Employing the vector auto-regression based on generalized forecast error variance decomposition, this paper investigates the connectedness of non-fungible tokens (NFTs) with precious and industrial metals and compares the results with those for conventional cryptocurrencies (CCCs). Our study scrutinizes separately the total static and the net dynamic spillovers of returns and volatilities from March 2018 to August 2021. We evidence that both, the total return and total volatility connectedness indices for the NFTs-metals framework are below the respective indices for the CCCs-metals framework, indicating new avenues for hedging and harvesting diversification benefits of NFT exposures. We provide empirical evidence that the NFTs are distinct from the CCCs not only in terms of the volatility spillovers, but in terms of the return spillovers too. In addition, we observe the decoupling in the net volatility spillovers between the precious and non-precious metals due to the COVID-19 meltdown. COVID-19 makes precious metals transmit volatility while industrial metals continue acting as net receivers of volatility shocks. Optimal weight and hedge ratios are presented for NFT-metal and crypto-metal pairs. These findings provide potential implications for investors and policy makers.
Blockchain technology is very useful. This paper considers the application of blockchain technology to smart contracts, green certification, and market information disclosure, and introduces the carbon trading market price as a parameter to solve the dynamic incentive problem of the government for port enterprises to reduce emissions under the carbon trading policy. Based on the state change of port carbon emission reduction, this paper uses principal–agent theory to construct the dynamic incentive contract model of government without blockchain, with blockchain, and when carbon trading is considered under blockchain, respectively, and uses the optimal control method to solve and analyze the model. This paper finds that only when the opportunity cost of port enterprises is greater than a certain critical point and the fixed cost of blockchain is less than a certain critical point, the implementation of blockchain will help improve government efficiency. However, only when the critical value of carbon emission reduction of port enterprises and the unit operating cost of blockchain are small, the government should start the carbon trading market under blockchain technology. Through numerical simulation, this paper also finds that it is usually beneficial for the government to regulate and appropriately increase the carbon trading market price.
Zaghum Umar, Sun‐Yong Choi, Тамара Теплова, Tatiana V. Sokolova
Are green investments decoupled from the dirty investment such as the fossil fuel markets? We address this issue by extending the literature on environmental, social, and governance (ESG) assets by examining the dynamic relationship between fossil fuels and digital ESG assets proxied by green cryptocurrencies using the TVP-VAR(Time-varying parameter vector auto regression) spillover framework. Furthermore, we analyze the hedging attributes of green cryptocurrencies and fossil fuels in a minimum connectedness framework. The main findings are as follows: First, green cryptocurrencies are the main shock transmitters in all asset systems. Second, the dynamic connectedness between green cryptocurrencies and fossil fuels increased during the COVID-19 and Russia-Ukraine conflicts. Third, green cryptocurrencies have shown considerable hedging effectiveness against the fossil fuels. Our study has important implications for investors, regulators, and policy makers, such as shifting to green cryptocurrencies, regulation of carbon footprint, and promoting eco-friendly assets.
This study investigates the interconnectedness of the Islamic stock market, Bullion, and Bitcoin as diversifiers for portfolios, exploring their role as hedges and safe havens. The analysis covers the period from January 2015 to December 2022, with a particular focus on the influence of the COVID-19 pandemic and the Russia-Ukraine War on the MSCI World Islamic Index, bullions (Gold, Silver, Platinum, Nickel, Palladium, and Aluminium), and Bitcoin, employing a time-varying parameter vector autoregression (TVP-VAR) model. During crisis periods, our findings reveal that the transmission and reception of shocks among these assets varied, with a heightened level of co-movement observed during the pandemic and war periods. These results emphasise the importance of considering the dynamic nature of financial assets' connectedness in asset investment decisions, particularly in times of crisis. Furthermore, the findings suggest that Bullion can serve as a hedge for both Bitcoin and the Islamic stock market. The study also explores the optimal diversification of investment portfolios and highlights the importance of adhering to Islamic principles in portfolio diversification. By integrating Islamic rules into the diversification process, investors can enhance the effectiveness and relevance of their investment strategies.
