【Author】 Wilson, Kathleen Bridget Karg, Adam Ghaderi, Hadi

【Source】BUSINESS HORIZONS

【影响因子】10.562

【主题类别】

区块链应用-虚拟经济-NFT

【Abstract】Non-fungible tokens (NFTs) are a highly nascent and emerging phenom-enon revolutionizing how digital assets are traded. NFTs embody immutable rights to unique digital assets such as digital art and collectibles and are represented as digital tokens that can be traded across marketplaces utilizing blockchain technol-ogies. NFTs engender new ways to organize, consume, move, program, and store digital information and have experienced a rapid rise in various adaptations across art, sports, broadcasting, content creation, and tech-crypto businesses. In this article, we define NFTs and look at how they fit with blockchain and cryptocurren-cies, how they are used by various industries, and the opportunities and risks they present. Our key contribution is a conceptual map of an initial NFT ecosystem. In doing so, we provide relational mapping between and among key stakeholders: con-tent creators, core and related technical and business intermediaries, consumers, investors, and speculators. We also highlight implications for managers and tie them to conceptual exploration and exploitation frameworks.(c) 2021 Kelley School of Business, Indiana University. Published by Elsevier Inc. All rights reserved.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】NFT; Non-fungible tokens; Blockchain; Business ecosystem; Digital innovation

【发表时间】2022

【收录时间】2022-09-09

【文献类型】 观点阐述

【DOI】 10.1016/j.bushor.2021.10.007

【Author】 Nakagawa, Kei Sakemoto, Ryuta

【Source】FINANCE RESEARCH LETTERS

【影响因子】9.848

【主题类别】

区块链技术-平台项目-Ethereum

【Abstract】This study investigates whether market states impact the Bitcoin-Ether correlation. We observe an increase in the average correlation due to a rise in popularity of Ether. We also find that an increase in uncertainty leads to the low Bitcoin-Ether correlation, suggesting that investors revise the relative valuation during high market uncertainty periods. The relationship between the Bitcoin-Ether correlation and uncertainty is nonlinear, and our search volume results show that investors' attention to both cryptocurrencies increases during the uncertainty periods.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】VIX; ADCC GARCH; Cryptocurrencies; Gold; Quantile regression

【发表时间】2022

【收录时间】2022-09-09

【文献类型】 实证数据

【DOI】 10.1016/j.frl.2022.103216

【Author】 Haffar, Adlane Le Fur, Eric

【Source】QUARTERLY REVIEW OF ECONOMICS AND FINANCE

【影响因子】4.324

【主题类别】

区块链技术-平台项目-数字货币

【Abstract】This paper analyzes Bitcoin investment in terms of portfolio diversification. Over the period July 2011-April 2021, we use the copula-GARCH approach to test the time-varying dependence of Bitcoin in a portfolio composed of six stock markets (CAC40, DJIA, EUROSTOXX50, FTSE100, HANGSENG, and NIKKEI225). Our results reveal that volatility modeling provides better results with the Dynamic Conditional Correlation model. The performance of the portfolio is largely due to the high returns of Bitcoin which allows for better portfolio diversification. As a result, there is a mitigation of the extreme rates of return associated with crypto-currencies. Finally, while Bitcoin's contribution to the portfolio is more attributable to its risk than its return, it does play a role in stabilizing portfolio performance, for varying levels of risk.(c) 2022 Published by Elsevier Inc. on behalf of Board of Trustees of the University of Illinois.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Bitcoin; Copula-GARCH model; Portfolio diversification; Portfolio risk; Robust MCD portfolio

【发表时间】2022

【收录时间】2022-09-09

【文献类型】 实证数据

【DOI】 10.1016/j.qref.2022.07.008

【Author】 Khan, Abdullah Ayub Laghari, Asif Ali Gadekallu, Thippa Reddy Shaikh, Zaffar Ahmed Javed, Abdul Rehman Rashid, Mamoon V. Estrela, Vania Mikhaylov, Alexey

