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Estimating Profitability of Alternative Cryptocurrencies (Short Paper)
Abstract
Digital currencies have flourished in recent years, buoyed by the tremendous success of Bitcoin. These blockchain-based currencies, called altcoins, are associated with a few thousand to millions of dollars of market capitalization. Altcoins have attracted enthusiasts who enter the market by mining or buying them, but the risks and rewards could potentially be significant, especially when the market is volatile. In this work, we estimate the potential profitability of mining and speculating 18 altcoins using real-world blockchain and trade data. Using opportunity cost as a metric, we estimate the mining cost for an altcoin with respect to a more popular but stable coin. For every dollar invested in mining or buying a coin, we compute the potential returns under various conditions, such as time of market entry and hold positions. While some coins offer the potential for spectacular returns, many follow a simple bubble-and-crash scenario, which highlights the extreme risks—and potential gains—in altcoin markets.
... Unlike other cryptocurrencies, it exists firmly in both the meme economy and financial economy, a duality that has yet to be fully explored. The academic literature on Dogecoin is scarce and primarily focused on either the blockchain's coding infrastructure (Teutsch et al., 2019;Herrigan et al., 2018) or financial metrics (Chohan, 2017;Huang et al., 2018), with only a passing mention of its cultural value. Similarly, the literature on memes has not yet discussed the Dogecoin phenomenon. ...
In the modern financial system, the ability to create money is in the hands of a few central institutions. Blockchain networks, and by extension cryptocurrencies, were created with the promise of giving that power to users. The most well-known example of a blockchain technology achieving such decentralization is Bitcoin, but its popularity has arguably been matched by an alternative-currency named Dogecoin. Unlike other cryptocurrencies, which have marketed themselves on differentiating technical features, Dogecoin’s allure likely stems from its cultural roots as a meme. Where cryptocurrency is typically regarded as a difficult topic to grasp, the introduction of Doge’s (2013) most popular meme, into the crypto-space increased crypto’s accessibility to new participants. Consequently, Dogecoin exists in two economies: the financial economy and the cultural meme economy, with the latter having unprecedented tangible impacts on the former. Dogecoin’s unique cultural significance provides an example of how blockchain can succeed in promoting alternative money systems. At its peak in 2021, Dogecoin achieved a market capitalization of $88 billion. Where analysis of the Dogecoin phenomenon is lacking in the current literature, we will fill that gap with a case study of Dogecoin. By studying Dogecoin as a combination of money and meme, we can further our understanding of how to better promote social finance initiatives through the virality of memes.
... Huang et al. [47] describe short-term investing and mining strategies for cryptocurrencies relative to base currencies Litecoin and Bitcoin. Nguyen et al. [48] show that new cryptocurrencies have a small but significant negative impact on the price of Bitcoin. ...
A key component of security in decentralized blockchains is proof of opportunity cost among block producers. In the case of proof-of-work (PoW), currently used by the most prominent systems, the cost is due to spent computation. In this paper, we characterize the security investment of miners in terms of its cost in fiat money. This enables comparison of security allocations across PoW blockchains that generally use different PoW algorithms and reward miners in different cryptocurrency units. We prove that there exists a unique allocation equilibrium, depending on market prices only, that is achieved by both strategic miners (who contemplate the actions of others) and by miners seeking only short-term profit. In fact, the latter will unknowingly compensate for any attempt to deliberately shift security allocation away from equilibrium. Our conclusions are supported analytically through the development of a Markov decision process, game theoretical analysis, and derivation of no arbitrage conditions. We corroborate those results with empirical evidence from more than two years of blockchain and price data. Overall agreement is strong. We show that between January 1, 2018 and August 1, 2020, market prices predicted security allocation between Bitcoin and Bitcoin Cash with error less than 0.6%. And from the beginning of October 2019, until August 1, 2020, market prices predicted security allocation between Bitcoin and Litecoin with error of 0.45%. These results are further corroborated by our establishment of Granger-causality between change in market prices and change in security allocation. To demonstrate the practicality of our results, we describe a trustless oracle that leverages the equilibrium to estimate the price ratios of PoW cryptocurrencies from on-chain information only.
Cryptocurrency based on blockchain technology has gradually become a choice for people to invest in, and a large number of users have participated in the accumulation of massive transaction data. The complete transaction records recorded in the blockchain and the open characteristics of data provide researchers with opportunities to mine and analyze the data in the chain. Network modeling and analysis of cryptocurrency transaction records is a common method of blockchain data analysis. The analysis of attribute graphs can provide insight into various economic indicators, illegal activities, general internet security, and so on. This article aims to summarize and analyze the literature on cryptocurrency transaction data from the perspective of complex networks. To provide systematic guidance for researchers, we put forward a blockchain data analysis framework based on introducing the relevant background and reviewed the work from five aspects: the blockchain data model, data acquisition on the chain, existing analysis tools, available insights, and common analysis methods. For each aspect, we introduce the research problems, summarize the methods, and discuss the results and findings. Finally, we present future research concepts and several open questions in this field.
