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.
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.
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 fĂźr solch eine Aufgabe verwendet werden. Die Entscheidung Ăźber die Anzahl der Indexteilnehmer wird mithilfe des AIC und BIC Kriteriums getroffen und die Liquiditätsregel wird auf Grundlage der BIS Umfrage ermittelt. Dieser neu entwickelte Index, CRIX, wird dann benutzt, um den Kryptowährungsmarkt gegen Bitcoins und andere Märkte zu vergleichen. Es wurde herausgefunden, dass dieser Markt wesentlich risikoreicher ist als andere Märkte. Es wird auĂerdem ein Minimum Varianz CRIX und ein optimales Vorhersagemodel fĂźr 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.
Augur is a trustless, decentralized platform for prediction markets. It is an extension of Bitcoin Core's source code which preserves as much of Bitcoin's proven code and security as possible. Each feature required for prediction markets is constructed from Bitcoin's input/output-style transactions.
There is yet any official guidance on the financial reporting of Bitcoin transaction from the standard setters as the crypto-currency become increasingly popular and tax accounting guidance begin to appear in 2014. Designed as a decentralized currency, Bitcoin will not become a reporting currency and will instead complement fiat money. We argue that the accounting principle of faithful representation requires interpreting the economic substance for financial reporting that varies with reporting entity: trading firms recognize Bitcoin like a foreign currency and measure the revenue, or expense, at the equivalent amount of the reporting currency; digital currency exchanges recognize Bitcoin as goods in line with tax accounting treatment. An Economica paper by Radford (1945) describing cigarette being used as commodity money in a POW camp has alluded to this economic basis. This paper applies accounting principle to a practical issue and contributes to the thinking process which may help standard setter issue an interpretation.
In this paper, we concern ourselves with cryptocurrency and how cryptocurrency affects the cryptocurrency market as well as the fiat currency market. The whole topic will be sepreted into two sections: competition among different currencies, as well as competition among exchanges[2]. We aim at figuring out the current circumstance of cryptocurrency which as a casual visitor in the market, and additionaly we will also look at the prospect of cryptocurrency and the currency market. Cryptocurrency with many new features has an uneasy development after entering into the financial market, although it is not yet powerful to compete with fiat currency, the effects of cryptocurrency and cryptocurrency exchange in financial market will still be full of meaning.
Bit coin, as the foundation for a secure electronic payment system, has drawn broad interests from researchers in recent years. In this paper, we analyze a comprehensive Bit coin transaction dataset and investigate the interrelationship between the flow of Bit coin transactions and its price movement. Using network theory, we examine a few complexity measures of the Bit coin transaction flow networks, and we model the joint dynamic relationship between these complexity measures and Bit coin market variables such as return and volatility. We find that a particular complexity measure of the Bit coin transaction network flow is significantly correlated with the Bit coin market return and volatility. More specifically we document that the residual diversity or freedom of Bit coin network flow scaled by the total system throughput can significantly improve the predictability of Bit coin market return and volatility.