【Source】COMPUTERS & ELECTRICAL ENGINEERING

【影响因子】4.152

【主题类别】

区块链应用-实体经济-无人机领域

【Abstract】The advent of fog computing as an extension of cloud-enabling technology has moved from the hub of the internet framework to the unmanned aerial vehicle (UAV)-enabled control and man-agement of drone-based data. The key objectives are to improve the computation and processing of drone-based resource constraints and deliver the data to the outsourced computational node to schedule, process, manage, optimize, and preserve it since they are located close to each other through a wireless sensor network. This collaborative technological approach to robustness is the standard of drone system design and implementation, reducing the computational power, resource consumption, and latency for the application that needs a fast response. However, recent research into fog-enabled drone-based data management and optimization poses a serious chal-lenge in terms of privacy, security, and preservation. On the other hand, Blockchain Hyperledger Technology, which is mostly used in Bitcoin Cryptocurrencies, has been applied in a large number of distributed applications due to the ledger integrity, transparency, trustworthiness, provenance, reliability, availability, protection, and security-related distributed features that are provided. Therefore, the distributed application of drone control has received more attention because of its ability to handle collaborative procedures to capture, schedule, process, optimize, manage, and preserve drone-based data using fog nodes and blockchain hyperledger technology. In this paper, we proposed a collaborative approach using blockchain hyperledger fabric and a metaheuristic-enabled genetic algorithm for fog node management called B-Drone. This approach handles drone-based data collection, scheduling, optimizing, processing, managing, and preservation in a secure manner in the fog node. The protection of each transaction between drone and fog node before exchange is private with the utilization of the hash-encryption (SHA-256) algorithm. The blockchain smart contracts are implemented and deployed to auto-manage all the connectivity and communication protocols between drones and fog nodes in the designed private permissioned network. The simulations of the proposed collaborative approach reduce the computing cost down to 12.03% and increase the performance up to 73.11%, thus decreasing the cost of drone -ledger preservation down to 30.13% and the robust usage of the network up to 54.29% as compared to other state-of-the-art methods .

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain; Smart contract; Metaheuristic; Genetic algorithm; Fog node; Drone data management and optimization

【发表时间】2022

【收录时间】2022-09-09

【文献类型】 实验仿真

【DOI】 10.1016/j.compeleceng.2022.108234

【Author】 Chen, Yali Huang, Dan Liu, Zhen Osmani, Mohamed Demian, Peter

【Source】SUSTAINABILITY

【影响因子】3.889

【主题类别】

区块链应用-实体经济-工业领域

【Abstract】At present, the smart city offers the most desired state of urban development, encompassing, as it does, the concept of sustainable development. The creation of a smart city is closely associated with upgrading the construction industry to encompass many emerging concepts and technologies, such as Construction 4.0, with its roots in Industry 4.0, and the deployment of building information modeling (BIM) as an essential tool for the construction industry. Therefore, this paper aims to explore the current state of the art and development trajectory of the multidisciplinary integration of Construction 4.0, Industry 4.0, BIM, and sustainable construction in the context of the smart city. It is the first attempt in the literature to use both macro-quantitative analysis and micro-qualitative analysis methods to investigate this multidisciplinary research topic. By using the visual bibliometric tool, VOSviewer, and based on macro keyword co-occurrence, this paper is the first to reveal the five keyword-constructed schemes, research hotspots, and development trends of the smart city, Construction 4.0, Industry 4.0, BIM, and sustainable construction, from 2014 to 2021 (a period of eight years). Additionally, the top 11 productive subject areas have been identified with the help of VOSviewer software keyword-clustering analysis and application. Furthermore, the whole-building life cycle is considered as an aid to identifying research gaps and trends, providing suggestions for future research with the assistance of an upgraded version of BIM, namely, city information modeling (CIM) and the future integration of Industry 5.0 and Construction 5.0, or even of Industry Metaverse with Construction Metaverse.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】smart city; Construction 4; 0; Industry 4; 0; building information modeling (BIM); sustainable building; Construction Metaverse; life cycle stage; keyword co-occurrence; visualization; bibliometric; VOSviewer

