Recently, the world of cryptocurrencies has experienced an undoubted increase in interest. Since the first cryptocurrency appeared in 2009 in the aftermath of the Great Recession, the popularity of digital currencies has, year by year, risen continuously. As of February 2021, there are more than 8525 cryptocurrencies with a market value of approximately USD 1676 billion. These particular assets can be used to diversify the portfolio as well as for speculative actions. For this reason, investigating the daily volatility and co-volatility of cryptocurrencies is crucial for investors and portfolio managers. In this work, the interdependencies among a panel of the most traded digital currencies are explored and evaluated from statistical and economic points of view. Taking advantage of the monthly Google queries (which appear to be the factors driving the price dynamics) on cryptocurrencies, we adopted a mixed-frequency approach within the Dynamic Conditional Correlation (DCC) model. In particular, we introduced the Double Asymmetric GARCH–MIDAS model in the DCC framework.
Cryptocurrencies are a type of digital currencies based on cryptography principles. Cryptocurrencies are a unique combination of three characteristics: they provide anonymity, they are independent of central authority and they provide protection from double spending attack. The aim of this paper is to capture trends in the area of significant cryptocurrencies price developments and to explain their causes. The current research in this area is exclusively limited to an analysis of the price developments of the most important Bitcoin cryptocurrency; our research is the first to focus on other cryptocurrencies too. The economic perspective on cryptocurrencies is based on IT knowledge regarding the principles of their functioning. We have created a database of prices of 1278 cryptocurrencies from 2013 to 2016. This database is publicly available. To analyse the data, SQL query language was used.
Bitcoin and other prominent cryptocurrencies have gained much attention since the last several years. Globally known as digital coin and virtual currency, this cryptocurrency is gained and traded within the blockchain system. The blockchain technology adopted in using the cryptocurrency has raised the eyebrows within the banking sector, government, stakeholders and individual investors. The rise of the cryptocurrency within this decade since the inception of Bitcoin in 2009 has taken the market by storm. Cryptocurrency is anticipated as the future currency that might replace the current paper currency worldwide. Even though the interest has caught the attention of users, many are not aware of its opportunities, drawbacks and challenges for the future. Researches on cryptocurrencies are still lacking and still at its infancy stage. In providing substantial guide and view to the academic field and users, this paper will discuss the opportunities in the cryptocurrency such as the security of its technology, low transaction cost and high investment return. The originality of this paper is on the discussion within law and regulation, high energy consumption, possibility of crash and bubble, and attacks on network. The future undertakings of cryptocurrency and its application will be systematically reviewed in this paper.
We propose a design for philanthropic or publicly-funded seeding to allow
(near) optimal provision of a decentralized, self-organizing ecosystem of
public goods. The concept extends ideas from Quadratic Voting to a funding
mechanism for endogenous community formation. Individuals make public goods
contributions to projects of value to them. The amount received by the project
is (proportional to) the square of the sum of the square roots of contributions
received. Under the "standard model" this yields first best public goods
provision. Variations can limit the cost, help protect against collusion and
aid coordination. We discuss applications to campaign finance, open source
software ecosystems, news media finance and urban public projects. More
broadly, we offer a resolution to the classic liberal-communitarian debate in
political philosophy by providing neutral and non-authoritarian rules that
nonetheless support collective organization.
More than a decade after the revolutionary whitepaper by Satoshi Nakamoto\[1\], bitcoin and the blockchain are still shaking the core foundations of how humans perceive money. Bitcoin’s disruptions in major traditional industries cannot be understated. Despite the groundbreaking feats of blockchain technology, it has failed to achieve its most important promise of one-CPU-one-vote, the core premise upon which its consensus protocol is built. Bitcoin has evolved into a store of value, rather than a medium for undertaking regular everyday transactions. On average, bitcoin is able to process about 4.6 transactions per second\[2\] in contrast to Visa’s 1,700 transactions per second\[3\]. This means that it may take minutes or even hours depending on network congestion, to make a bitcoin transaction. While there have been a number of spinoff cryptosystems intent on fixing the blockchain’s failings, the ultimate dream of a truly decentralized peer-to-peer cryptosystem is far from reality. It is worth noting that the blockchain's inherent weakness is not a bug but a feature of how its proof-of-work (PoW) consensus protocol is implemented. This essay seeks to explain bitcoin’s PoW and how it is responsible for bitcoin’s scalability issues, and to a greater extent waste electric and computing power.
