Can competition among privately issued fiat currencies such as Bitcoin or Ethereum work? Only sometimes. To show this, we build a model of competition among privately issued fiat currencies. We modify the current workhorse of monetary economics, the Lagos-Wright environment, by including entrepreneurs who can issue their own fiat currencies in order to maximize their utility. Otherwise, the model is standard. We show that there exists an equilibrium in which price stability is consistent with competing private monies, but also that there exists a continuum of equilibrium trajectories with the property that the value of private currencies monotonically converges to zero. These latter equilibria disappear, however, when we introduce productive capital. We also investigate the properties of hybrid monetary arrangements with private and government monies, of automata issuing money, and the role of network effects.
In this paper we propose to use the Grand Canonical Minority Game (GCMG, a highly simplified financial market model) as a model of bitcoin market to show how the lack of an income for âminersâ, similar to yield earned by bond holders, could be a structural reason for high volatility of bitcoin price in a reference currency. Coherently with present analysis, the introduction of future contracts on bitcoin would have the effect of reducing the overall market volatility.
Cryptocurrencies became popular with the emergence of Bitcoin and have shown an unprecedented growth over the last few years. As of November 2016, more than 720 cryptocurrencies exist, with Bitcoin still being the most popular one. We show the statistical properties of the most important cryptocurrencies. We characterize their exchange rates versus the US Dollar by fitting parametric distributions to them, including the Student t distribution, the generalized hyperbolic distribution as well as the asymmetric normal inverse Gaussian and the asymmetric variance gamma distribution. Our findings show that cryptocurrencies exhibit strong non-normal characteristics, with standard heavy-tailed distributions such as the Student t distribution giving good descriptions of the data. This is the first study that looks at the parametric distribution of cryptocurreny returns. The results are important for investment and risk management purposes.
We study the macroeconomic consequences of issuing central bank digital currency (CBDC) â a universally accessible and interest-bearing central bank liability, implemented via distributed ledgers, that competes with bank deposits as medium of exchange. In a DSGE model calibrated to match the pre-crisis United States, we find that CBDC issuance of 30% of GDP, against government bonds, could permanently raise GDP by as much as 3%, due to reductions in real interest rates, distortionary taxes, and monetary transaction costs. Countercyclical CBDC price or quantity rules, as a second monetary policy instrument, could substantially improve the central bankâs ability to stabilise the business cycle.
Abstract A multidimensional financial system could provide benefits for individuals, companies, and states. Instead of top-down control, which is destined to eventually fail in a hyperconnected world, a bottom-up creation of value can unleash creative potential and drive innovations. Multiple currency dimensions can represent different externalities and thus enable the design of incentives and feedback mechanisms that foster the ability of complex dynamical systems to self-organize and lead to a more resilient society and sustainable economy. Modern information and communication technologies play a crucial role in this process, as Web 2.0 and online social networks promote cooperation and collaboration on unprecedented scales. Within this contribution, we discuss how one dimension of a multidimensional currency system could represent socio-digital capital (Social Bitcoins) that can be generated in a bottom-up way by individuals who perform search and navigation tasks in a future version of the digital world. The incentive to mine Social Bitcoins could sustain digital diversity, which mitigates the risk of totalitarian control by powerful monopolies of information and can create new business opportunities needed in times where a large fraction of current jobs is estimated to disappear due to computerization.
Cryptocurrencies became popular with the emergence of Bitcoin and have shown an unprecedented growth over the last few years. As of November 2016, more than 720 cryptocurrencies exist, with Bitcoin still being the most popular one. We provide both a statistical analysis as well as an extreme value analysis of the returns of the most important cryptocurrencies. A particular focus is on the tail risk characteristics and we will provide an in-depth univariate and multivariate extreme value analysis. The tail dependence of cryptocurrencies is investigated (using both empirical and Gaussian copulas). For investorsâespecially institutional onesâas well as regulators, an understanding of the risk and tail characteristics are of utmost importance. For cryptocurrencies to become a mainstream investable asset class, studying these properties is necessary. Our findings show that cryptocurrencies exhibit strong non-normal characteristics, large tail dependencies, depending on the particular cryptocurrencies and heavy tails. Statistical similarities can be observed for cryptocurrencies that share the same underlying technology. This has implications for risk management, financial engineering (such as derivatives on cryptocurrencies)âboth from an investorâs as well as from a regulatorâs point of view. To our knowledge, this is the first detailed study looking at the extreme value behaviour of cryptocurrencies, their correlations and tail dependencies as well as their statistical properties.
