utilizing Rothwell and Zegveld's taxonomy of twelve innovation policy tools, this study offers a nuanced comparison of domestic blockchain policies, dissecting supply, environment, and demand-driven policy dimensions to distill prevailing strategic orientations towards blockchain healthcare adoption. The findings indicate that blockchain technology has seen rapid growth in the healthcare industry. However, a certain misalignment exists between the corporate and policy layers in terms of supply and demand. While companies focus more on technological applications, existing policies are geared towards regulations and governance. Government emphasis lies on legal supervision through environmental policies, aiming to guide the standardization and regulation of blockchain technology. This maintains a balance between encouraging innovation and market and legal regulatory order, thereby providing a reference for the development of the distributed intelligent healthcare industry in our country.
This study seeks to investigate how distributed ledger technology can be applied to the green bond market. Second, this study examines how green bonds can finance the suck cost of decarbonizing the ammonia industry. Third, this study seeks to forecast the spot price of ammonia. This forecast is relevant since the bondâs coupon should be indexed and linked to the price of ammonia. The proposed tokenized indexed-green bond is a new idea that leverages the technologies of distributed ledgers, indexation, and green bonds. No study to current date has undertaken such research that integrates these technologies to fund the decarbonization of the ammonia industry. Data was collected on the spot price of ammonia from the Central Bank of Trinidad and Tobago online database at the monthly frequency over the January 1991 to June 2023 period. The applied forecasting methodology was a hybrid framework combining Particle Swarm Optimization and Support Vector Regression. This study found that an out-of-sample forecast for ammonia prices would be US$438.89/ton in the 1st quarter, US$289.99/ton by the 2nd quarter, US$448.30/ton by the 3rd quarter, and US$331.57/ton by the 4th quarter. The decarbonization of the ammonia industry is technically possible. Economically, it would involve leveraging several technologies such as green bond financing, tokenization, and indexation. Received: 26 May 2023 | Revised: 1 September 2023 | Accepted: 3 December 2023 Conflicts of Interest The author declares that he has no conflicts of interest to this work. Data Availability Statement Data available on request from the corresponding author upon reasonable request. Author Contribution Statement Don Charles: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, resources, data curation, Writing - original draft, Writing - review & editing, Visualization, Supervision, Project administration.
<abstract> <p>In this paper, we aim to uncover the dynamic spillover effects of Bitcoin environmental attention (EBEA) on major asset classes: Carbon emission, crude oil and gold futures, and analyze whether the integration of Bitcoin into portfolio allocation performance. In this study, we document the properties of futures assets and empirically investigate their dynamic correlation between Bitcoin, carbon emission, oil and gold futures. Overall, it is evident that the volatility of Bitcoin, as well as other prominent returns, exhibit an asymmetric response to good and bad news. Additionally, we evaluate the hedge potential benefits of these emerging futures assets for market participants. The evidence supports the idea that the leading cryptocurrency-Bitcoin can be a suitable hedge instrument after the COVID-19 pandemic outbreak. More importantly, our analysis of the portfolio's performance shows that carbon emission futures are diversification benefit products in most of the considered cases. Notably, incorporating carbon futures into portfolios may attract new investors to carbon markets for double goals of risk diversification. These findings also provide insightful evidence to investors, crypto traders, and portfolio managers in terms of hedging strategy, diversification and risk aversion <sup>[<xref ref-type="bibr" rid="b19">19</xref>,<xref ref-type="bibr" rid="b20">20</xref>,<xref ref-type="bibr" rid="b21">21</xref>,<xref ref-type="bibr" rid="b22">22</xref>,<xref ref-type="bibr" rid="b23">23</xref>,<xref ref-type="bibr" rid="b24">24</xref>,<xref ref-type="bibr" rid="b25">25</xref>]</sup>.</p> </abstract>
This paper explores the role of Economic Policy Uncertainty (EPU) as driver of the Bitcoin public attention. Using Google trends data from January 2010 to November 2021 in a set of 22 countries, a Principal Components Analysis reveals a strong unique commonality on the internet searching patterns for Bitcoin across countries, which suggests that the potential explaining factors of the Bitcoin attention should be global instead of local. The multivariate analysis corroborates this hypothesis since EPU at the country level does not play a significant role in explaining the searching patterns on Google for Bitcoin, while the global EPU does.
