【Author】 Okoroafor, Ugochi C. Leirvik, Thomas
【影响因子】9.848
【主题类别】
区块链治理-市场治理-市场分析
【Abstract】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.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Safe-haven; Market efficiency; Bitcoin; Gold; Crude oil
【发表时间】2023
【收录时间】2023-08-03
【文献类型】 实证数据
【Author】 Valadares, Julia Almeida Villela, Saulo Moraes Bernardino, Heder Soares Goncalves, Glauber Dias Vieira, Alex Borges
CCF-C
【影响因子】8.665
【主题类别】
区块链治理-技术治理-实体分类
【Abstract】Ethereum is one of the largest blockchain platforms currently that has become a digital business environment. This platform allows for decentralized transactions between anonymous users. Thus, the development of methods to identify users' behaviors and keep them anonymous can potentially leverage business on this platform. In this work, we aim to combine different categories of machine learning approaches, namely, unsupervised and semi-supervised, to map the behaviors of users' owned accounts and identify users with professional activities in Ethereum. In addition, we provide here data to the community and analyze different machine learning techniques to characterize the users of Ethereum. These are challenging tasks due to the small fraction of publicly labeled data referring to users' accounts that provide services on this platform, such as exchange, payment, and entertainment, among most casual behavior users. Initially, we use unsupervised learning techniques to cluster the unlabeled users' accounts and to identify a set of them with casual behavior. As an outcome, a dataset containing labeled (casual or professional) and unlabeled instances is obtained. Semi-supervised learning methods are then applied (i) to generate models that classify accounts' behaviors into casual or professional ones and (ii) to discover accounts with professional behaviors among the unlabeled ones. Computational experiments were conducted, and the results obtained by the proposed procedure are compared to those achieved by supervised learning techniques from the literature. The proposal outperformed those from the literature and reached values higher than 95% for the accuracy, precision, recall, F beta-scores, MCC, and AUC-ROC.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Cryptocurrency; Blockchain; Ethereum; Transactions; Machine learning; Semi -supervised learning
【发表时间】2023
【收录时间】2023-08-03
【文献类型】 实证数据
【Author】 Chen, Ping-Kuo Huang, Xiang
【影响因子】8.562
【主题类别】
区块链应用-虚拟经济-元宇宙
【Abstract】This study explores how the virtual environment of metaverse generates benefits to drive firms' rational choice in mutual trust building, and further ensures the green knowledge sharing intention maintaining for continuous enhancing supply chain resilience and realizing green performance, further promoting environmentally sustainable development. A conceptual framework is formulated by incorporating the natural resource-based view, knowledge-based view, and rational choice theory. This framework is supported and validated using PLS-SEM. The findings of the analysis reveal that the virtual environment of the metaverse can create a sense of physical proximity, effectively managing communication distance and influencing firms' emotional attitude during interactions. Furthermore, the metaverse facilitates sensory feedback, thereby strengthening emotional expression. Based on these observations, supply chain firms are likely to adopt rational thinking and demonstrate rational behavior, making choices that foster mutual trust. As trust is established, it promotes the sharing of green knowledge, strengthens supply chain resilience, facilitates the achievement of environmentally friendly performance in the green supply chain, and contributes to the sustainable development of the environment. This study makes valuable contributions to the existing literature concerning the integration of green supply chain and the metaverse.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】green knowledge sharing; metaverse; supply chain resilience; sustainable development; virtual environment
【发表时间】2023
【收录时间】2023-08-03
【文献类型】 实证数据
【DOI】 10.1002/sd.2663
【影响因子】6.353
【主题类别】
区块链应用-虚拟经济-元宇宙
【Abstract】Technological advances are enabling more immersive experiences in virtual worlds and digitally augmented experiences in the physical world. These experiences are increasingly associated with the metaverse, a term rooted in science fiction originally referring to a dystopian digital reality.2 The recent pandemic highlighted how tech-nology can transform work and help us overcome great obstacles, prompting orga-nizations to consider how virtual and augmented reality can enable next-generation workplace and customer experiences. Our research explores the potential promise and peril of emergent metaverses to business and society. We also take a position on how they should be governed.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】
【发表时间】2023
【收录时间】2023-08-03
【文献类型】 观点阐述
【DOI】 10.17705/2msqe.00079
【Author】 Garett, Renee Emish, Mohamed Young, Sean D.