Bitcoin is defined as digital money within a decentralized peer-to-peer payment network. It is a hybrid between fiat currency and commodity currency without intrinsic value and independent of any government or monetary authority. This paper analyses the question of whether bitcoin is a currency or an asset and, more specifically, what is its current usage and what usage will prevail in the future, given its characteristics? We analyse the statistical properties of bitcoin and find that it is essentially uncorrelated with traditional asset classes such as stocks, bonds and commodities, both in normal times and in periods of financial turmoil. The analysis of transaction data of bitcoin accounts shows that bitcoins are mainly used as a speculative investment and not as an alternative currency and medium of exchange. Bitcoin is still small relative to the size of other asset classes and, thus, does not pose an immediate risk for monetary, financial or economic stability.
Giuseppe Di Battista, Valentino Di Donato, Maurizio Patrignani, Maurizio Pizzonia · 6 authors
Bitcoin is a digital currency whose transactions are stored into a public ledger, called blockchain, that can be viewed as a directed graph with more than 70 million nodes, where each node represents a transaction and each edge represents Bitcoins flowing from one transaction to another one. We describe a system for the visual analysis of how and when a flow of Bitcoins mixes with other flows in the transaction graph. Such a system relies on high-level metaphors for the representation of the graph and the size and characteristics of transactions, allowing for high level analysis of big portions of it.
More and more companies start offering digital payment systems. Smartphones evolve to a digital wallet such that it seems like we are about to enter the era of digital finance. In fact we are already inside an digital economy. The market of e-x (x = "finance", "money", "book", you name it . . . ) has not only picked up enormous momentum but has become standard for driving innovative activities of the global economy. A few clicks at y and payment at z brings our purchase to location w. Own currencies for the digital market were therefore just a matter of time. The idea of the Nobel Laureate Hayek, see [1], to let companies offer concurrent currencies seemed for a long time scarcely probabilistic, but the invention of the Blockchain made it possible to fill his vision with life. Cryptocurrencies (abbr. cryptos) came up and widened the angle towards this new level of economic interaction. Since bitcoinsâ appearance a bunch of new cryptos spread the web and offered new ways of proliferation. The crypto market then fanned out and showed clear signs of acceptance and deep liquidity so that one has to look closer at the general moves and dynamics.
This paper sets out to explore the hedging capabilities of bitcoin by applying the asymmetric GARCH methodology used in investigation of gold. The results show that bitcoin can clearly be used as a hedge against stocks in the Financial Times Stock Exchange Index. Additionally bitcoin can be used as a hedge against the American dollar in the short-term. Bitcoin thereby possess some of the same hedging abilities as gold and can be included in the variety of tools available to market analysts to hedge market specific risk.
Pavel Ciaian, Miroslava RajÄĂĄniovĂĄ, dâArtis Kancs
Abstract This paper identifies and analyzes BitCoin features which may facilitate BitCoin to become a global currency, as well as characteristics which may impede the use of BitCoin as a medium of exchange, a unit of account and a store of value, and compares BitCoin with standard currencies with respect to the main functions of money. Among all analyzed BitCoin features, the extreme price volatility stands out most clearly compared to standard currencies. In order to understand the reasons for such extreme price volatility, we attempt to identify drivers of BitCoin price formation and estimate their importance econometrically. We apply time-series analytical mechanisms to daily data for the 2009â2014 period. Our estimation results suggest that BitCoin attractiveness indicators are the strongest drivers of BitCoin price followed by market forces. In contrast, macro-financial developments do not determine BitCoin price in the long-run. Our findings suggest that as long as BitCoin price will be mainly driven by speculative investments, BitCoin will not be able to compete with standard currencies.
Bitcoin, the first electronic payment system, is becoming a popular currency. We provide a statistical analysis of the log-returns of the exchange rate of Bitcoin versus the United States Dollar. Fifteen of the most popular parametric distributions in finance are fitted to the log-returns. The generalized hyperbolic distribution is shown to give the best fit. Predictions are given for future values of the exchange rate.
The availability of data on digital traces is growing to unprecedented sizes, but inferring actionable knowledge from large-scale data is far from being trivial. This is especially important for computational finance, where digital traces of human behavior offer a great potential to drive trading strategies. We contribute to this by providing a consistent approach that integrates various datasources in the design of algorithmic traders. This allows us to derive insights into the principles behind the profitability of our trading strategies. We illustrate our approach through the analysis of Bitcoin, a cryptocurrency known for its large price fluctuations. In our analysis, we include economic signals of volume and price of exchange for USD, adoption of the Bitcoin technology, and transaction volume of Bitcoin. We add social signals related to information search, word of mouth volume, emotional valence, and opinion polarization as expressed in tweets related to Bitcoin for more than 3 years. Our analysis reveals that increases in opinion polarization and exchange volume precede rising Bitcoin prices, and that emotional valence precedes opinion polarization and rising exchange volumes. We apply these insights to design algorithmic trading strategies for Bitcoin, reaching very high profits in less than a year. We verify this high profitability with robust statistical methods that take into account risk and trading costs, confirming the long-standing hypothesis that trading based social media sentiment has the potential to yield positive returns on investment.