Purpose — The main objective of this study is to analyze the influence of socioeconomic development and fiscal decentralization on environmental quality in Indonesia, as well as to identify causal relationships between them.Method — The data utilized in this study are secondary data collected over the period from 2010 to 2020. Data sources were obtained from the Ministry of Environment and Forestry, the Central Bureau of Statistics, the Ministry of Finance, and the World Bank. This study uses a quantitative approach in dynamic panel data analysis with a generalized method of moments (GMM) estimation analysis. The causal relationship between environmental quality and the research variables is analyzed using the Granger causality test.Result — The study's findings indicate the presence of the reverse of an Environmental Kuznet Curve (EKC) relationship between Gross Regional Domestic Product (GRDP) per capita and environmental quality. Environmental quality is influenced positively and significantly by various factors, including human development, expenditure on environmental functions, poverty, and the manufacturing industry. On the other hand, fiscal transfers and urbanization have a negative and significant effect on environmental quality.Contribution — A more comprehensive analysis of the impact of development achievements in Indonesia on environmental quality indicators is needed at the provincial government level, considering economic development, social development, and governance aspects. This study also classifies research results based on three regional classifications and includes GMM estimation analysis, which has not been widely done.
Green bonds have gained significant attention in supporting sustainable development goals for achieving sustainability. During the issuance of green bonds, there are a few concerns such as standardization, greenwashing, and lack of benefits that can be gained with green bonds. However, blockchain technology is a promising solution for green bond issuance because it has already shown its impact on different finance activities. This study aims to address and analyze the role and significance of green bond issuance for meeting sustainability with blockchain technology and also suggested recommendations for future research. Decentralized application based on the Algorand blockchain and high-level architecture proposed for the issuance of green bonds is at the primary level. There is no discussion regarding standardizing the environmental data, and the number of benefits gained by the green bond is not addressed in the previously published literature. From the analysis, it has been identified that a similar framework of blockchain cannot be implemented as the geographical and environmental parameters are quite different for every nation. So, every nation needs to customize the framework according to the nation's requirements. This study is the first attempt to combine information from previously published research about green bond issuance and integration of blockchain for green bond issuance, enlightening the disruption caused in the issuance of green.
In view of the need for portfolio diversification, we investigate the interlinkages between a private equity ETF and a set of high-demand asset classes including bonds, equities, crude oil, gold, commodities, currency, Bitcoin, and shipping within a spillover framework. For this objective, we apply the enhanced modification of the Diebold and Yilmaz approach for the period 1 January 2010 to 31 January 2023. The empirical findings indicate a modest degree of connectedness among the investigated markets, whereas volatility spillovers showed acceleration during tumultuous periods. In addition, we assess the capacity of private equities for hedging, for the whole sample period and during COVID-19 infectious disease, in order to suggest investors for potential portfolio restructures. Results demonstrate that the short position in the volatility of private equity ETF can result in strong hedging effectiveness for investors holding long positions in Bitcoin, shipping, bonds, and crude oil. JEL Classification: C32, C58, G11, G15
Yunfei Yang, Jiamei Xiong, Lei Zhao, Xiaomei Wang · 6 authors
Cryptocurrency prices have the characteristic of high volatility, which has a specific resistance to cryptocurrency price prediction. Therefore, the appropriate cryptocurrency price predictive method can help reduce the investment risk of investors. In this study, we proposed a novel prediction method using a fractional grey model (FGM (1,1)) to predict the price of blockchain cryptocurrency. Specifically, this study established the FGM (1,1) through the closing price of three representative blockchain cryptocurrencies (Bitcoin (BTC), Ethereum (ETH), and Litecoin (LTC)). It adopted the PSO algorithm to optimize and obtain the optimal order of the model, thereby conducting prediction research on the price of blockchain cryptocurrency. To verify the predictive precision of the FGM (1,1), we mainly took MAPE, MAE, and RMSE as the judging criteria and compared the model’s predictive precision with the GM (1,1) through experiments. The research results indicate that within the data range studied, the predictive accuracy of the FGM (1,1) in the closing price of BTC, ETH, and LTC has reached a “highly accurate” level. Moreover, in contrast to the GM (1,1), the FGM (1,1) outperforms predictive capability in the experiments. This study provides a feasible new method for the price prediction of blockchain cryptocurrency. It has specific references and enlightenment for government departments, investors, and researchers in theory and practice.