Interest in cryptocurrencies has skyrocketed since their introduction a decade ago, with hundreds of billions of dollars now invested across a landscape of thousands of different cryptocurrencies. While there is significant diversity, there is also a significant number of scams as people seek to exploit the current popularity. In this paper, we seek to identify the extent of innovation in the cryptocurrency landscape using the open-source repositories associated with each one. Among other findings, we observe that while many cryptocurrencies are largely unchanged copies of Bitcoin, the use of Ethereum as a platform has enabled the deployment of cryptocurrencies with more diverse functionalities.
Bitcoin is a purely online virtual currency, unbacked by either physical commodities or sovereign obligation; instead, it relies on a combination of cryptographic protection and a peer-to-peer protocol for witnessing settlements. Consequently, Bitcoin has the unintuitive property that while the ownership of money is implicitly anonymous, its flow is globally visible. In this paper we explore this unique characteristic further, using heuristic clustering to group Bitcoin wallets based on evidence of shared authority, and then using re-identification attacks (i.e., empirical purchasing of goods and services) to classify the operators of those clusters. From this analysis, we consider the challenges for those seeking to use Bitcoin for criminal or fraudulent purposes at scale.
Bitcoin is a purely online virtual currency, unbacked by either physical commodities or sovereign obligation; instead, it relies on a combination of cryptographic protection and a peer-to-peer protocol for witnessing settlements. Consequently, Bitcoin has the unintuitive property that while the ownership of money is implicitly anonymous, its flow is globally visible. In this paper we explore this unique characteristic further, using heuristic clustering to group Bitcoin wallets based on evidence of shared authority, and then using re-identification attacks (i.e., empirical purchasing of goods and services) to classify the operators of those clusters. From this analysis, we characterize longitudinal changes in the Bitcoin market, the stresses these changes are placing on the system, and the challenges for those seeking to use Bitcoin for criminal or fraudulent purposes at scale.
The Bitcoin cryptocurrency records its transactions in a public log called the blockchain. Its security rests critically on the distributed protocol that maintains the blockchain, run by participants called miners. Conventional wisdom asserts that the mining protocol is incentive-compatible and secure against colluding minority groups, that is, it incentivizes miners to follow the protocol as prescribed.
We show that the Bitcoin mining protocol is not incentive-compatible. We present an attack with which colluding miners obtain a revenue larger than their fair share. This attack can have significant consequences for Bitcoin: Rational miners will prefer to join the selfish miners, and the colluding group will increase in size until it becomes a majority. At this point, the Bitcoin system ceases to be a decentralized currency.
Unless certain assumptions are made, selfish mining may be feasible for any group size of colluding miners. We propose a practical modification to the Bitcoin protocol that protects Bitcoin in the general case. It prohibits selfish mining by pools that command less than \(1/4\) of the resources. This threshold is lower than the wrongly assumed \(1/2\) bound, but better than the current reality where a group of any size can compromise the system.
We study the strategic considerations of miners participating in the bitcoin's protocol. We formulate and study the stochastic game that underlies these strategic considerations. The miners collectively build a tree of blocks, and they are paid when they create a node (mine a block) which will end up in the path of the tree that is adopted by all. Since the miners can hide newly mined nodes, they play a game with incomplete information. Here we consider two simplified forms of this game in which the miners have complete information. In the simplest game the miners release every mined block immediately, but are strategic on which blocks to mine. In the second more complicated game, when a block is mined it is announced immediately, but it may not be released so that other miners cannot continue mining from it. A miner not only decides which blocks to mine, but also when to release blocks to other miners. In both games, we show that when the computational power of each miner is relatively small, their best response matches the expected behavior of the bitcoin designer. However, when the computational power of a miner is large, he deviates from the expected behavior, and other Nash equilibria arise.
This survey appears in extension of a previous exploratory survey (Bouraoui, 2008) dedicated to the impact of stock spams on volumes. The interest of the present research is to study the impact on stock prices while taking into account the evolution of volatility over time through a GARCH modelling. We use the methodology of event studies on a sample of hundred ten firms of penny stocks over the period from February 2006 to June 2008. Our results show that sending stock spams has generated significant variations and positive returns during the first three days of the event. Field of research: Financial markets, Equities, Financial econometric
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.