The present study addresses one of the most problematic phenomena: Bitcoin price. We explore the Granger causality for two relationships (Bitcoin price and trade transactions; Bitcoin price and investors' attractiveness) from a frequency domain perspective-based on unconditional and conditional data analysis. Accurately, this research empirically assesses the causal links between these variables unconditionally on the one hand and conditioning upon relevant control variables (recorded in literature) on the other hand. The observed outcomes reveal some differences with respect to the frequencies involved, highlighting the difficulty to reach clearer insights and better paths into this nascent crypto-currency. Beyond the nuances of short-, medium- and long-run frequencies, this paper confirms the extremely speculative nature of Bitcoin without overlooking its usefulness in economic reasons. The consideration of the Chinese market index, the hash rate, the monetary velocity and the estimated output volume has led to solid and meaningful findings connecting further Bitcoin to speculation.
Digital currencies, such as Bitcoin, offer convenience and security to criminals operating in the black marketplace. Some Bitcoin marketplaces, such as Silk Road, even claim anonymity. This claim contradicts the findings in this work, where long term transactional behavior is used to identify and verify account holders. Transaction timestamps and network properties observed over time contribute to this finding. The timestamp of each transaction is the result of many factors: the desire purchase an item, daily schedule and activities, as well as hardware and network latency. Dynamic network properties of the transaction, such as coin flow and the number of edge outputs and inputs, contribute further to reveal account identity. In this paper, we propose a novel methodology for identifying and verifying Bitcoin users based on the observation of Bitcoin transactions over time. The behavior we attempt to quantify roughly occurs in the social band of Newell's time scale. A subset of the Blockchain 230686 is taken, selecting users that initiated between 100 and 1000 unique transactions per month for at least 6 different months. This dataset shows evidence of being nonrandom and nonlinear, thus a dynamical systems approach is taken. Classification and authentication accuracies are obtained under various representations of the monthly Bitcoin samples: outgoing transactions, as well as both outgoing and incoming transactions are considered, along with the timing and dynamic network properties of transaction sequences. The most appropriate representations of monthly Bitcoin samples are proposed. Results show an inherent lack of anonymity by exploiting patterns in long-term transactional behavior.
To examine whether the recent price patterns and transaction costs of Bitcoin represent a general characteristic of decentralized virtual currencies, we analyze virtual currencies in online games that have been voluntarily managed by individuals since 1990s. We find that matured game currencies have price stability similar to that of small size equities or gold, and their transaction costs are sometimes lower than real currencies. Assuming that virtual currencies with a longer history can provide an estimate for Bitcoin's prospects, we project that Bitcoin will be less influenced by speculative trades and become a low cost alternative to real currencies.
In dieser Thesis wird ein Marktindex konstruiert, wobei neu entwickelte Methoden fĂŒr solch eine Aufgabe verwendet werden. Die Entscheidung ĂŒber die Anzahl der Indexteilnehmer wird mithilfe des AIC und BIC Kriteriums getroffen und die LiquiditĂ€tsregel wird auf Grundlage der BIS Umfrage ermittelt. Dieser neu entwickelte Index, CRIX, wird dann benutzt, um den KryptowĂ€hrungsmarkt gegen Bitcoins und andere MĂ€rkte zu vergleichen. Es wurde herausgefunden, dass dieser Markt wesentlich risikoreicher ist als andere MĂ€rkte. Es wird auĂerdem ein Minimum Varianz CRIX und ein optimales Vorhersagemodel fĂŒr den Index entwickelt, wobei Daten aus sozialen Netzwerken verwendet werden.
Bitcoin extreme deflationary price instability has hampered its usability, making it impractical for spot transactions and unserviceable for deferred payments. Ametrano (2014) has proposed as Hayek Money a cryptocurrency price stability paradigm of elastic non-discretionary monetary policy. An implementation using a dual asset ledger for stable coins and seigniorage shares is presented here. A DeCentralized Reserve Bank (as Decentralized Autonomous Organization) is introduced as active market agent using bitcoin as reserve asset to preserve price parity. The socially inefficient over-investment of seigniorage revenues in transaction verification can be avoided using proof-of-payment.This schema frees coins from any speculative value, thus favoring money velocity and increasing the number of transactions. Seigniorage shares are effectively to be considered as a participation in a distributed central bank: as such the owners are entitled to seigniorage revenues in exchange for being subjected to the losses associated to coin price stability defense, obliged to validation task duties, and in charge of price index observation.