【发表时间】2022

【收录时间】2022-09-09

【文献类型】 实证数据

【DOI】 10.3390/su141610028

【Author】 Kumar, Prabhat Kumar, Randhir Gupta, Govind P. Tripathi, Rakesh

【Source】IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING

【影响因子】3.525

【主题类别】

区块链应用-实体经济-交通领域

【Abstract】Green Connected and Autonomous Vehicles (CAVs) are the future of next-generation Intelligent Transportation Systems (ITS) that will help humans to improve road safety and reduce pollution, energy consumption, and travel delays. To increase the performance of green CAV, the data generated by Autonomous Vehicles (AVs) and associated infrastructure needs to be processed in real-time. Mobile Edge Computing (MEC) is a promising paradigm that can be integrated with green CAV to save energy and to improve the network performance in terms of low latency for data processing. However, MEC servers and other communication entities in green CAV environment cannot be fully trusted and may bring vulnerabilities related to data privacy and security. Motivated by the above challenges, we design a blockchain and Deep-Learning (DL)-enabled secure data processing framework for an edge-envisioned green CAV environment (hereafter referred to as BDEdge). In blockchain-based scheme, all communication entities are registered, verified and thereafter validated using smart contract-based Practical Byzantine Fault Tolerance (PBFT) consensus algorithm. The authenticated data is forwarded to DL scheme. In DL-based scheme, an Intrusion Detection System (IDS) based on a hybrid model of Sparse Auto-Encoder-enabled Attention Bidirectional Gated Recurrent Unit (SAE-ABIGRU) is designed by analyzing the link load behaviors of the MEC-enabled Road Side Unit (RSU) server. The security analysis and comparative simulation findings shows that the proposed BDEdge framework can significantly reduce false alarm rate and increase accuracy close to 99%.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Green products; Blockchains; Servers; Security; Image edge detection; Intrusion detection; Computational modeling; Blockchain; connected and autonomous vehicles (CAVs); deep-learning; green communication; edge computing (EC); intrusion detection system (IDS)

【发表时间】2022

【收录时间】2022-09-09

【文献类型】 实验仿真

【DOI】 10.1109/TGCN.2022.3165692

【Author】 Razmjouei, Pouyan Kavousi-Fard, Abdollah Dabbaghjamanesh, Morteza Jin, Tao Su, Wencong

【Source】IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING

【影响因子】3.525

【主题类别】

区块链应用-实体经济-交通领域

【Abstract】This study proposes a novel secure and lightweight charging scheduling framework approach to provide the customization of edge computing services and personalized edge computing services for Moving EVs (MEVs) and Parking EVs (PEVs) in 6G heterogeneous Vehicular Networks (HetVNETs). A DAG-based smart-contract well-protected edge computing structural design is specially designed in the scheme by taking the wireless charging models into account including the attributes of 6G smart devices, where each vehicle network infrastructure copes with some more EVs in parking station wireless zone (PEVs) to make computing services whole through a wireless task. Each communication network handles a group of Electric Vehicles (EVs) in the parking zone to fulfill Cloud Computing Services (CCS) in wireless charging tasks. With this architecture, the collaborative computing resource allocation (CCRA) algorithm is developed to assist each network computing and communication hardware and software systems in deciding a customized service strategy (CSS) to fulfill the fast wireless charging and secure easy access of MEVs based on the widely available computational complexity solution held by various network infrastructures.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】6G mobile communication; Inductive charging; Dynamic scheduling; Edge computing; Communication system security; Vehicle dynamics; Task analysis; Vehicle wireless charging; DAG cryptocurrency; 6G vehicular networks