【影响因子】5.211
【主题类别】
区块链治理-市场治理-技术采用
【Abstract】Public health research relies heavily on participant involvement. Investigators have examined factors that affect participation and found that altruism enables engagement. At the same time, time commitment, family concerns, multiple follow-up visits, and potential adverse events are barriers to engagement. Thus, investigators may need to find new methods to attract and motivate participants to participate, including new compensation methods. As cryptocurrency is being increasingly used and accepted to pay and reimburse people for work activities, this currency should be similarly explored as an option for research participants to attempt to incentivize them to participate in studies and offer new possibilities for study reimbursement. This paper explores the potential use of cryptocurrency as a form of compensation in public health research studies and discusses the pros and cons of its use. Although few studies have used cryptocurrency to compensate participants, cryptocurrency may be used as a reward for various research tasks, including filling out surveys, participating in-depth interviews or focus groups, and/or completing interventions. Using cryptocurrencies to compensate participants in health-related studies can provide benefits such as anonymity, security, and convenience. However, it also poses potential challenges, including volatility, legal and regulatory challenges, and the risk of hacking and fraud. Researchers must care-fully weigh the benefits against the potential downsides before using them as a compensation method in health-related studies. Lay Summary: People who participate in research are provided with compensation to reimburse them for being involved. This compensation is usually in the form of cash, check, or electronic gift cards. Given the increasing use of and interest in cryptocurrencies, such as Bitcoin and Ethereum, cryptocurrencies should be explored as a possibility for paying participants to participate in studies. This manuscript describes that compensation option, with considerations for researchers and the public.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Cryptocurrency; Participant compensation; Public health; Research; Surveys and questionnaire
【发表时间】2023
【收录时间】2023-08-03
【文献类型】 实证数据
【Author】 Li, Jiahui Liang, Haoshen Ni, Likun
【影响因子】5.190
【主题类别】
区块链治理-市场治理-市场分析
【Abstract】Numerous economic and financial crises, particularly the present crisis in the healthcare sector, have pushed major shock spillover channels over stock marketplaces. This research studied how the shock spillover system is affected by three significant factors: Bitcoins, unpredictability, and the China stock market between 2014 and 2021. While much earlier empirical research has looked at risk dispersion in different financial markets, this article will zero in on green markets. This investigation seeks to accomplish something that has never been done before: determine whether or not green commodities, Bitcoin, and uncertainty impact the performance of the China stock market. The following are significant results based on a quantile vector autoregressive (VAR) connection. (i) A static spillover system indicates that information was widely shared across markets during intense market circumstances. (ii) The global green economy and clean energy marketplaces are the primary sources of knowledge spillover in adverse market conditions. This research elucidates the asymmetrical influence of green products, Bitcoin, and market volatility in China. This is vital due to the dynamic nature of international and regional connections. Recent studies have shown that shock spillovers are excellent for cryptocurrencies such as Bitcoin (BTC), uncertainty indices, and global carbon indexes, but bad for most eco-friendly products.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Quantile VAR network; Spillover effects; China; Stock markets; Green commodities; Bitcoin
【发表时间】2023
【收录时间】2023-08-03
【文献类型】 实证数据
【影响因子】4.820
【主题类别】
区块链治理-市场治理-市场分析
