Canh Phuc Nguyen, Nguyen Quang Binh, Thanh Dinh Su
The study examines the diversification capability of seven cryptocurrencies with the largest market size against risks from economic factors as oil price, gold price, interest rate, USD strength, and S&P500. Using the weekly data of Bitcoin, Litecoin, Ripple, Stellar, Monero, Dash, and Bytecoin in the period Aug/2014-Jun/2018, the study finds that there are structural breaks and ARCH disturbance in each cryptocurrency, suggesting a systematic risk within the cryptocurrency market. However, the causality between cryptocurrencies and economic factors is undirected. Interestingly, our findings show that cryptocurrencies are insignificant correlations with economic factors. The result implies that cryptocurrencies can not be assumed as financial assets to hedge systematic risks from economic factors.
Guglielmo Maria Caporale, Woo-Young Kang, Fabio Spagnolo, Nicola Spagnolo
This paper uses a Markov-switching non-linear specification to analyse the effects of cyber attacks on returns in the case of four cryptocurrencies (Bitcoin, Ethernam, Litecoin and Stellar) over the period 8/8/2015–2/28/2019. The analysis considers both cyber attacks in general and those targeting cryptocurrencies in particular, and also uses cumulative measures capturing persistence. On the whole, the results suggest the existence of significant negative effects of cyber attacks on the probability for cryptocurrencies to stay in the low volatility regime. This is an interesting finding, that confirms the importance of gaining a deeper understanding of this form of crime and of the tools used by cybercriminals in order to prevent possibly severe disruptions to markets.
We examine all available 146 Proof-of-Work-based cryptocurrencies that started trading prior to the end of 2014 and track their performance until December 2018. We find that about 60% of those cryptocurrencies were eventually in default. The substantial sums of money involved mean those bankruptcies will have an enormous societal impact. Employing cryptocurrency-specific data, we estimate a model based on linear discriminant analysis to predict such defaults. Our model is capable of explaining 87% of cryptocurrency bankruptcies after only one month of trading and could serve as a screening tool for investors keen to boost overall portfolio performance and avoid investing in unreliable cryptocurrencies.
Vasily Derbentsev, Natalia Datsenko, Olga Stepanenko, Vitaly Bezkorovainyi
This paper describes the construction of the short-term forecasting model of cryptocurrencies’ prices using machine learning approach. The modified model of Binary Auto Regressive Tree (BART) is adapted from the standard models of regression trees and the data of the time series. BART combines the classic algorithm classification and regression trees (C&RT) and autoregressive models ARIMA. Using the BART model, we made a short-term forecast (from 5 to 30 days) for the 3 most capitalized cryptocurrencies: Bitcoin, Ethereum and Ripple. We found that the proposed approach was more accurate than the ARIMA-ARFIMA models in forecasting cryptocurrencies time series both in the periods of slow rising (falling) and in the periods of transition dynamics (change of trend).
Derek Leung, Adam Suhl, Yossi Gilad, Nickolai Zeldovich
Decentralized cryptocurrencies rely on participants to keep track of the state of the system in order to verify new transactions. As the number of users and transactions grows, this requirement becomes a significant burden, requiring users to download, verify, and store a large amount of data to participate.
Jan 1, 2019·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Taneli Hukkinen, Juri Mattila, Kari Smolander, Timo Seppälä · 5 authors
In recent years, information systems have not been largely evaluated by their operating costs, but mainly by their strategic benefit and competitive advantage. As blockchain-based decentralized applications become more commonplace, representing a shift towards fully consumption-based distributed computing, a new mode of thinking is required of developers, with meticulous attention to computational resource efficiency. This study improves on a blockchain application designed for conducting microtransactions of electricity in a nanogrid environment. By applying the design science research methodology, we improve the efficiency of the application’s smart contract by 11 %, with further improvement opportunities identified. Despite the results, we find the efficiency remains inadequate for public Ethereum deployment. From the optimization process, we extrapolate a set of general guidelines for optimizing the efficiency of Ethereum smart contracts in any application.
Konstantin Mironov, Sergey Trishin, Amir Makhmutov, Vadim Kartak · 5 authors
In this article we consider tasks related to ensuring the integrity and availability of information in the Internet of Things (IoT) sphere. Such systems include sensors and similar devices, which are the sources of data, access points, which transmit data from sensors to the Internet and servers, which store received data and grant access to users. When storing data on a server and providing access to it, it is necessary to ensure its integrity and availability to users. To this end, it is proposed to apply a distributed ledger technology (DLT). One of the applications of DLT for data protection is energetics. Here we consider a system for processing and storing data on the production and consumption of electricity in a decentralized power grid. A review of currently existing projects related to the use of distributed ledger technologies in the energy sector is carried out. An important obstacle to the use of DLT in the IoT is the contradiction between, on the one hand, high memory computational requirements of the DLT, and, on the other hand, limited resources of IoT nodes. Further research directions are proposed that are associated with overcoming this obstacle in applying distributed ledger technologies in the energetics.