The idea of PoW was invented in 1993 by Cynthia Dwork and Moni Naor in a conference article titled “Pricing via Processing or Combating Junkmail”\[4\]. The article proposed a mechanism for dealing with the frivolousness of junk mail by requiring a participant to compute a selectable function in order to gain access to a resource. Dwork and Naor noted that this mechanism could be implemented for general use in controlling access to a shared resource. For bitcoin, the shared resource is a distributed peer-to-peer PoW chain (blockchain), a chain of the hash of a block (ledger) of transactions. When nodes receive broadcast transactions, they work to create (mine) blocks by expending CPU power to compute the PoW function based on a predetermined difficulty. Using CPU power as votes, other nodes may express acceptance of a valid block by working on extending it and refusing an invalid block by refusing to work on it. The majority (51%) of nodes determine the course of the chain. This consensus protocol prevents double-spending even in the absence of a trusted entity. By convention, incentives are baked into the network in the form of coins. The first transaction in a block is a special transaction that starts a new coin credited to the owner of the block. While incentives are the best reward for nodes supporting the network, the competitive nature of how blocks are mined, has become the network’s own achilles heel.
The blockchain operates a traditional competitive winner-takes-all type of cryptosystem. Two main problems arise from this type of structure. The first problem is continuous centralization. This arises when only nodes with large CPU powers among the lot are able to mine blocks. Coin rewards from PoW lead to a scramble for incentives as with any system designed around merit. The scramble inherently increases the mining difficulty at the behest of nodes with relatively small computing power. As it stands now, about 1% of nodes on the blockchain control about 99% of the computing power expended on the network. Running a blockchain node on a PC with a regular CPU can be described as crazy at best. The convention in recent times is to acquire special-purpose GPU miners which are way faster and more efficient than regular CPUs. Putting many individual nodes together in a pool to form a single node is the other ‘profitable’ alternative. On the blockchain, motivation for incentives supersedes that of pure enthusiasm and enthusiasm is essential for innovation. How can nodes, programmed to be divided against each other work to support the network? As our Lord Jesus said in Matthew 12:25, “Every kingdom divided against itself will be ruined and every city or household divided against itself will not stand”\[5\].
The second problem is energy inefficiency. When nodes work to mine the next block in the chain, only one node wins. The resources expended by the loser nodes in trying to compete are wasted. It is estimated that the blockchain wastes about 78 terawatt-hours of electricity annually. To put this into context, it is about four times Ghana’s electricity consumption (~0.093 TWh) in 2019\[6\]. Climate scientists warn that bitcoins emissions alone could have a significant effect on the environment\[7\].
We have explained proof-of-work and how such a consensus mechanism is implemented in the blockchain network. It has been established that blockchain PoW works in a competing fashion and that incentives are awarded in a winner-takes-all manner. These features are responsible for bitcoin’s energy inefficiency and continuous centralization.
Nakamoto, S., 2019. Bitcoin: A peer-to-peer electronic cash system. Manubot.
Kenny, L., 2019. The Blockchain Scalability Problem & the Race for Visa-Like Transaction Speed. https://towardsdatascience.com/the-blockchain-scalability-problem-the-race-for-visa-like-transaction-speed-5cce48f9d44
Dwork, C. and Naor, M., 1992, August. Pricing via processing or combatting junk mail. In Annual international cryptology conference (pp. 139-147). Springer, Berlin, Heidelberg.
Matthew 12:25, Holy Bible, New International Version.
Energy Commission of Ghana. 2020. National Energy Statistics. http://energycom.gov.gh/files/2020%20ENERGY%20STATISTICS-revised.pdf
Mora, C., Rollins, R.L., Taladay, K., Kantar, M.B., Chock, M.K., Shimada, M. and Franklin, E.C., 2018. Bitcoin emissions alone could push global warming above 2 C. Nature Climate Change, 8(11), pp.931-933.