Cryptocurrencies, which started with Bitcoin, which was released differently from traditional payment and investment tools, have large transaction volumes today. In addition to the many economic benefits of cryptocurrencies, which are used both as a payment tool and as a financial investment tool, high energy consumption and a heavy carbon footprint come with them. With the owner of the automaker Tesla stating that he is worried about the increasing use of fossil fuels in Bitcoin mining and cutting its support for Bitcoin, the price of Bitcoin has fallen sharply, while green cryptocurrencies have reached historical peaks. This situation reminded the investors that they should handle risky investments carefully and also highlighted the importance of green investment tools. Understanding the relationship between green cryptocurrencies and other assets is essential for investors looking to expand their portfolios and seize emerging opportunities. In this direction, the study examined whether green cryptocurrencies are a safe haven against non-green cryptocurrencies in the period of January 2022âJuly 2023. In the analysis, DCC-GARCH analysis, risk, and return analyses were performed for safe haven. According to the analysis' findings, among cryptocurrencies, green cryptocurrencies are most likely to be a safe haven for investors.
Shoaib Ali, Muhammad Naveed, Hasan Hanif, Mariya Gubareva
This study investigates the return spillover between the Islamic gold-backed cryptocurrencies and equity markets of the Gulf Cooperation Council (GCC) countries. The study utilizes the QVAR method to determine the quantile connectedness among the asset classes and identify optimal portfolio weights across different economic conditions. The results show that the GCC economies have stronger connections with each other than with the cryptocurrencies. However, there is an increase in connections between the GCC economies and cryptocurrencies during extreme events. This suggests that extreme news can amplify the relationship between the Islamic cryptocurrencies and GCC markets. The findings suggest that asymmetric tails exist in the connectedness between the asset classes, meaning that the relationship between them is stronger during extreme market conditions. Accordingly, the dynamic connectedness analysis reveals varying patterns of connectedness across different periods, outlining pivotal portfolio implications. The study also suggests optimal weights for portfolio managers and investors and outlines the least expensive hedging strategy. The research proposes that investors in the GCC region could potentially mitigate the risk of their Islamic equity portfolios by incorporating the Islamic Shariah-compliant gold-backed cryptocurrencies in their portfolio. Further studies could explore the role of other factors such as liquidity, market volatility, and investor sentiment in the relationship between asset classes. Future research could examine the effects of other types of news, such as macroeconomic news, on the relationship between asset classes. Additional research could focus on the implications of incorporating Islamic gold-backed cryptocurrencies in a portfolio for investors beyond the GCC region.
This paper explores the connectedness between the cryptocurrency environmental attention index and four major green financial assets using time-varying parameter vector autoregression model from January 2014 to December 2021. Findings reveal that connectedness follows a heterogeneous trajectory over time. Results show evidence of higher volatility transmission during the COVID-19 period relative to the entire sample period. The high volatility transmission is a source of concern to policymakers, green stakeholders, and investors, due to limited diversification options.
What do we know about the interrelations between economic inequality, ecology and the increased use of Bitcoin? The aim of the paper was to empirically test the relationship between economic and ecological effects related to the increase in Bitcoinâs network hashrate in a selection of countries that have the highest influx of crypto-mining. To test these three types of relationships, I collected a dataset concerning Bitcoin indicators, economic indicators and ecological indicators that were obtained from multiple trustworthy sources: OECD, World Bank, Fred Data, World Inequality Database (WID). Handling the data challenges, I used this unique panel dataset to explore the relationship between Bitcoinâs hashrate and two types of outcomes: (i) economic outcomes (such as the GDP which as we know relates to inequalities through the Kuznets curve) or direct measures of inequality (such as, income inequality (GINI) and the share of people with top 1% of income and 1% of wealth), and (ii) ecological outcomes (such as carbon emissions, carbon footprint and electronic waste). I found that the Bitcoin currency associates with certain redistribution of wealth, but the accumulation of crypto-currency-related wealth itself remains still concentrated in the wealth of the top 1%. Also, there is evidence for certain nonlinearities in the relationships with the ecological degradation, echoing the concept of the Kuznets curve.
There is a growing interest in understanding the energy and environmental footprint of digital currencies, specifically in cryptocurrencies such as Bitcoin and Ethereum. These cryptocurrencies are operated by a geographically distributed network of computing nodes, making it hard to estimate their energy consumption accurately. Existing studies, both in academia and industry, attempt to model cryptocurrency energy consumption often based on a number of assumptions, for instance, about the hardware in use or the geographic distribution of the computing nodes. A number of these studies have already been widely criticized for their design choices and subsequent over- or under-estimation of energy use. In this study, we evaluate the reliability of prior models and estimates by leveraging existing scientific literature from fields cognizant of blockchain, such as social energy sciences and information systems. We first design a quality assessment framework based on existing research, and we then conduct a systematic literature review examining scientific and non-academic literature demonstrating common issues and potential avenues of addressing these issues. Our goal with this article is to to advance the field by promoting scientific rigor in studies focusing on blockchain energy footprint. To that end, we provide a novel set of codes of conduct for the five most widely used research methodologies: quantitative energy modeling, literature reviews, data analysis and statistics, case studies, and experiments. We envision that this code of conduct would assist in standardizing the design and assessment of studies focusing on blockchain-based systems' energy and environmental footprint.
