【Author】 Bouteska, Ahmed Mefteh-Wali, Salma Dang, Trung
【影响因子】10.884
【主题类别】
区块链治理-市场治理-数字货币
【Abstract】In this paper, we examine the impact of investor sentiment on Bitcoin returns. Using a large dataset of messages discussed on social media and several financial indicators, we create a sentiment indicator based on computational text analysis and driven by the principal component analysis (PCA) method. We utilize a vector autoregressive analysis and other analytical methods to examine the sentiment index-bitcoin return nexus. Our findings reveal that the sentiment index is a strong predictor of cryptocurrency market returns in the short term. Furthermore, we confirm that during the COVID-19 pandemic, investors' sentiments significantly impacted Bitcoin returns. Our results show that the proposed sentiment index can generate excess returns for investors who utilize it as a return predictor. Our empirical findings suggest important policy implications.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Behavioral finance; Investor sentiment; Bitcoin; Cryptocurrencies; Textual analysis for sentiment analysis
【发表时间】2022
【收录时间】2022-12-19
【文献类型】 实证数据
【影响因子】7.307
【主题类别】
区块链应用-实体经济-众包领域
区块链技术-协同技术-机器学习
【Abstract】In this paper, we address the problem of behavior prediction for task allocation in blockchain-based crowdsourcing framework. Centralized crowdsourcing frameworks complement workers' reputations with predicted behavior, through Machine Learning (ML) models, to improve the task allocation performance and maintain worker engagement. Existing blockchain-based crowdsourcing frameworks allocate tasks to workers using reputation solely, which neglects the impact of a task's context on the worker's behavior. Our contribution is an on-chain behavior prediction ML model for task allocation on top of a proposed blockchain-based crowdsourcing framework. The ML model, hosted on blockchain, reflects a worker's unique behavior for a task given its context. The proposed ML model is: (1) trained off-chain since it has lower monetary cost compared to on-chain training, and (2) deployed on-chain as a smart contract to enable transparent predictions. The task allocation mechanism in the proposed blockchain-based crowdsourcing framework considers workers' predicted behavior and a Quality of Information (QoI) metric that includes distance to the task, completion time, and workers' reputation. The evaluation conducted confirms that the proposed task allocation mechanism, implemented using Solidity, outperforms the benchmark in terms of percentage of allocation, workers' QoI, and reputation change. (C) 2022 Elsevier B.V. All rights reserved.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Machine Learning; Blockchain; Behavior; Crowdsourcing; Smart contract; Bagged Trees
【发表时间】2022
【收录时间】2022-12-19
【文献类型】 实验仿真
【影响因子】6.239
【主题类别】
区块链应用-虚拟经济-元宇宙
【Abstract】The accuracy of artificial intelligence (AI) models is crucial for connected and autonomous vehicles (CAVs). However, in reality, model training under less frequent weather faces the problem of insufficient sampling. Also, in the real world, weather, sunlight, etc., can only change with the speed of the real-time clock, so the traditional sampling process is very slow. Moreover, currently, collective learning, which can make up the limited experience and computing power of a single vehicle, is always introduced to cases where the data from participants have the same structure, wasting massive heterogeneous data from vehicles of different brands. Therefore, in this paper, we propose a quantum collective learning and many-to-many matching game-based scheme in the metaverse for CAVs. The environment is simulated in the metaverse, which has its own time clock system, thereby expanding sample size and speeding up the sampling process. And we quantify the quality of intelligence in collective learning from the perspective of feature diversity. It is the cornerstone of collective learning between heterogeneous vehicles, facilitating maximum utilization of data with different structures. Then, we formulate the distributed vehicles selection problem as a many-to-many matching game and use Gale-Shapely algorithm to solve it. Also, we formulate the spectrum resource allocation problem as a discrete Markov decision process (MDP) and adopt a quantum-inspired reinforcement learning (QRL) algorithm to find the optimal policy to achieve the high revenue of the system. In simulations, the performance of the proposed scheme is compared with existing methods.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Metaverse; connected and autonomous vehicles (CAVs); collective learning; many-to-many matching game; inte-lligence networking
【发表时间】2022
【收录时间】2022-12-19
【文献类型】 理论模型
【DOI】 10.1109/TVT.2022.3190271
【影响因子】3.860
【主题类别】
区块链治理-技术治理-智能合约漏洞检测