【发表时间】2022

【收录时间】2022-09-09

【文献类型】 观点阐述

【DOI】 10.1109/TGCN.2022.3170303

【Author】 Yang, Dana Doh, Inshil Chae, Kijoon

【Source】IEEE ACCESS

【影响因子】3.476

【主题类别】

区块链技术-核心技术-共识机制

【Abstract】Due to the explosive increase in IoT devices and traffic, big data is developing into smart data that helps the data science experts understand human activities, through the relationship between mobility and resource application of the users in public spaces. For example, smart data markets help to predict crimes or understand the cause of COVID-19 infections. For these smart services, the users agree to the privacy policy so that the personal and sensitive information can be collected by a third party. But the conditions of the privacy policy do not specify whether the information of the users can be tracked. To ensure data transparency, many systems are applying consortium/private blockchains with raft algorithm. The raft algorithm requires nodes to check countless messages for a single transaction. Eventually, as the number of nodes increases, the overall system degradation is derived from the burden of the leader node. This paper proposes a method to process the collected transactions by dividing a certain amount of transactions into cells, without any extra protocol. The proposed scheme also uses the federated learning model with high accuracy and data privacy, in order to determine the optimized cell size in a blockchain system that should lead to consensus on multiple servers. Therefore, the proposed CBR (Cell-based Raft) consensus algorithm proposes a protocol that reduces the number of messages, without interfering with the concept of the existing raft algorithm, in order to maintain stable throughput in the smart data market where massive transactions occur.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchains; Servers; Consensus algorithm; Collaborative work; Internet of Things; Throughput; Smart devices; Data science; Smart service; blockchain; consensus algorithm; raft algorithm; federated learning

【发表时间】2022

【收录时间】2022-09-09

【文献类型】 观点阐述

【DOI】 10.1109/ACCESS.2022.3197758

【Author】 Pranto, Tahmid Hasan Hasib, Kazi Tamzid Akhter Md Rahman, Tahsinur Haque, Akm Bahalul Islam, A. K. M. Najmul Rahman, Rashedur M.

【Source】IEEE ACCESS

【影响因子】3.476

【主题类别】

区块链技术-协同技术-机器学习

【Abstract】Financial fraud cases are on the rise even with the current technological advancements. Due to the lack of inter-organization synergy and because of privacy concerns, authentic financial transaction data is rarely available. On the other hand, data-driven technologies like machine learning need authentic data to perform precisely in real-world systems. This study proposes a blockchain and smart contract-based approach to achieve robust Machine Learning (ML) algorithm for e-commerce fraud detection by facilitating inter-organizational collaboration. The proposed method uses blockchain to secure the privacy of the data. Smart contract deployed inside the network fully automates the system. An ML model is incrementally upgraded from collaborative data provided by the organizations connected to the blockchain. To incentivize the organizations, we have introduced an incentive mechanism that is adaptive to the difficulty level in updating a model. The organizations receive incentives based on the difficulty faced in updating the ML model. A mining criterion has been proposed to mine the block efficiently. And finally, the blockchain network is tested under different difficulty levels and under different volumes of data to test its efficiency. The model achieved 98.93% testing accuracy and 98.22% Fbeta score (recall-biased f measure) over eight incremental updates. Our experiment shows that both data volume and difficulty level of blockchain impacts the mining time. For difficulty level less than five, mining time and difficulty level has a positive correlation. For difficulty level two and three, less than a second is required to mine a block in our system. Difficulty level five poses much more difficulties to mine the blocks.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchains; Machine learning; Smart contracts; Adaptation models; Data models; Smart contracts; Computational modeling; Collaboration; Financial industry; Blockchain; collaborative machine learning; incremental learning; privacy; smart contract

【发表时间】2022

【收录时间】2022-09-09

【文献类型】 实证数据

【DOI】 10.1109/ACCESS.2022.3198956

【Author】 Zhang, Xiaohui Miao, Xianghua Xue, Mingying

【Source】SECURITY AND COMMUNICATION NETWORKS CCF-C

【影响因子】1.968

【主题类别】

区块链应用-实体经济-情报领域

【Abstract】The CTI (Cyber Threat Intelligence) sharing and exchange is an effective method to improve the responsiveness of the protection party. Blockchain technology enables sharing collaboration consortium to conduct a trusted CTI sharing and exchange without a centralized institution. However, the distributed connectivity of the blockchain-based CTI sharing model proposed before exposes the systems to byzantine attacks. The compromised members of partner organizations will further decrease the accuracy and trust level of CTI by generating false reporting. This paper proposes a new blockchain-based CTI model to address the unbalance issues of performance in speed, scalability, and security, which combines consortium blockchain and distributed reputation management systems to achieve automated analysis and response of tactical threat intelligence. In addition, the novel consensus algorithm of consortium blockchain that is fit for CTI sharing and exchange is introduced in this paper. The new consensus algorithm is called "Proof-of Reputation" (PoR) consensus, which meets the requirements of transaction rate and makes the consensus in a creditable network environment through constructing a reputation model. Finally, the effectiveness and security performance of the proposed model and consensus algorithm is verified by experiments.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】