Through a bibliometric analysis, this article researches the central topics that link blockchain to public policy design and investigates the key policy priorities for the use of blockchain technology in the public sector. The analysis points out six thematic foci in the current literature: (1) business and strategic management, (2) technology adoption, (3) system infrastructure, (4) cryptocurrency and decentralized economy, (5) regulations and geopolitics, and (6) governance. The analysis demonstrates a high degree of co-occurrence between “barriers” and “blockchain adoption” confirming that blockchain adoption in the public sector domain is perceived as challenging. The association of the term “barrier” with other key terms suggests theoretical, technological, resource-based, and managerial challenges as the main showstoppers. The bibliometric analysis also reveals the underrepresentation of social and political sciences in our knowledge base, despite the thematic relevance of these disciplines to understand the underlying challenges. More research from these disciplines is warranted to understand better how this technology can be best integrated into the public policy processes.
Ngô Thái Hưng, Toan Luu Duc Huynh, Muhammad Ali Nasir
Abstract This study investigates the impacts of economic policy uncertainty on the Bitcoin market using the monthly data from January 2014 to December 2022. In so doing, six major uncertainty indices (Global Economic Policy Uncertainty, Equity Market Volatility, Twitter‐based Economic Uncertainty, Geopolitical risk index, The Cryptocurrency Policy Uncertainty Index, The Cryptocurrency Price Uncertainty Index), and in particular, two novel Cryptocurrency Uncertainty indexes as introduced by Lucey et al. (2022) are taken into account. Our findings uncover a negative connectedness between Bitcoin prices and the key selected uncertainty indices, suggesting that higher uncertainties result in lower Bitcoin fluctuation across time and frequency domains. Our results provide valuable information on constructing asset portfolios for investors who have investment strategies entailing Bitcoin since Bitcoin would be a diversifier under economic policy uncertainty shocks. Our results hold robust by using the alternative methodology.
This paper studies asymmetric spillovers from Bitcoin to green and traditional assets by using a full distributional framework established by a recently-developed Quantile-on-Quantile approach. The spillovers from gold to the same are further studied to compare the effectiveness of the underlying digital investment shelter of Bitcoin with its traditional counterpart of gold. Statistical evidence indicates that the cross-market spillover features evident asymmetry and non-linearity from three perspectives involving various quantiles of the joint distribution of dependent and independent variables, data in return and volatility, and before/after the COVID-19 pandemic. The investment sheltering role of Bitcoin is examined by its weakly positive, negligible, or even negative dependence with financial assets under different market conditions, while such the role is found to be relatively stronger for green assets compared to that for traditional assets. Moreover, the digital investment shelter is shown to be more effective than the traditional shelter given Bitcoin’s weaker or even more negative dependence with both green and traditional financial assets than gold. Additional analyses confirm the robustness of our findings that should be of interest to various stakeholders.
Rui Dias, Paulo Alexandre, Nuno Teixeira, Mariana Chambino
Green investors have expressed concerns about the environment and sustainability due to the high energy consumption involved in cryptocurrency mining and transactions. This article investigates the safe haven characteristics of clean energy stock indexes in relation to three cryptocurrencies, taking into account their respective levels of “dirty” energy consumption from 16 May 2018 to 15 May 2023. The purpose is to determine whether the eventual increase in correlation resulting from the events of 2020 and 2022 leads to volatility spillovers between clean energy indexes and cryptocurrencies categorized as “dirty” due to their energy-intensive mining and transaction procedures. The level of integration between clean energy stock indexes and cryptocurrencies will be inferred by using Gregory and Hansen’s methodology. Furthermore, to assess the presence of a volatility spillover effect between clean energy stock indexes and “dirty-classified” cryptocurrencies, the t-test of the heteroscedasticity of two samples from Forbes and Rigobon will be employed. The empirical findings show that clean energy stock indexes may offer a viable safe haven for dirty energy cryptocurrencies. However, the precise associations differ depending on the cryptocurrency under examination. The implications of this study’s results are significant for investment strategies, and this knowledge can inform decision-making procedures and facilitate the adoption of sustainable investment practices. Investors and policy makers can gain a deeper understanding of the interplay between investments in renewable energy and the cryptocurrency market.