Applications and uses cases of distributed ledger technology (DLT) are increasingly attracting interest in the construction industry. However, DLT in construction is still considered a nascent field of research and practical applications of DLT in construction are at the very early readiness stages. This paper builds on a previously developed socio-technical systems framework for DLT in construction (i.e. Li et al., 2019) built on four dimensions of technical, process, policy and social, and proposes a roadmap to achieving readiness for macro adoption of DLT in the construction industry. First, the paper reviews existing readiness and adoption models and technology roadmaps for new technological innovations in the context of DLT highlighting their strengths and detailing why they are not suitable for DLT. Then, drawing on experience of existing models as a basis, it proposes a four-stage roadmap to readiness for adoption of DLT in the construction industry. The four-stage DLT Roadmap incorporates Conceptualisation, Appraisal, Preparation and Implementation. This roadmap is intended to provide the industry with a comprehensive framework to support adoption and diffusion of DLT for specific use cases. Future work will involve proposal of guidelines for each of the four dimensions across the four-stage DLT Roadmap and testing through workshop-identified use cases of DLT in construction.
A vehicular ad-hoc network (VANET) can improve the flow of traffic to facilitate intelligent transportation and to provide convenient information services, where the goal is to provide self-organizing data transmission capabilities for vehicles on the road to enable applications, such as assisted vehicle driving and safety warnings. VANETs are affected by issues such as identity validity and message reliability when vehicle nodes share data with other nodes. The method used to allow the vehicle nodes to upload sensor data to a trusted center for storage is susceptible to security risks, such as malicious tampering and data leakage. To address these security challenges, we propose a data security sharing and storage system based on the consortium blockchain (DSSCB). This digital signature technique based on the nature of bilinear pairing for elliptic curves is used to ensure the reliability and integrity when transmitting data to a node. The emerging consortium blockchain technology provides a decentralized, secure, and reliable database, which is maintained by the entire network node. In DSSCB, smart contracts are used to limit the triggering conditions for preselected nodes when transmitting and storing data and for allocating data coins to vehicles that participate in the contribution of data. The security analysis and performance evaluations demonstrated that our DSSCB solution is more secure and reliable in terms of data sharing and storage. Compared with the traditional blockchain system, the time required to confirm the data block was reduced by nearly six times and the transmission efficiency was improved by 83.33%.
Over the past decade, blockchain technology has attracted tremendous attention from both academia and industry. The popularity of blockchains was originated from the concept of crypto-currencies to serve as a decentralized and tamper-proof transaction data ledger. Nowadays, blockchains as the key framework in the decentralized public data-ledger have been applied to a wide range of scenarios far beyond crypto-currencies, such as the Internet of Things, healthcare, and insurance. This survey aims to fill the gap between a large number of studies on blockchain networks, where game theory emerges as an analytical tool, and the lack of a comprehensive survey on the game theoretical approaches applied in blockchain-related issues. In this survey, we review the game models proposed to address common issues in the blockchain network. The focus is placed on security issues, e.g., selfish mining, majority attack and denial of service attack, issues regarding mining management, e.g., computational power allocation, reward allocation, and pool selection, as well as issues regarding blockchain economic and energy trading. Additionally, we discuss the advantages and disadvantages of these selected game theoretical models and solutions. Finally, we highlight important challenges and future research directions of applying game theoretical approaches to incentive mechanism design and the combination of blockchain with other technologies.
Hongfang Lü, Kun Huang, Mohammadamin Azimi, Lijun Guo
Blockchain technology has been developed for more than ten years and has become a trend in various industries. As the oil and gas industry is gradually shifting toward intelligence and digitalization, many large oil and gas companies were working on blockchain technology in the past two years because of it can significantly improve the management level, efficiency, and data security of the oil and gas industry. This paper aims to let more people in the oil and gas industry understand the blockchain and lead more thinking about how to apply the blockchain technology. To the best of our knowledge, this is one of the earliest papers on the review of the blockchain system in the oil and gas industry. This paper first presents the relevant theories and core technologies of the blockchain, and then describes how the blockchain is applied to the oil and gas industry from four aspects: trading, management and decision making, supervision, and cyber security. Finally, the application status, the understanding level of the blockchain in the oil and gas industry, opportunities, challenges, and risks and development trends are analyzed. The main conclusions are as follows: 1) at present, Europe and Asia have the fastest pace of developing the application of blockchain in the oil and gas industry, but there are still few oil and gas blockchain projects in operation or testing worldwide; 2) nowadays, the understanding of blockchain in the oil and gas industry is not sufficiently enough, the application is still in the experimental stage, and the investment is not enough; and (3) blockchain can bring many opportunities to the oil and gas industry, such as reducing transaction costs and improving transparency and efficiency. However, since it is still in the early stage of the application, there are still many challenges, primarily technological, and regulatory and system transformation. The development of blockchains in the oil and gas industry will move toward hybrid blockchain architecture, multi-technology combination, cross-chain, hybrid consensus mechanisms, and more interdisciplinary professionals.