【Abstract】Recently, security issues of smart contracts are arising great atten-tion due to the enormous financial loss caused by vulnerability attacks. There is an increasing need to detect similar codes for hunting vulnerability with the increase of critical security issues in smart contracts. Binary similarity detection that quantitatively measures the given code diffing has been widely adopted to facilitate critical security analysis. However, due to the difference between common programs and smart contract, such as diversity of bytecode generation and highly code homogeneity, directly adopting existing graph matching and machine learning based techniques to smart contracts suffers from low accuracy, poor scalability and the limitation of binary similarity on function level. Therefore, this paper investigates graph neural network to detect smart contract binary code similarity at the program level, where we conduct instruction-level normalization to reduce the noise code for smart contract pre-processing and construct contract control flow graphs to represent smart contracts. In particular, two improved Graph Convolutional Network (GCN) and Message Passing Neural Network (MPNN) models are explored to encode the contract graphs into quantitatively vectors, which can capture the semantic information and the program-wide control flow information with temporal orders. Then we can efficiently accomplish the similarity detection by measuring the distance between two targeted contract embeddings. To evaluate the effectiveness and efficient of our proposed method, extensive experiments are performed on two real-world datasets, i.e., smart contracts from Ethereum and Enterprise Operation System (EOS) blockchain-based platforms. The results show that our proposed approach outperforms three state-of-the-art methods by a large margin, achieving a great improvement up to 6.1% and 17.06% in accuracy.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Smart contract; similarity detection; neural network
【发表时间】2023
【收录时间】2022-12-19
【文献类型】 实证数据
【DOI】 10.32604/cmc.2023.028058
【影响因子】3.239
【主题类别】
区块链治理-市场治理-市场分析
【Abstract】This study examines how the COVID-19 pandemic has affected the connectedness between non -fungible tokens, decentralized finance coins, traditional financial assets, and cryptocurrencies. We employed a time-varying parameter vector autoregressive based frequency-dependent network connectedness approach to investigate return and volatility spillover effects between assets in time and frequency domains. The findings show that both the returns and volatility spillovers have been significantly affected by the COVID-19 pandemic, and long-and short-term connect-edness vary over the course of the pandemic. These findings have implications for investors, portfolio managers, and policymakers regarding their investment strategies, portfolio allocation, and risk monitoring.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Non -fungible tokens; Decentralized finance; COVID-19 pandemic; Spillover effects
【发表时间】2022
【收录时间】2022-12-19
【文献类型】 实证数据
【影响因子】3.136
【主题类别】
区块链治理-市场治理-市场分析
【Abstract】The sudden market crash around 20 February 2020 on the dawn of the COVID-19 pandemic has accelerated the digitalization of all human communication and revived the interest for risk mitigation during stress periods. Interestingly, FAANA (Facebook, Apple, Amazon, Netflix, and Alphabet) stocks exhibited positive returns with remarkable resilience throughout the pandemic period, suggesting a change in their investing risk. In this paper, we take a different step from the existing literature and examine the hedging, diversifying, and safe haven properties of FAANA stocks against four alternative assets, namely gold, U.S. Treasury bonds, Bitcoin, and U.S. Dollar/ CHF. Our analysis covers an extended sample period comprising the heightened uncertainty during the recent pandemic period. It involves conditional correlations, optimal weights, hedge ratios, and hedging effectiveness for the pairs of FAANA stock and alternative asset during the full sample period and the COVID-19 pandemic period. The results show that the majority of FAANA stocks serve as weak/strong safe havens against gold, Treasury bonds, Bitcoin, and Dollar/CHF in the full sample period. Further, few FAANA stocks serve as strong safe havens against the U.S. Treasury and Dollar/CHF during the pandemic. Our findings suggest that FAANA, once thought as risky high growth tech stocks, have gained maturity and became a safe blanket during the latest turbulent period.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Safe haven assets; Hedging and diversification; FAANA stocks; Bitcoin; Gold; U; S; Treasury bonds; Dollar Swiss franc; COVID-19 outbreak
【发表时间】2023
【收录时间】2022-12-19
【文献类型】 实证数据
【Author】 Trucios, Carlos Taylor, James W.