【Abstract】This article is the first one to examine the moderating role of bitcoin sentiment indices on the short term and long-term time-frequency-based good and bad network connectedness of all US sectors. In more detail, the paper quantifies the above relationship between the 11 US sectoral high frequency returns and then identifies the moderating impact of bitcoin investors' fear and greed sentiment on good and bad network connectedness during pre-Covid-19 and Covid-19. For the said purpose, we decompose the returns into good and bad volatility, and rely on time and frequency dependent spillover measures and quantify a spillover symmetrical and asymmetrical measure for network connectedness for different investment horizons. Furthermore, we also quantify the NET good-bad volatility transmission and reception capability of all our sectors within the frequency dependent network. The extracted good and bad network connectedness indices are then regressed on multiple thresholds of bitcoin sentiment indices. Quantile regression results revealed that fear, extreme fear, greed and extreme greed moderate the short term and long term good and bad volatility spillovers within the network connectedness. Finally, we also utilize hedge ratios and optimal portfolio weight selection strategies to explain whether short positioning in the US sectoral returns can be used to hedge against bitcoin sentiment risk.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Financial markets; Network modelling; Asymmetrical network connectedness; Time-frequency dependent US sectoral network; Bitcoin sentiment indexes; Portfolio diversification; Realized and semi-realized variances; Covid-19; Hedge ratios; Optimal portfolio weight selection strategy; High frequency data
【发表时间】2023
【收录时间】2023-08-03
【文献类型】 实证数据
【Author】 De Araujo, Fernando H. A. Fernandes, Leonardo H. S. Silva, Jose W. L. Sobrinho, Kleber E. S. Tabak, Benjamin Miranda
【影响因子】4.555
【主题类别】
区块链治理-市场治理-市场分析
【Abstract】This paper has investigated the predictability of the top 10 cryptocurrencies' price dynamics, ranked by their daily market capitalization and trade volume, via the information theory quantifiers. Our analysis considers the Complexity-entropy causality plane to study the temporal evolution of the price of these cryptocurrencies and their respective locations along this 2D map, bearing in mind after and during the Russia-Ukraine war. Moreover, we apply the permutation entropy and the Jensen-Shannon statistical complexity measure to rank these cryptocurrencies similarly to a complexity hierarchy. Our findings reflect that the Russian-Ukraine war affects the informational efficiency of cryptocurrency dynamics. Specifically, the cryptocurrencies notably showed a decrease in informational inefficiency (USD-coin, Binance-USD, BNB, Dogecoin, and XRP). At the same time, the cryptocurrencies with more expressiveness for the financial market, considering the volume traded and the capitalized market, were strongly impacted, presenting an increase in informational inefficiency (Tether, Cardano, Ethereum, and Bitcoin). It clarifies the potential of cryptocurrencies to mitigate exogenous shocks and their capability to use with portfolio selection, risk diversification and herding behavior.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Russia-Ukraine War; Cryptocurrency; Information Theory Quantifiers; Complexity; Inefficiency
【发表时间】2023
【收录时间】2023-08-03
【文献类型】 实证数据
【影响因子】3.476
【主题类别】
区块链技术-核心技术-扩展方案
【Abstract】Blockchain emerged in the last decade as a promising technology with possible applications in numerous fields such as healthcare, supply chain, and finance. Its immutability, transparency, security, and decentralisation gained significant attention in academia and industry. One technology that blockchain can support is the Internet of Things (IoT). However, there are still challenges hindering the real-world adoption of blockchain due to concerns about its performance, scalability, and complexity. This study contributes to a comparative study that analyses blockchain platforms in terms of their performance and scalability, with specific reference to IoT applications. We focus on the Ethereum and Hyperledger Fabric blockchain platforms. As part of the implementation, an IoT healthcare use case is developed. We conducted performance and scalability tests on private platform networks to measure the throughput and latency parameters. To evaluate scalability, we examined the behaviour of the studied platforms in response to an increase in the number and rate of transactions. Hyperledger Caliper is used to collect these parameters. Experiment analysis shows that Fabric outperforms Ethereum in terms of latency and throughput. As for performance and scalability analysis, Fabric was found to be more suitable than Ethereum for private networks such as IoT healthcare ecosystems.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; Ethereum; hyperledger fabric; Internet of Things; performance; scalability
【发表时间】2023
【收录时间】2023-08-03
【文献类型】 实验仿真
【影响因子】3.229
【主题类别】
区块链治理-市场治理-市场分析
