The Bitcoin phenomenon—and the technological innovation that made it possible—is interesting, but for investors large and small, the more pertinent question is whether they should buy the digital currency or avoid it. Using both in-sample and out-of-sample settings, we analyze a Bitcoin investment from the standpoint of an investor with a diversified portfolio. Within the in-sample setting, Bitcoin does not yield added value to investors, with a utility function consistent with the mean-variance setting. On the other hand, Bitcoin does offer diversification benefits to investors with negative exponential and power utility functions. However, these benefits are not preserved in the out-of-sample framework. In most cases, the optimal portfolios that include only the traditional asset classes appear to have superior performance. <b>TOPICS:</b>Currency, portfolio construction, performance measurement
Florian Glaser, Martin Haferkorn, Moritz Weber, Kai Zimmermann
Digital currencies are gaining more and more attention against the backdrop of recent events triggered by the ongoing economic crisis. While digital currencies face increasing popularity, the currencies' prices are free floating and subject to high volatility as a result of lacking fundamental valuation methods. On the basis of an overview over the most prominent currency -- Bitcoin -- and an economic literature review we propose an econometric model that incorporates the basic components of the current price discovery process of a digital currency's exchange rate. On the basis of our empirical validation we further show that, in the case of Bitcoin, price volatility is significantly influenced by the media coverage and positive sentiment.
OBJECTIVES OF THE STUDY:\n\nThis thesis has three objectives. First, the past development of monetary systems is studied to see how Bitcoin is positioned as the forerunner of a new category. Second, the attitudes and expecta-tions of Finnish stakeholders are studied to recognize the general perception and future outlook for Bitcoin. Third, bitcoins are examined as an investment instrument by studying price drivers and the degree of predictability of future returns.\n\nDATA AND METHODOLOGY:\n\nThe qualitative methods are based on a literature review and an interview study conducted with Finnish stakeholders from different financial institutions and Bitcoin start-ups. The quantitative methods consist of market sizing calculations, a regression analysis, and Granger tests. The regres-sions utilize novel variables network hashrate, network transactions, and bitcoin supply as explan-atory variables for bitcoin price. Also bitcoin price and Google Trends SVI are used as explanatory variables. The market sizing calculations are based on M2 monetary aggregates for USD, EUR, and JPY.\n\nFINDINGS OF THE STUDY:\n\nThe thesis develops a categorization for decentralized cpytocurrencies that takes into account the main developments of the past monetary systems. The interview study reveals optimism for the technology behind Bitcoin and other decentralized systems, while all interviewees accept the un-certainty of Bitcoin survival. The stakeholders perceive the main challenges of Bitcoin to be tech-nological weaknesses, trust, and reputational issues. In terms of market sizing, it is clear that Bitcoin is not currently a serious threat to fiat currencies. Price driver analysis revealed a momen-tum effect in price returns, as well as an inflationary effect caused by the increasing supply. Also the network hashrate was found to forecast future bitcoin returns. The results from the Granger tests challenge the causality assumed in the regressions.
The present study addresses one of the most problematic phenomena: Bitcoin price. We explore the Granger causality for two relationships (Bitcoin price and transactions; Bitcoin price and investors’ attractiveness) from a frequency domain perspective using Breitung and Candelon’s (2006) approach. Intuitively, this research gauges empirically the causal links between these variables unconditionally on the one hand and conditionally to the Chinese stock market and the processing power of Bitcoin network on the other hand. The observed outcomes reveal some differences with respect to the frequencies involved, highlighting the complexity of assessing what Bitcoin looks like and the difficulty to gain clearer insights 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 neglecting its usefulness in economic reasons (trade transactions). The consideration of the Chinese market index and the hash rate has led to solid and unambiguous findings connecting further Bitcoin to speculation.
This working paper presents a simple model for the macroeconomic behavior of bitcoin based on the economic equation of exchange. According to this model, the value of bitcoin is determined largely by the willingness of bitcoin holders to save bitcoin and not by its transactional use. This model therefore predicts that increased use of bitcoin will not cause its value to rise, but that the value of bitcoin in terms of fiat currency will be almost solely determined by the willingness of bitcoin holders to pull bitcoin out of circulation. This model suggests that bitcoin will not fall victim to a liquidity trap as suggested by some economists.
This paper discusses the potential and limitations of Bitcoin as a digital currency. Bitcoin as a digital asset has been extensively discussed from the viewpoints of engineering and security design. But there are few economic analyses of Bitcoin as a currency. Bitcoin was designed as a payments vehicle and as a store of value (or speculation). It has no use bar as money or currency. Despite recent enthusiasm for Bitcoin, it seems very unlikely that currencies provided by central banks are at risk of being replaced, primarily because of the market price instability of Bitcoin (i.e. the exchange rate against the major currencies). We diagnose the instability of market price of Bitcoin as being a symptom of the lack of flexibility in the Bitcoin supply schedule ‐ a predetermined algorithm in which the proof of work is the major driving force. This paper explores the problem of instability from the viewpoint of economics and suggests a new monetary policy rule (i.e. monetary policy without a central bank) for stabilizing the values of Bitcoin and other cryptocurrencies.