【发表时间】2022

【收录时间】2022-09-09

【文献类型】 实验仿真

【DOI】 10.1155/2022/7760509

【Author】 Ruan, Yali

【Source】MOBILE INFORMATION SYSTEMS

【影响因子】1.863

【主题类别】

区块链应用-实体经济-教育领域

【Abstract】With the increasing trend of globalization, English, as the most widely used language in the world, has become a subject that many people must learn. English for special purposes is mainly applied to some specialized occupations or English in specific professional skill fields. Due to the increasing national demand for professional compound talents, the status of English for special purposes is also getting higher and higher. However, there are still many problems in the curriculum setting of English for special purposes, for example, outdated teaching mode, lack of oral language skills training, lack of students' ability to cope with actual situations, weak teaching awareness of teachers, and lack of analysis of students' needs for English for special purposes, resulting in poor students' enthusiasm for learning and so on. With the support of blockchain technology, combined with consensus algorithm, hash function algorithm, and smart contract, this paper analyzes English for special purposes, establishes an ESP management system and a corpus of spoken English for special purposes, and analyzes the integrity of the corpus data. The test found that when the number of error data blocks is 10, the total number of damaged data blocks and verification accuracy data blocks is about 4% in order to achieve 99% accuracy. Therefore, the integrity of the system is higher when the damage ratio is lower. The system integrity test finds that, with the number of wrong data being larger, when the wrong data block is at 100, 50% of the data blocks of the system integrity are about 1%. The database is complete, which is more helpful for students to study systematically.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】

【发表时间】2022

【收录时间】2022-09-09

【文献类型】 实证数据

【DOI】 10.1155/2022/9460419

【Author】 Ecer, Fatih Boyukaslan, Adem Hashemkhani Zolfani, Sarfaraz

【Source】AXIOMS

【影响因子】1.824

【主题类别】

区块链治理-市场治理-数字货币

【Abstract】Blockchain technologies, which form the basis of Industry 4.0, paved the way for cryptocurrencies to emerge as technological innovation in the technology age. Recently, investors worldwide have been interested in cryptocurrencies with increasing acceleration due to high earning expectations though they have no backing and intrinsic value. As such, this paper seeks to identify the most proper cryptocurrencies from an investment standpoint in our technological era. Fifteen well-known cryptocurrencies with the highest market capitalization are evaluated as per sixteen factors. An intuitionistic fuzzy set-driven methodology incorporating Evaluation Based on Distance from Average Solution (EDAS), Multi-Attributive Ideal Real Comparative Analysis (MAIRCA, and Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS), which is the study's prominent novelty, has been applied to provide a strong group decision vehicle for cryptocurrency selection. Notwithstanding, although the results obtained with the three approaches are highly consistent, investors would not like to doubt the instrument they will invest in. The Borda count is then applied to obtain a compromise for the rankings obtained from each approach. As per our findings, Ethereum, Tether, and Bitcoin are the most suitable cryptocurrencies, whereas reliable software, ease of inclusion in the wallet, and stability are the foremost factors to consider when investing in cryptocurrencies. The findings are further discussed in detail from a financial perspective. The proposed approach could be employed to select different investment instruments in future studies.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】MCDM; intuitionistic fuzzy sets; cryptocurrency; cryptocurrency selection; investment decisions; financial innovation; Industry 4.0