【影响因子】2.627
【主题类别】
区块链治理-市场治理-数字货币
【Abstract】Several procedures to forecast daily risk measures in cryptocurrency markets have been recently implemented in the literature. Among them, long-memory processes, procedures taking into account the presence of extreme observations, procedures that include more than a single regime, and quantile regression-based models have performed substantially better than standard methods in terms of forecasting risk measures. Those procedures are revisited in this paper, and their value at risk and expected shortfall forecasting performance are evaluated using recent Bitcoin and Ethereum data that include periods of turbulence due to the COVID-19 pandemic, the third halving of Bitcoin, and the Lexia class action. Additionally, in order to mitigate the influence of model misspecification and enhance the forecasting performance obtained by individual models, we evaluate the use of several forecast combining strategies. Our results, based on a comprehensive backtesting exercise, reveal that, for Bitcoin, there is no single procedure outperforming all other models, but for Ethereum, there is evidence showing that the GAS model is a suitable alternative for forecasting both risk measures. We found that the combining methods were not able to outperform the better of the individual models.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】digital assets; forecast combining; model misspecification; outliers; risk measures; structural breaks
【发表时间】
【收录时间】2022-12-19
【文献类型】 理论模型
【DOI】 10.1002/for.2929
CCF-C
【影响因子】1.968
【主题类别】
区块链应用-实体经济-电商领域
【Abstract】The days of storing data manually are behind us. We are opting for the online form of data storage and transfer. The new era of data digitization comes with its own perks and detriments. Cybersecurity is still a crucial concern today. As more data transfer occurs through an online medium, the risks of a breach and cyberattacks are inevitable. The whole foundation of e-commerce is based on the online transfer of goods and transactions without the need to travel. Transferring transactional data and transactions in e-commerce are prone to cyber threats. Our research's major objective is to develop a system that protects against such mishaps, especially during the transfer of transactional data, and also implement an automated system that ensures these transactions occur without any errors. To implement this, we are taking advantage of new emerging technologies called blockchain and smart contract. Blockchain allows a decentralized, immutable digital ledger to safely store and transfer data across the network. Blockchain technology is used in e-commerce to transfer transactions in a safe, secure, and faster way. Blockchain enables a peer-to-peer transaction system and data encryption that enables the safe transfer of transactional data. Blockchain is used to transfer transactional data. A smart contract is a special program that enables, verifies, and enforces the terms of a contract digitally. It provides transactional security as the contact is in place. The blockchain, coupled with smart contracts, will revolutionize the future of e-commerce. We have combined blockchain technology to ensure data security and user privacy with smart contracts to ensure that the protocol for the transaction is maintained. The results are presented by building and implementing the proposed system that provides the solution for transactional data privacy.
