Purpose This paper aims to present a methodology for constructing cointegrated portfolios consisting of different cryptocurrencies and examines the performance of a number of trading strategies for the cryptocurrency portfolios. Design/methodology/approach The authors apply a series of statistical methods, including the Johansen test and Engle–Granger test, to derive a linear combination of cryptocurrencies that form a mean-reverting portfolio. Trading systems are designed and different trading strategies with stop-loss constraints are tested and compared according to a set of performance metrics. Findings The paper finds cointegrated portfolios involving four cryptocurrencies: Bitcoin (BTC), Ethereum (ETH), Bitcoin Cash (BCH) and Litecoin (LTC), and the corresponding trading strategies are shown to be profitable under different configurations. Originality/value The main contributions of the study are the use of multiple altcoins in addition to bitcoin to construct a cointegrated portfolio, and the detailed comparison of the performance of different trading strategies with and without stop-loss constraints.
Laura Alessandretti, Abeer ElBahrawy, Luca Maria Aiello, Andrea Baronchelli
Machine learning and AI-assisted trading have attracted growing interest for the past few years. Here, we use this approach to test the hypothesis that the inefficiency of the cryptocurrency market can be exploited to generate abnormal profits. We analyse daily data for 1,681 cryptocurrencies for the period between Nov. 2015 and Apr. 2018. We show that simple trading strategies assisted by state-of-the-art machine learning algorithms outperform standard benchmarks. Our results show that non-trivial, but ultimately simple, algorithmic mechanisms can help anticipate the short-term evolution of the cryptocurrency market.
Stephen Chan, Jeffrey Chu, Yuanyuan Zhang, Saralees Nadarajah
In financial trading, cryptocurrencies like bitcoin use decentralization, traceability, and anonymity features to perform transactional activities. These digital currencies, using the emerging blockchain technologies, are forming the basis of the largest unregulated markets in the world. This creates various regulatory challenges, including the illicit purchase of drugs and weapons, money laundering, and funding terrorist activities. This chapter analyzes various legal and ethical implications, their effects, and various solutions to overcome the inherent issues that are currently faced by the policymakers and regulators. The authors present the result of an analysis of 30 recently published peer-reviewed scientific publications and suggest various mechanisms that can help in the detection and prevention of illegal activities that currently account for a substantial proportion of cryptocurrency trading. They suggest methods and applications that can also be used to identify the dark marketplaces in the future.
The evolution of money has accompanied the development of civilizations and technological innovations, leading to today’s cryptocurrencies. Cryptocurrencies have become a popular mode of payment globally because of their low cost, high-speed transferability and a decentralized tracking network that provides secure transactions and a high degree of anonymity. However, the decentralized system of cryptocurrencies has made global monetary systems more dynamic and therefore more prone to misuse as well as posing a threat to financial stability. Cryptocurrencies are also gaining popularity in Pakistan: its first cryptocurrency, named ‘Pakcoin’, was launched in 2015. The State Bank of Pakistan does not recognize any digital currency, and the Federal Board of Revenue and Federal Investigation Agency have taken legal action against local and internationally traded cryptocurrencies. This article reviews these risks and provides various regulatory solutions so that methods can be developed to improve the management of financial innovations and create a safer environment in which financial innovation can continue. Furthermore, developing countries such as Pakistan can take advantage of distributed ledger technology (used in cryptocurrencies) in applications including: microfinance to help the unbanked, in data identification systems and in land registries to help enforce property rights.
In this paper, we study the contemporaneous tail dependence structure in a pairwise comparison of the ten largest cryptocurrencies, namely Bitcoin, Dash, Dogecoin, Ethereum, Litecoin, Monero, Namecoin, Novacoin, Peercoin, and Ripple. We apply multivariate extreme value theory and we estimate a bias-corrected extreme correlation coefficient. Our findings reveal clear patterns of significantly high bivariate dependency in the distribution tails of some of the most basic and widespread cryptocurrencies, primarily over various downside constraints. This means that extreme correlation is not related to cryptocurrency market volatility per se, but to the trend of the cryptocurrency market. Therefore, extreme correlation increases in bear markets, but not in bull markets for these pairs. Interestingly, there is also a significant number of pairs which exhibit a weak level of dependency in distribution tails.
P2P networks are the mechanism used by cryptocurrencies to disseminate system information while keeping the whole system as much decentralized as possible. Cryptocurrency P2P networks have new characteristics that propose new challenges and avoid some problems of existing P2P networks. By characterizing the most relevant cryptocurrency network, Bitcoin, we provide details on different properties of cryptocurrency networks and their similarities and differences with standard P2P network paradigms. Our study allows us to conclude that cryptocurrency networks present a new paradigm of P2P networks due to the mechanisms they use to achieve high resilience and security. With this new paradigm, interesting research lines can be further developed, both in the focused field of P2P cryptocurrency networks and also when such networks are combined with other distributed scenarios.