【发表时间】2022

【收录时间】2022-09-09

【文献类型】 实证数据

【DOI】 10.3390/axioms11080404

【Author】 Vazquez, Eric

【Source】SOUTH ATLANTIC QUARTERLY

【影响因子】1.763

【主题类别】

区块链治理-市场治理-数字货币

【Abstract】

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】

【发表时间】2022

【收录时间】2022-09-09

【文献类型】 观点阐述

【DOI】 10.1215/00382876-9826018

【Author】 Patra, Gyana Ranjan Mohanty, Mihir Narayan

【Source】COMPUTATIONAL ECONOMICS

【影响因子】1.741

【主题类别】

区块链治理-市场治理-数字货币

【Abstract】In today's world the cryptocurrencies have taken a special place in the financial market with the aid of time series forecasting and with a market value of almost USD 1.5 Trillion as of August 2021. These financial commodities show more volatility and effect of different internal and external forces. The prediction of such cryptocurrencies is a time consuming and difficult affair. In this paper, an attempt is made with a multilayer Gated Recurrent Unit based model for price prediction of cryptocurrencies. The currencies considered in this work are Bitcoin, Ethereum and Dogecoin and are pre-processed to deal with the NaN values. The LSTM model, one variant of recurrent neural network is used initially for predication. Further, the Gated Recurrent Unit is used with single feature. However, it is observed that for multiple features with three layers of Gated Recurrent Units based model is working well with error minimization. The performance of the proposed model is compared with other two models over a 21-day forecasting window. The proposed model is found to provide better performance in terms of different parameters like mean square error, root mean square error, mean absolute error, mean absolute percentage error, p-value, and precision values than the other two models.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Crypto-currency; Prediction; Gated recurrent unit; Long short-term memory; Mean absolute percentage error

【发表时间】

【收录时间】2022-09-09

【文献类型】 实证数据

【DOI】 10.1007/s10614-022-10310-1

【Author】 Nyakurukwa, Kingstone Seetharam, Yudhvir

【Source】INTERNATIONAL FINANCE

【影响因子】1.204

【主题类别】

区块链治理-市场治理-数字货币

【Abstract】This study revisits stock market integration in Africa using an information-theoretic framework that quantifies the flow of information between exchanges. We use daily return data for seven MSCI-classified African stock exchanges between 2011 and 2021. As Bitcoin has become an important asset class on the African continent, we also explore whether this cryptocurrency confers any diversification benefits. Our method holds that stock markets are integrated if there is a significant flow of information between exchanges. The results reveal a statistically insignificant flow of information among African stock exchanges, and for the few cases in which information flow is statistically significant, the magnitudes are low. South Africa is the most influential stock market, as it transmits most of the total transfer entropy (informational value) in the system. We also observe that African stock exchanges are weakly integrated with Bitcoin.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Bitcoin; information theory; stock market integration; transfer entropy

【发表时间】

【收录时间】2022-09-09

【文献类型】 实证数据

【DOI】 10.1111/infi.12419

【Author】 Bruhn, Pascal Ernst, Dietmar

【Source】JOURNAL OF RISK AND FINANCIAL MANAGEMENT

【影响因子】0.000

【主题类别】

区块链治理-市场治理-数字货币

【Abstract】The cryptocurrency market offers significant investment opportunities but also entails higher risks as compared to other asset classes. This article aims to analyse the financial risk characteristics of individual cryptocurrencies and of a broad cryptocurrency market portfolio. We construct a portfolio comprising the 20 largest cryptocurrencies, which cover 82.1% of the total cryptocurrency market. The returns are examined for extreme tail risks by the application of Extreme Value Theory. We utilise the GARCH-EVT approach in combination with a novel algorithm to automatically determine the optimal threshold to model the tail distribution. Furthermore, we aggregate the individual market risks with a t-Student Copula to investigate possible diversification effects on a portfolio level. The empirical analysis indicates that all examined cryptocurrencies show high volatility in their price movements, whereby Bitcoin acts as the most stable cryptocurrency. All return distributions are heavy-tailed and subject to extreme tail risks. We find strong, positive intra-market correlations, in particular with the two largest cryptocurrencies Bitcoin and Ethereum. No diversification effect can be achieved by aggregating market risks. On the contrary, a negligibly lower expected return and higher joint extreme returns can be observed. From this analysis, it can be concluded that investments in individual cryptocurrencies as well as in a portfolio show extreme risks of losses. From the investor's point of view, a possible strategy of risk reduction through portfolio formation within cryptocurrencies is only promising to a limited extent and does not offer a satisfactory solution to significantly reduce the risk within this asset class.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】cryptocurrencies; extreme value theory; GARCH; Copulas; cryptocurrency portfolio; GARCH-EVT; risk management

【发表时间】2022

【收录时间】2022-09-09

【文献类型】 实证数据

【DOI】 10.3390/jrfm15080346

【Author】 Zeng, Hongjun Ahmed, Abdullahi D.