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】2022-12-19
【文献类型】 理论模型
【DOI】 10.1155/2022/2213336
【Author】 Ren, Diandian Guo, Hongyu Jiang, Tingfeng
【影响因子】1.916
【主题类别】
区块链治理-市场治理-数字货币
【Abstract】China's central bank digital currency (CBDC), e-CNY, is currently in a large-scale pilot stage. In this study, a new monetarist model, both theoretically and quantitively, is developed to assess the relationship between the managed anonymity feature of e-CNY, social welfare, and taxation. The findings are as follows. First, the introduction of managed anonymous CBDC affects the official and shadow economy by increasing the diversity of payment instruments and suppressing tax evasion, thereby improving social welfare and government tax revenue. Second, if CBDC is 'cash-like' in the sense that it offers relatively high anonymity, then issuing CBDC meets the public demand for anonymous small value payment services and enhances the individual welfare of most households. Third, if CBDC is 'deposit-like' in the sense that it offers relatively low anonymity, then issuing CBDC combats illegal transactions in the shadow economy, and increases the total amount of social welfare and government tax revenue. The model, calibrated to the Chinese economy, suggests that aggregate welfare and government tax revenue can be increased by up to 3.2% and 10%, respectively. These findings suggest that policy-makers can dynamically adjust the anonymity design of CBDC to better align it with changing policy objectives and economic conditions.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】CBDC; New monetarism; Social welfare; Taxation; E41; E47; E58
【发表时间】
【收录时间】2022-12-19
【文献类型】 理论模型
【Author】 Zhang, Yaoyu Zhang, Jiarui Zhang, Han
【影响因子】0.695
【主题类别】
区块链技术-核心技术-智能合约
区块链应用-实体经济-政务领域
【Abstract】With the development of blockchain technology, the automatic generation of smart contract has become a hot research topic. The existing smart contract automatic generation technology still has improvement spaces in complex process, third-party specialized tools required, specific the compatibility of code and running environment. In this paper, we propose an automatic smart contract generation method, which is domain-oriented and configuration-based. It is designed and implemented with the application scenarios of government service. The process of configuration, public state database definition, code generation and formal verification are included. In the Hyperledger Fabric environment, the applicability of the generated smart contract code is verified. Furthermore, its quality and security are formally verified with the help of third-party testing tools. The experimental results show that the quality and security of the generated smart contract code meet the expect standards. The automatic smart contract generation will "elegantly" be applied on the work of anti-disclosure, privacy protection, and prophecy processing in government service. To effectively enable develop "programmable government ".
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】smart contract; automatic code generation; anti-disclosure; privacy protection; prophecy processing
【发表时间】2022
【收录时间】2022-12-19
【文献类型】 实验仿真
【影响因子】0.000
【主题类别】
区块链治理-市场治理-数字货币