In previous chapters, you learned about the Ethereum architecture, Solidity programming, and how to debug and deploy using different local and test setups. So far so good; but is that all enough to make you a master in the Ethereum blockchain? The main challenge that the blockchain market faces today is a lack of knowledge about where this technology can be best applied. Business leaders across verticals are struggling to find use cases that would be a good fit for blockchain implementation, and loads of arguments are taking place in this area. As a blockchain expert, it’s your job to dream, innovate, come up with ideas, and advise businesses about where this technology can bring maximum benefits.
In the past decade, many blockchain and DLT frameworks have flooded the market, but Ethereum is still the favorite of most blockchain lovers. As per a recent report, “Ethereum currently has the most active developer community in the space and has 30 times more developers than the second most active community.” The Ethereum blockchain does have some issues, yet it’s the market leader in its space, and no other framework is anywhere even close to this framework.
Abstract Baker and Wurgler identify high sentiment betas with small startup firms that have great growth potential. On the surface, cryptocurrencies share important features in common with high sentiment beta stocks. This paper investigates the degree to which, during the period July 18, 2010–February 26, 2018, the return to bitcoin displayed the characteristics of a high sentiment beta stock. Using a sentiment‐dependent factor model, the analysis indicates that in large measure, bitcoin returns resembled returns to high sentiment beta stocks. Additionally, we show that bitcoin's expected returns are low when sentiment measured by Volatility Index is high while expected returns are high when sentiment is low.
Yi Liu, Xingtong Liu, Chaojing Tang, Jian Wang · 5 authors
Bitcoin combines a peer-to-peer network and cryptographic algorithm to implement a distributed digital currency system, which keeps all transaction history on a public blockchain. Since all transactions recorded on the blockchain are public to everyone, Bitcoin users face a threat of leaking financial privacy. Many analysis and deanonymization approaches have been proposed to link transaction records to real identities. To eliminate this threat, we present an unlinkable coin mixing scheme that allows users to mix their bitcoins without trusting a third party. This mixing scheme employs a primitive known as ring signature with elliptic curve digital signature algorithm (ECDSA) to conceal the transfer of coins between addresses. The mixing server is only able to check whether the output addresses belong to its customers, but it cannot tell which address owned by which customer. Customers do not have to rely on the reputation of a third party to ensure his money will be returned, and his privacy will not be leaked. This scheme needs no modifications on current Bitcoin system and is convenient to deploy by any communities. We implemented a prototype of our scheme and tested it under the Bitcoin core's regtest mode. Security and privacy of our mixing scheme are ensured through the standard ring signature and ECDSA unforgeability.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Cüneyt Gürcan Akçora, Matthew Dixon, Yulia R. Gel, Murat Kantarcıoğlu
A key challenge for Bitcoin cryptocurrency holders, such as startups using ICOs to raise funding, is managing their FX risk. Specifically, a misinformed decision to convert Bitcoin to fiat currency could, by itself, cost USD millions. In contrast to financial exchanges, Blockchain based crypto-currencies expose the entire transaction history to the public. By processing all transactions, we model the network with a high fidelity graph so that it is possible to characterize how the flow of information in the network evolves over time. We demonstrate how this data representation permits a new form of microstructure modeling - with the emphasis on the topological network structures to study the role of users, entities and their interactions in formation and dynamics of crypto-currency investment risk. In particular, we identify certain sub-graphs ('chainlets') that exhibit predictive influence on Bitcoin price and volatility, and characterize the types of chainlets that signify extreme losses.
Using tick-level bitcoin data from February 2013 through April 2018, we show substantial arbitrage spreads between global bitcoin markets. Spreads follow multiple consistent patterns. Minimum and maximum prices show significant clustering. Spreads increase during the early hours of a day (according to coordinated universal time), when new exchanges enter markets, and following bitcoin heists and hacks. The full year 2017 and the first quarter of 2018 each had exploitable net arbitrage profit opportunities of at least USD380 million that smart money failed to capture. Based on long-term analyses, we also found that bitcoin market inefficiency has increased over time.