Afees A. Salisu, Ahamuefula E. Ogbonna, Tirimisiyu F. Oloko
This study examines the effect of pandemic-induced uncertainty on cryptocoins (Bitcoin, Ethereum and Ripple). It employs the Westerlund and Narayan (2012, 2015) predictive model to examine the predictability of pandemic-induced uncertainty and our model's forecast performance. We examine the role of asymmetry in uncertainty and the sensitivity of our results to the recently-developed Salisu and Akanni (2020) Global Fear Index. Cryptocoins act as a hedge against uncertainty due to pandemics, albeit with reduced hedging effectiveness in the COVID-19 period. Accounting for asymmetry improves predictability and model forecast performance. Our results may be sensitive to the choice of measure of pandemic-induced uncertainty.
This study investigates the hedge and safe-haven possibilities with bitcoin, gold and crude oil in different equity markets in the presence of time-varying market inefficiency. Our results indicate that periods of market inefficiency for the Bitcoin, gold and crude oil price positively influence their function as a hedge asset for the equity markets of Japan, China, the US, Europe and emerging countries. In addition to contributing to the discussion on the factors which affect the functioning of safe-haven assets, the empirical findings of this study further highlight the importance of market efficiency as a market microstructure feature. These results have important implications for investors seeking to manage risk through diversification across different asset classes.
Surmounted environmental concerns and energy challenges have created an augmented awareness among the public and policymakers about alternate energy resources. Using a network approach, this paper aims to investigate the dependence between cryptocurrencies and the alternative energy market using data from January 1, 2018, to December 23, 2021. For this investigation, first, we build a static dependency network for a given set of variables using partial correlations. Then, we demonstrate within-system connections in a minimum spanning tree (MST) to assess the centrality of all variables. Finally, rolling-window estimations are made to exhibit time variations in both dependency and centrality networks. We find that clean alternative markets (SPGCE, ELEVHC & WILCE) and ETH are net risk transmitters to other markets and system-wide net contributors. We also demonstrate how SPGCE is essential for tying together the various parts of the networks and provide convincing evidence of time-varying within-system dependency. Our thorough examination of the dependency analysis offers significant insights to macroprudential regulators, policymakers, and portfolio managers, enabling them to safeguard the most vulnerable markets and choose the best legislative and policy measures to protect investors' interests in the face of unforeseen financial and economic conditions.
Crude oil, Bitcoin, and carbon dioxide emissions are major issues that are significantly impacting the global economy and environment. These three issues are complexly interlinked, with profound economic and environmental implications. In this study, we explore the correlation among these three issues and attempt to understand the influence of crude oil and Bitcoin on carbon dioxide emissions. We created a novel approach, named quantile mediation analysis, which blends mediation regression with quantile regression, enabling us to explore the influence of Brent crude oil on carbon dioxide emissions by considering the mediating impact of Bitcoin. According to the findings from using our new approach, the impact of Brent crude oil on carbon dioxide emissions is partly mediated by Bitcoin, and the association between Brent crude oil and carbon dioxide emissions involves both direct and indirect effects. Since the carbon dioxide generated by the extraction of crude oil and Bitcoin has a great impact on the environment, accelerating the use of clean energy technologies to reduce our reliance on crude oil should be the direction that the cryptocurrency industry ought to pursue in the future.
Investigating the essential impact of the cryptocurrency market on carbon emissions is significant for the U.S. to realize carbon neutrality. This exploration employs low-frequency vector auto-regression (LF-VAR) and mixed-frequency VAR (MF-VAR) models to capture the complicated interrelationship between cryptocurrency policy uncertainty (CPU) and carbon emission (CE) and to answer the question of whether cryptocurrency policy uncertainty could facilitate U.S. carbon neutrality. By comparison, the MF-VAR model possesses a higher explanatory power than the LF-VAR model; the former’s impulse response indicates a negative CPU effect on CE, suggesting that cryptocurrency policy uncertainty is a promoter for the U.S. to realize the goal of carbon neutrality. In turn, CE positively impacts CPU, revealing that mass carbon emissions would raise public and national concerns about the environmental damages caused by cryptocurrency transactions and mining. Furthermore, CPU also has a mediation effect on CE; that is, CPU could affect CE through the oil price (OP). In the context of a more uncertain cryptocurrency market, valuable insights for the U.S. could be offered to realize carbon neutrality by reducing the traditional energy consumption and carbon emissions of cryptocurrency trading and mining.