A purely peer-to-peer version of electronic cash would allow online payments to be sent directly from one party to another without going through a financial institution. Digital signatures provide part of the solution, but the main benefits are lost if a trusted third party is still required to prevent double-spending. We propose a solution to the double-spending problem using a peer-to-peer network. The network timestamps transactions by hashing them into an ongoing chain of hash-based proof-of-work, forming a record that cannot be changed without redoing the proof-of-work. The longest chain not only serves as proof of the sequence of events witnessed, but proof that it came from the largest pool of CPU power. As long as a majority of CPU power is controlled by nodes that are not cooperating to attack the network, they'll generate the longest chain and outpace attackers. The network itself requires minimal structure. Messages are broadcast on a best effort basis, and nodes can leave and rejoin the network at will, accepting the longest proof-of-work chain as proof of what happened while they were gone.
Cryptocurrencies have become a very popular topic recently, primarily due to their disruptive potential and reports of unprecedented returns. In addition, academics increasingly acknowledge the predictive power of Twitter for a wide variety of events and more specifically for financial markets. This paper studies to what extent public Twitter sentiment can be used to predict price returns for the nine largest cryptocurrencies: Bitcoin, Ethereum, XRP, Bitcoin Cash, EOS, Litecoin, Cardano, Stellar and TRON. By using a cryptocurrency-specific lexicon-based sentiment analysis approach, financial data and bilateral Granger-causality testing, it was found that Twitter sentiment has predictive power for the returns of Bitcoin, Bitcoin Cash and Litecoin. Using a bullishness ratio, predictive power is found for EOS and TRON. Finally, a heuristic approach is developed to discover that at least 1–14% of the obtained Tweets were posted by Twitter “bot” accounts. This paper is the first to cover the predictive power of Twitter sentiment in the setting of multiple cryptocurrencies and to explore the presence of cryptocurrency-related Twitter bots.
ResearchCoin (RSC) is the incentive within the ResearchHub network designed to encourage open participation in the scientific community. The scientific record is too important to be hidden behind paywalls and in ivory towers. Science should be open: not only for reading, but also for reusing. ResearchCoin, and by extension ResearchHub, are designed to accelerate the pace of scientific research by encouraging academics to interact in a fully open and collaborative manner. This paper will describe ResearchCoin, the ResearchHub network, the impetus for the creation of both, and the intended impact on the scientific community.
This paper reviews the empirical literature on the highly popular phenomenon of herding behaviour in the markets of digital currencies. Furthermore, a comparison takes place with outcomes from earlier studies about traditional financial assets. Moreover, we empirically investigate herding behaviour of 240 cryptocurrencies during bull and bear markets. The present survey suggests that empirical findings about whether herding phenomena have made a significant appearance or not in cryptocurrency markets are split. The Cross-sectional absolute deviations (CSAD) and Cross-sectional standard deviations (CSSD) approaches for measuring herding tendencies are found to be the most popular. Different behaviour is detected in bull periods compared to bear markets. Nevertheless, evidence from primary studies indicates that herding is stronger during extreme situations rather than in normal conditions. However, our empirical estimations reveal that herding behaviour is evident only in bull markets. These findings cast light on and provide a roadmap for investment decisions with modern forms of liquidity.
Blockchain technology has attracted a lot of attention in the previous years as a secure way to protect transactions in different processes. It has been particularly used to define cryptocurrencies. While inherently secure against classical single node attacks, the blockchain cryptocurrencies have recently been subject to attacks by malwares able to capture a single user wallet and its included keys. In this work we propose the use of biometric cryptosystems to control the access to the wallets on single machines. After a brief description of the blockchain, the cryptocurrencies and the possible attacks, the paper describes the use of convolutional neural network face recognition as a tool to extract biometric features that help in a key binding approach to protect the personal data in the wallet. Experiments have been conducted on three independent face datasets and the results obtained are satisfactory. The equal error rate between false acceptance and false rejection is negligible when testing on images from the same dataset used for the training of the convolutional neural network. This generalizes well when experimenting on two other independent datasets. These results prove that face cryptosystems can be used to protect the access on sensitive data existing in the wallets of many cryptocurrencies.