Yingli Wang, Catherine Huirong Chen, Ahmed Zghari-Sales
While blockchain technologies are gaining momentum within supply chains, academic understanding of concrete, real-life design and implementation is still lagging, hence offering very limited insights into the true implications of blockchain technology on supply chains. This paper reports a two-year design science research (DSR) study of a smart contract initiative piloted by a consortium in the UK’s construction sector. We seek answers to the research question, ‘How should a blockchain enabled supply chain be designed?’ Guided by the theory of business model, we explore how a group of supply chain actors collectively designs and pilots a blockchain solution that addresses the supply chain transparency and provenance problem. Our research is one of the very few longitudinal empirical studies to offer in-depth evidence about how blockchain is deployed in complex multi-tier supply chain networks. In compliance with DSR research paradigm, we make contributions at three levels: designing and instantiating the blockchain architect and proving its utility in addressing the target problem; developing a set of design principles as a mid-range theory that can be applied and tested in different blockchain supply chain contexts; and refining and extending the kernel theory of business value at supply chain network level.
Despite the past decade’s rapid innovation in adapting blockchain technology to new uses, financial intermediation remains elusive except in basic and highly collateralized forms. We introduce the concept of the technical frontier to delimit the kinds of interactions that can feasibly be structured algorithmically among pseudonymous agents, as on a blockchain, and show that lending and financial intermediation – unlike monetary exchange – lie outside it, even in simple forms. The path forward for truly blockchain-native financial applications, therefore, must involve the integration of real-world identity information in order to disincentivize defection. We discuss several potential technologies for doing so, and conclude that such integration is possible without compromising pseudonymity, provided real-world identity is available in the breach.
Decentralized finance has evolved as a major contender for traditional banking systems over the last few years. Evolution in blockchain and cryptography technologies are the driving forces for decentralized finance’s growth. The emergence of Bitcoin in the finance system was a major driving force toward the tremendous growth of decentralized finance. However, with various platforms merging every day, the decentralized finance sector is still in its early, unorganized stages. The current decentralized finance market is chaotic. With a new “coin” being introduced almost every month, standardization is highly lacking in the system. DeFi already has several different applications available. For instance, one can purchase stable coins, or assets pegged to a national currency, on decentralized exchanges, move the assets to a lending platform that is also decentralized to earn interest, and then add the interest-earning instruments to a decentralized liquidity pool or an on-chain investment fund. DeFi enterprises frequently aim at decentralized decision-making, or governance, in everything from the user fees to the products they provide. A decentralized program may be started by one person or a small number of individuals, but as the project gathers traction, its leaders frequently try to step down and cede control to the user base. A decentralized autonomous organization that has its rules and regulations written into computer code and that may issue governance tokens, which allow its holders a voice in decisions rather than allowing the decision-making to a centralized government authority as in case of traditional finance, could represent this transition. While on one side, world governments are still trying to grasp and regulate the sector, on the other side, the technology’s reach has been very limited. Undoubtedly, the emergence of blockchain-based decentralized finance is massively influencing our current finance technology industry. In this chapter, we discuss the current growth in the FinTech industry and the blockchain-based decentralized finance sector. Furthermore, we discuss how decentralized finance can be used in the current FinTech industry.
Since first coined by Google in 2012, knowledge graph has received extensive attention from both industry and academia, and has been widely used in many scenarios with success, e.g. information retrieval, online recommendation, question-answering, and so on. However, traditional centralized construction of knowledge graph faces many challenges, such as laborious and time-consuming, vulnerable to manipulation or tampering, lacking scrutiny, among others. Therefore, in this paper, we propose a novel decentralized knowledge graph construction method by means of crowdsourcing, and the business logic of crowdsourcing is implemented by blockchain-powered smart contracts to guarantee the transparency, integrity, and auditability. On this basis, the decentralized knowledge graph is used for a deep recommender system, and case studies validate the effectiveness of the system. This paper is aimed at providing a novel decentralized approach for constructing knowledge graph and serving as reference and guidance for future research and practical applications of knowledge graph.
One of the purported benefits of blockchain technologies is the ability to house what have been termed ‘smart’ contracts. Such contracts are potentially self-executing depending on the state of information recorded on a blockchain ledger. This paper examines the capabilities of smart contracts from an economic perspective. It is demonstrated that by improving observability and reducing the costs of verification of contract obligation performance, the space of feasible contracts can be enlarged. Moreover, by providing commitments to various monetary payments, a blockchain can potentially create a foundation to house certain mechanisms that have been shown to overcome difficulties of contractual incompleteness. This is demonstrated using a simple international trade environment. Thus, even though smart contracts must respect the incentives of decision-makers in their obligations, they have the potential to use easily verifiable elements to create incentives to reduce hold-up and other contractual difficulties.