In recent years, blockchain technology has seen significant growth and widespread adoption in various industries. However, one major drawback of blockchain investments is their substantial energy consumption, which has negative impacts on both the economy and the environment. The main cause of concern is the generation of atmospheric carbon emissions resulting from excessive energy usage. This research study aims to identify blockchain networks and systems that assert themselves as environmentally friendly and determine which of them produces the least amount of carbon emissions, such as Cardano, Tezos, and Bitgreen. This has been accomplished by following a comprehensive hybrid literature review. Our study has identified 23 blockchain networks that consume significantly less power and release fewer carbon dioxide emissions compared to the Bitcoin network. Some of these environmentally friendly networks include Algorand, Fantom, MobileCoin, and Electroneum. Additionally, we have found various projects and organizations that support greener blockchain initiatives, such as the Renewable Energy Certificate Mechanism, Green Digital Finance Alliance, GreenTrust, and the Energy Web Foundation. While several projects in this area have been recognized and examined, comprehensive research and analysis are still needed to provide empirical evidence regarding the power consumption and carbon dioxide emissions of these claimed environmentally friendly blockchains. This is due to the relatively early stage of development in this field.
The effect of the RussiaâUkraine war has fluctuated in Europe and Asia's economic conjuncture by virtue of constant shifting balances. The portfolios of investors who made decisions in uncertain conditions have been affected by these fluctuations that have caused volatility in the stock market's indexes. The aim of this study is to examine the impact of the Fear Index (FI), the Dollar Index, and Bitcoin on the volatility of the Borsa Istanbul 100 Index (BIST). Autoregressive distributed lag (ARDL) time series analysis was used for the study, which revealed that the Dollar Index has no effect on volatility, while the FI was found to have an effect on volatility both in the short and long runs. In addition, Bitcoin was determined to have an effect on volatility only in the long run. When the period of the data used is examined, the outbreak of the RussiaâUkraine war in February 2022 is thought to be the reason for the increase in the FI. It can be assumed that the decisions of investors to invest in the BIST were adversely affected by the war as a natural consequence of this, and investors who ceased investing in the BIST index opted to invest elsewhere.
Yang Junhua, Samuel Kwaku Agyei, Ahmed Bossman, Mariya Gubareva · 5 authors
To address ESG stock susceptibility to episodic shocks in financial markets, we use nonparametric quantile-based techniques applied to the 2014-2022 period. We (i) analyse the ability of traditional assets to predict ESG stocks returns, (ii) explore whether oil or gold serves as a safe haven for ESG stocks, and (iii) ascertain how ESG stocks respond to market sentiment, crypto-based uncertainty, and geopolitical risk (GPR). We find that gold, oil, market sentiment (tracked by the VIX), the implied volatility of crude oil (OVX) and GPR are significant predictors of ESG returns. None of gold or oil serves as a safe haven for ESG stocks, both acting just as diversifiers. In their turn, ESG could stocks hedge against the shocks from GPR and cryptocurrency-triggered market uncertainties in bearish states of the market. These findings are important for asset allocation and risk management, assisting investors in the already ongoing switch from ordinary to sustainable investments.
Abstract Since the onset of the COVID-19 pandemic, financial and commodity markets have exhibited significant volatility and displayed fat tail properties, deviating from the normal probability curve. The recent Russia-Ukraine war has further disrupted these markets, attracting considerable attention from both researchers and practitioners due to the occurrence of consecutive black swan events within a short timeframe. In this study, we utilized the Quantile-VAR technique to examine the interconnectedness and spillover effects between African equity markets and international financial/commodity assets. Daily data spanning from January 3, 2020, to September 6, 2022, was analyzed to capture tail risks. Our main findings can be summarized as follows. Firstly, the level of connectedness in returns is more pronounced in the lower and upper tails compared to the median. Secondly, during times of crisis, African equity markets primarily serve as recipients of systemic shocks. Lastly, assets such as Silver, Gold, and Natural Gas exhibit greater resilience to systemic shocks, validating their suitability as hedging instruments for African equities, in contrast to cryptocurrencies and international exchange rates. These findings carry significant implications for policymakers and investors in Africa equities.