Non-linearity is characterized by an asymmetric mean-reverting property, which has been found to be inherent in the short-term return dynamics of stocks. In this paper, we explore as to whether cryptocurrency returns, as represented by Bitcoin, exhibit similar asymmetric reverting patterns for minutely, hourly, daily and weekly returns between June 2010 and February 2018. We identify several differences in the behavior of Bitcoin price returns in the pre-and post-$1,000 sub-periods and evidence of asymmetric reverting patterns in the Bitcoin price returns under all the ANAR models employed, regardless of the data frequency considered. We also present evidence indicating stronger reverting behavior of negative price returns in terms of both reverting speed and magnitude compared to positive returns and evidence of positive serial correlation with prior positive price returns. Finally, we also investigated asymmetries in Bitcoin price return series’ persistence by employing higher order ANAR models, finding evidence of a higher persistence of positive returns than negative returns, a result that further supports the existence of asymmetric reverting behavior in the Bitcoin price returns.
Trading of Bitcoin is spread about multiple venues where buying and selling is offered in various currencies. However, all markets trade one common good and by the law of one price, the different prices should not deviate in the long run. In this context we are interested in which platform is the most important one in terms of price discovery. To this end, we use a pairwise approach accounting for a potential impact of exchange rates. The contribution to price discovery is measured by Hasbrouck's and Gonzalo and Granger's information share. We then derive an ordering with respect to the importance of each market which reveals that the Chinese OKCoin platform is the leader in price discovery of Bitcoin, followed by BTC China.
Aim/Purpose: This paper explored the factors (enablers and barriers) that affect Bitcoin adoption in South Africa, a Sub-Saharan country with the high potential for Bitcoin adoption. Background: In recent years, Bitcoin has seen a rapid growth as a virtual cryptocurrency throughout the world. Bitcoin is a protocol which allows value to be exchanged over the internet without a central bank or intermediary. Cryptocurrencies such as Bitcoin are technological tools that arguably can contribute to reducing transactions costs. This paper explored the factors that affect Bitcoin adoption in South Africa, a Sub-Saharan country with the high potential for Bitcoin adoption, as little is known about the factors that affect Bitcoin adoption and the barriers to adoption. Methodology: A quantitative questionnaire was distributed to South African virtual communities where Bitcoin is a topic of interest, and 237 quantitative responses were received, along with 212 open-ended comments. Contribution: This research contributes to the body of knowledge in information systems by providing insights into factors that affect Bitcoin adoption in South Africa. It raises awareness of incentives and barriers to Bitcoin adoption at a time when financial literacy is a crucial issue both in South Africa and worldwide. Findings: The results indicate that perceived benefit, attitude towards Bitcoin, subjective norm, and perceived behavioral control directly affected the participants’ intentions to use Bitcoin. Perceived benefit, usefulness, ease of use, and trust-related risk were found to indirectly affect intention to use Bitcoin. Further, it emerges that the barriers to Bitcoin adoption in South Africa consist of the complex nature of Bitcoin and its high degree of volatility. Recommendations for Practitioners: Bitcoin can contribute to reducing transactions costs, but factors that affect adoption and the barriers to adoption should be taken into consideration. These findings can inform systems and software developers to develop applications that make managing Bitcoin keys and transacting using Bitcoin less complex and more intuitive for end users. Recommendation for Researchers: Bitcoin adoption in South Africa is a topic that has not been previously researched. Researchers could research similarities or differences in the various constructs that were used in this research model. Impact on Society: South African Bitcoin users consider it as a universal currency that makes cross-border payments cheaper. A large number of refugees and workers in South Africa make regular payments across borders. Bitcoin could reduce the costs of these transfers. Future Research: Future research could explore Bitcoin (and other cryptocurrencies) adoption in other developing countries. Researchers could look at factors that influence cryptocurrency adoption in general. The factors affecting adoption of other cryptocurrencies can be compared to the results of this study, and similarities and differences can thus be identified.
This article presents a brief overview of the Distributed Ledger Technology, Token Offering and their regulation, if any, in four main jurisdictions, the United States (U.S.), Switzerland, the European Union (EU), and Singapore. It should be noted that is expected to have new developments on the regulatory side, in this and other jurisdictions, of Distributed Ledger Technology and token offerings, Malta, for example, has recently officially stated the creation of the Malta Digital Innovation Authority that will be responsible to regulate and incentivize this industry in Malta and the EU. Distributed Ledger Technology and token offerings are fairly new concepts and are revolutionizing different industries at an incredibly fast pace. The regulators, as well as all other stakeholders, must maintain attention and remain vigilant to any developments in this regard. Conclusively, the Distributed Ledger Technology will, undoubtedly, bring innovative solutions to different industries, especially the financial services industry. As analyzed in the present article, key components previous to launching a token offering, are: define the jurisdiction that will be used for the corporate structure; the categorization of the token; and the applicable regulation accordingly.