【Abstract】PurposeThe purpose of this research is to analyze the Bitcoin (BTC) and Ether (ETH) long memory and conditional volatility. Design/methodology/approachThe empirical approach includes ARFIMA-HYGARCH and ARFIMA-FIGARCH, both models under Student's t-distribution, during the period (ETH: November 9, 2017 to November 25, 2021 and BTC: September 17, 2014 to November 25, 2021). FindingsFindings suggest that ARFIMA-HYGARCH is the best model to analyze BTC volatility, and ARFIMA-FIGARCH is the best approach to model ETH volatility. Empirical evidence also confirms the existence of long memory on returns and on BTC volatility parameters. Results evidence that the models proposed are not as suitable for modeling ETH volatility as they are for the BTC. Originality/valueFindings allow to confirm the fractal market hypothesis in BTC market. The data confirm that, despite the impact of the Covid-19 crisis, the dynamics of BTC returns, and volatility maintained their patterns, i.e. the way in which they evolve, in relation to the prepandemic era, did not change, but it is rather reaffirmed. Yet, ETH conditional volatility was more affected, as it is apparently higher during Covid-19. The originality of the research lies in the focus of the analysis, the proposed methodology and the variables and periods of study.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Bitcoin; Ethereum; Conditional volatility; Covid-19
【发表时间】
【收录时间】2022-12-19
【文献类型】 理论模型
【DOI】 10.1108/SEF-05-2022-0251
【Author】 Beltramini, Enrico
【影响因子】0.000
【主题类别】
区块链应用-虚拟经济-元宇宙
【Abstract】In this article, I investigate the relationship between the sacred and technology through the lens of the Metaverse. I place theological anthropology in relationship with the Metaverse and the related, although theoretical, hypothesis of an invasive computer simulation. Initially, I consider the possibility of a continuum between the Metaverse and the simulation hypothesis. I conclude that there is no real continuum, as they differ greatly. Accordingly, the Metaverse cannot produce effects on human nature as theologically conceived. Next, I examine the hypothesis of the possible effects of the Metaverse on Christian life. I resolve that these effects are real, but only in case the sense of the sacredness of human nature is lost. Thus, a sense of the sacredness of human nature protects Christian life from the effects of an invasive virtual reality.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Metaverse; simulation; theology; anthropology
【发表时间】2022
【收录时间】2022-12-19
【文献类型】 观点阐述
【作者】 和鸿鹏;
【作者单位】北京航空航天大学人文与社会科学高等研究院;
【文献来源】医学与哲学
【复合影响因子】
【综合影响因子】
【主题类别】
区块链应用-虚拟经济-元宇宙
【摘要】人工智能技术的发展促使虚拟永生成为一种可能的技术化永生方式，虚拟永生的核心就在于对人类情感和意识的数字化存储、复制以及模拟，所以虚拟永生也就是数字化永生。从技术层面解读了读取意识、存储意识和再现意识的可能性，以及从社会层面探讨了虚拟化社会空间的现实探索，指出了完全虚拟化的在线乌托邦已通过游戏方式实现。最后基于泰格马克提出的生命3.0概念，指出身体不再为虚拟生命所必须，并讨论了虚拟生命可能带来的公平性、虚拟人死亡等问题。
【关键词】虚拟永生;;人工智能;;元宇宙;;生命3.0
【文献类型】 观点阐述
【发表时间】2022-12-19
【作者】 赵蔚;
【作者单位】同济大学建筑与城市规划学院;
【文献来源】城市规划学刊
【复合影响因子】
【综合影响因子】
【主题类别】
区块链应用-虚拟经济-元宇宙
【摘要】元宇宙作为数据驱动型智慧城市主义的虚拟建构虽然“元宇宙（Metaverse）”的概念已经存在了30年，但直到最近，“元宇宙”才成为公众关注的焦点。当前该领域的研究主要集中在两个方面。第一类涉及元宇宙在计算技术、沉浸式技术、生态系统、发展、趋势、应用、机遇、重大挑战、开放问题、研究议程、路线图等方面的最新技术和技术层次。讨论元宇宙作为一种将物理现实与数字虚拟相融合的多用户环境的许多主题。
【关键词】城乡规划管理;
【文献类型】 观点阐述
【发表时间】2022-12-19
【作者】 陈志霞;任兵;
【作者单位】华中科技大学;
【文献来源】理论探索
【复合影响因子】
【综合影响因子】
【主题类别】
区块链应用-虚拟经济-元宇宙
【摘要】政府数智领导力是元宇宙数智时代的产物，是政府在虚实共融的数智空间运用数智技术构建起一种具有共时、共识、共情的智能结构和社会秩序，以提高数智社会治理绩效的能力。在“宏观—中观—微观”维度上，它具有战略愿景与价值引领、互动共鸣与敏捷适应、数智素养和经验凝练的特征；在“社会—个人”双向价值构面上，它具有发掘价值、创造价值、扩大价值、提供价值的作用。因而，政府数智领导力提升有赖于领导干部发挥关键性作用，基于数智化思维围绕决策力和影响力增强方面，从虚实空间数据挖掘、数智政务信息公开、数智化元数据监控、虚拟数字人参与的关键应用到人本思维、平台思维、数据思维、迭代思维、敏捷思维的综合视角，实施区块化分布决策、全链路数智决策和轻战略敏捷决策来促进政府数智领导力的提升。
【关键词】元宇宙;;数智时代;;数智政府;;数智领导力;;数智化思维
【文献类型】 观点阐述
【发表时间】2022-12-19