【Source】INTERNATIONAL JOURNAL OF MANAGERIAL FINANCE

【影响因子】0.000

【主题类别】

区块链治理-市场治理-市场分析

【Abstract】Purpose This paper aims to provide new perspectives on the integration of East Asian stock markets and the dynamic volatility transmission to the Bitcoin market utilising daily data from 2014 to 2020. Design/methodology/approach The authors undertake comprehensive analyses of the dependency dynamics, systemic risk and volatility spillover between major East Asian stock and Bitcoin markets. The authors employ a vine-copula-CoVaR framework and a VAR-BEKK-GARCH method with a Wald test. Findings (a) With exception of KS11 and N225; HSI and SSE; HSI and KS11, which have moderate dependence, dependencies among other markets are low. In terms of tail risk, the upper tail risk is more significant in capturing strong common variation. (b) Two-way and asymmetric risk spillover effects exist in all markets. The Hong Kong and Japanese stock markets have significant risk spillovers to other markets, and quite notably, the Chinese stock market is the largest recipient of systemic risk. However, the authors observe a more significant risk spillover from the Chinese stock market to the Bitcoin market. (c) The VAR-BEKK-GARCH results confirm that the Korean market is a significant emitter of volatility spillovers. The Bitcoin market does provide diversification benefits. Interestingly, the Chinese stock market has an intriguing relationship with Bitcoin. (d) An increase in spillovers in East Asia boosts spillovers to Bitcoin, but there is no intuitive effect of Bitcoin spillovers on East Asian spillovers. Originality/value For the first time, the authors examine the dynamic linkage between Bitcoin and the major East Asian stock markets.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Major East Asian stock markets; Bitcoin; Spillover; Systemic risk; Multivariate GARCH; E52; F50; G23; G28

【发表时间】

【收录时间】2022-09-09

【文献类型】 实证数据

【DOI】 10.1108/IJMF-03-2021-0161

【Author】 Lv, Zhihan Qiao, Liang Li, Yuxi Yuan, Yong Wang, Fei-Yue

【Source】PATTERNS

【影响因子】0.000

【主题类别】

区块链应用-虚拟经济-元宇宙

【Abstract】The development of Digital Twins has enabled them to be widely applied to various fields represented by intelligent manufacturing. A Metaverse, which is parallel to the physical world, needs mature and secure Digital Twins technology in addition to Parallel Intelligence to enable it to evolve autonomously. We propose that Blockchain combined with other areas does not simultaneously require all of the basic elements. We extract the immutable characteristics of Blockchain and propose a secure multidimensional data storage solution called BlockNet that can ensure the security of the digital mapping process of the Internet of Things, thereby improving the data reliability of Digital Twins. Additionally, to address some of the challenges faced by multiscale spatial data processing, we propose a nonmutagenic multidimensional Hash Geocoding method, allowing unique indexing of multidimensional information and avoiding information loss due to data dimensionality reduction while improving the efficiency of information retrieval and facilitating the implementation of the Metaverse through spatial Digital Twins based on these two studies.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】

【发表时间】2022

【收录时间】2022-09-09

【文献类型】 理论模型

【DOI】 10.1016/j.patter.2022.100468

【Author】 Haslwanter, Elias

【Source】INTERNATIONALE KATHOLISCHE ZEITSCHRIFT COMMUNIO

【影响因子】0.000

【主题类别】

区块链应用-虚拟经济-元宇宙

【Abstract】The relationship between Liturgy and Media is very complex and multi-layered. This paper looks at the beginnings of broadcasts of liturgical services on radio and television and recalls the brief but heated discussion in the 1950s, in which Romano Guardini and Karl Rahner, among others, rejected them with reference to arcane discipline. In the face of de facto success of liturgical broadcasts, the concept of intentional participation in worship by those not physically present was coined. The current pandemic has seen a significant increase in the number of church service broadcasts, livestreams, and other digital offerings. These, with their more and more interactive potentials, and the Internet's progression into the metaverse raise numerous fundamental liturgical and sacramental theological questions. Many of these are not as new as they may seem.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】liturgy; metaverse; sacraments; digitalization; theology

【发表时间】2022

【收录时间】2022-09-09

【文献类型】 观点阐述

【DOI】 10.14623/com.2022.3.287-297