Despite the growing interest in Blockchain Innovation (BI), there is a lack of research on its predictors. This study draws on the policy uncertainty literature to hypothesize the positive influence of economic policy uncertainty (EPU) and cryptocurrency policy uncertainty (UCRY Policy) on country-level BI, determined by the total number of blockchain patents in a country. We tested our hypotheses using a two-level sample of 126 quarterly observations nested in five countries: Australia, China, Japan, Korea, and the United States. The results confirm our expectation that the EPU and UCRY Policy lead to an enhanced BI. Moreover, we found that the UCRY Policy is more impactful on BI than EPU, and that when examining the two policy uncertainty indicators simultaneously, the effect of EPU on BI becomes insignificant. This study has important implications for policymakers and investors.
Purpose This study aims to identify the ability of gold and cryptocurrency (Cryptocurrency Uncertainty Index (UCRY) Price) as safe haven assets (SHA) for stocks and bonds in both conventional (i.e. stock indices and government bonds) and Islamic markets (i.e. Islamic stock indices and Islamic bonds (IB)). Design/methodology/approach The authors employed the nonadditive panel quantile regression model by Powell (2016). It measured the safe haven characteristics of gold and UCRY Price for stock indices, government bonds, Islamic stocks, and IB under gold circumstances and level of cryptocurrency uncertainty, respectively. The period spanned from 11 March 2020 to 31 December 2021. Findings This study discovered three findings, including: (1) gold is a strong safe haven for stocks and bonds in conventional and Islamic markets under bearish conditions; (2) UCRY Price is a strong safe haven for conventional stocks and bonds but only a weak safe haven for Islamic stocks under high crypto uncertainty; and (3) gold offers a safe haven in both emerging and developed countries, while UCRY Price provides a better safe haven in developed than in emerging countries. Practical implications Gold always wins big for safe haven properties during unstable economy. It can also win over investors who consider shariah compliant products. Therefore, it should be included in an investor's portfolio. Meanwhile, cryptocurrencies are more common for developed countries. Thus, the governments and regulators of emerging countries need to provide more guidance around cryptocurrency so that the societies have better literacy. On top of that, the investors can consider crypto to mitigate risks but with limited safe haven functions. Originality/value The originality aspects of this study include: (1) four chosen assets from conventional and Islamic markets altogether (i.e. stock indices, government bonds, Islamic stock indices and IB); (2) indicator countries selected based on the most used and owned cryptocurrencies for the SHA study; and (3) the utilization of UCRY Price as a crypto indicator and a further examination of the SHA study toward four financial assets.
This paper assesses the effectiveness of a broad set of 1066 active and continuously traded cryptocurrencies as a safe haven instrument against extreme oil price movements, in comparison to the corresponding roles of gold. The uncertainty for the oil market during the COVID-19 pandemic and the subsequent Russia–Ukraine conflict set the tone for natural experiments for our study. We use a trail-blazing dynamic generalized autoregressive score model to estimate the tail riskiness of the potential safe haven assets from January 1, 2020, to September 30, 2022. By estimating the risk exposure of all cryptocurrency assets, we determine top ten safest assets for investment. Our results show the emergence of new safe haven cryptocurrencies, which have previously been ignored by the academic literature and policy makers alike. Intriguingly, our findings reveal that gold has been replaced by altcoins as the safest assets during both the COVID-19 pandemic and the Russia–Ukraine conflict. At this instance, our findings suggest that Bitcoin provides lengthier safe haven properties than gold for oil returns in both periods. However, the safe haven properties of gold and cryptocurrencies are time varying. Last but not least, we introduce a new Cryptocurrency Tail Risk Index (CTRI) that captures the risk exposure of cryptocurrency market, as a whole. Our results suggest that investment in numerous cryptocurrencies provides lengthier safe haven properties than investing in gold alone.