【Abstract】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
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Alternative investments; Bitcoin; crude oil; gold; private equities; volatility spillovers
【发表时间】2023
【收录时间】2023-08-03
【文献类型】 实证数据
【影响因子】2.592
【主题类别】
区块链治理-市场治理-市场分析
【Abstract】In the turbulent landscape of financial markets, Bitcoin has emerged as a significant focus for investors due to its highly volatile returns. However, the risks and uncertainties associated with it necessitate effective hedging strategies. This paper explores the potential of various financial assets, including interest rates, stock markets, commodities, and exchange rates, as dynamic hedges against Bitcoin's risk. Utilizing a DCC-GARCH model, we construct a dynamic hedging model to analyze the viability of these financial assets as hedges. The data is categorized into pre-pandemic and pandemic periods to assess any change in hedging performance due to the outbreak of COVID-19. Our empirical findings suggest that the dynamic DCC-GARCH model outperforms the static OLS model in this context. During the pandemic period, a diverse set of financial assets demonstrated enhanced efficiency in hedging Bitcoin risk compared to the pre-pandemic phase. Among the hedging commodities, stock market indices, the US dollar index, and commodity futures displayed superior performance.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】cryptocurrency risk; financial volatility; dynamic hedging; COVID-19 impact; DCC-GARCH model
【发表时间】2023
【收录时间】2023-08-03
【文献类型】 实证数据
【DOI】 10.3390/math11132917
【影响因子】1.411
【主题类别】
区块链治理-市场治理-价格预测
【Abstract】. Bitcoin has high price fluctuations, which involve high risks and high return rates for investors. These high earnings have attracted the attention of investors. This paper proposes a new model for Bitcoin price prediction that effectively reduces prediction error. Hyperparameter optimization methods such as Bayesian optimization (BO), random search and grid search with Long Short-Term Memory (LSTM), Gated Repetitive Unit (GRU), and hybrid LSTM-GRU utilised. Models with BO achieved better results than others. To improve each model's results with BO; Gradient Incremental Regression Trees (GBRT), Gaussian Process (GP), Random Forest (RF) and Extra Trees (ET) were applied to optimizers and corresponding surrogate functions. Evaluating the effects of hyper-parameter values on the problem for each method contributes to the parameter selection process for similar prediction problems. To increase comparability in the literature, Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE) and Mean Square Error (MSE) were used. There is a least one hyper-parameter combination, which produces a result close to the best value for each model when the results obtained from the experiments are interpreted. BO with hybrid LSTM-GRU outperformed all methods in this paper and the examined literature for the value of RMSE, MSE, and MAE.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】LSTM; GRU; grid search; random search; Bayesian optimization; Bitcoin; hybrid
【发表时间】2023
【收录时间】2023-08-03
【文献类型】 实证数据
【DOI】 10.3934/jimo.2023091
【影响因子】0.670
【主题类别】
区块链应用-实体经济-通信领域
【Abstract】Security is the basis for the normal operation of advanced measurement infrastructure (AMI). As an important part of key management scheme, key establishment is indispensable in meeting AMI communication security requirements. Most proposed key management schemes rely on a trusted third party (TTP). Once there is a problem with TTP, the security of these schemes will be greatly reduced. Furthermore, the data concentrators (DCs) in traditional AMI architectures all manage smart meters (SMs) in their respective regions, and the lack of interaction between the DCs exposes a serious single point of failure. To alleviate these problems, we propose a blockchain-based authenticated key agreement scheme to secure the communication of AMI. In this scheme, the blockchain comprises DCs as network nodes that interact with the SMs. The proposed key agreement and distributed consensus protocol ensure the authenticity and validity of the communication content without relying on TTP. We analyse the resistance of the proposed protocol to multiple known attacks and evaluate its performance. The proposed protocol has higher security or better performance than other schemes.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Authenticated key agreement scheme; Consensus algorithm; Blockchain; Advanced measurement infrastructure security
【发表时间】2023
【收录时间】2023-08-03
【文献类型】 实验仿真