Bitcoins are digital gold. They are a purely electronic commodity traded for speculative purposes as well as in exchange for goods and services. Just like physical gold, the relative price of bitcoins denominated in different currencies implies a nominal exchange rate. This is a departure from previous literature which treats bitcoin prices themselves as nominal exchange rates. I argue that treating prices as exchange rates is inappropriate as one would not consider the price of physical gold to be an exchange rate. Therefore, this paper characterizes the behavior of nominal exchange rates implied by relative bitcoin prices. I show that the implied nominal exchange rate is highly cointegrated with the nominal exchange rate determined in conventional foreign currency exchange markets. I also show that the direction of causality flows from the conventional markets to the bitcoin market and not vice-versa which can explain much of the volatility in bitcoin prices.
We present a thorough empirical analysis of market impact on the Bitcoin/USD exchange market using a complete dataset that allows us to reconstruct more than one million metaorders. We empirically confirm the "square-root law'' for market impact, which holds on four decades in spite of the quasi-absence of statistical arbitrage and market marking strategies. We show that the square-root impact holds during the whole trajectory of a metaorder and not only for the final execution price. We also attempt to decompose the order flow into an "informed'' and "uninformed'' component, the latter leading to an almost complete long-term decay of impact. This study sheds light on the hypotheses and predictions of several market impact models recently proposed in the literature and promotes heterogeneous agent models as promising candidates to explain price impact on the Bitcoin market -- and, we believe, on other markets as well.
This paper overviews the entire landscape of Bitcoin-like cryptocurrencies. Bitcoin has not emerged out of cryptocurrency competition, but rather became a dominant currency as the first broad market based cryptocurrency. But there are more than a hundred of cryptocurrencies in the market, and some are catching up to Bitcoin. This is a healthy sign of currency competition á la Hayek. Through this competition new technological and security innovations may emerge. In this paper, we point out potential problems with Bitcoin and propose some ideas for an alternative cryptocurrency.
We analyze how network effects affect competition in the nascent cryptocurrency market. We do so by examining the changes over time in exchange rate data among cryptocurrencies. Specifically, we look at two aspects: (1) competition among different currencies, and (2) competition among exchanges where those currencies are traded. Our data suggest that the winner-take-all effect is dominant early in the market. During this period, when Bitcoin becomes more valuable against the U.S. dollar, it also becomes more valuable against other cryptocurrencies. This trend is reversed in the later period. The data in the later period are consistent with the use of cryptocurrencies as financial assets (popularized by Bitcoin), and not consistent with "winner-take-all" dynamics.
Cryptocurrencies like Biteoin are transferable digital assets, secured by cryptography. To date, all of them have been created by private individuals, organizations, or firms. Unlike bank account balances, they are not anyone's liability. They are not redeemable for any government fiat money such as Federal Reserve Notes or for any commodity money such as silver or gold coins. The cryptocurrency is thus a of competing private irredeemable monies (or would-be monies). Friedrich A. Hayek (1978a) and other economists over the last 40 years could only imagine how competition among issuers of private irredeemable monies would work. Today we have an actual study. In what follows I will discuss the main economic features of the market. I also discuss whether the is purely a bubble. As an introduction the topic, I offer the following comic verse about the contrast between Biteoin and the physical gold coins of the past: In the past, money's value was judged with our teeth; We bit coins confirm they were real. Now a Bitcoin's just data, no gold underneath. That's okay if it buys you a meal. (1) The Size and Composition of the Cryptocurrency Market Bitcoin rightly gets the lion's share of media attention, but it is not alone in the for cryptocurrencies. The authoritative website CoinMarketCap.com tracks the U.S. dollar price and total market (price per unit multiplied by number of units outstanding) for each of more than 500 traded cryptocurrencies. Bitcoin is the largest by far. On a recent day (March 9, 2015), the site showed Bitcoin trading at $291 per unit, with a cap of $4.05 billion. The second and third largest cryptocurrencies, Ripple and Litecoin, had caps respectively 8.5 percent and 1.8 percent as large. The entire set of non-Bitcoin cryptocurrencies (known as altcoins) had a cap of roughly $619 million, or 15 percent of Bitcoin's. Stated differently, Bitcoin had roughly 87 percent of the market, altcoins 13 percent. In percentage terms, altcoins do a higher share of Bitcoin's business than Bitcoin does of the Federal Reserve Note's business (currently $1.35 trillion in circulation). In trading volume the percentage share of altcoins (led by litecoin and Ripple) has been similar. The cryptocurrency has grown about fourfold in cap over the last 22 months, with altcoins growing faster than Bitcoin. This is seen by comparing recent data the oldest snapshot of the CoinMarketCap site available via the Internet Archive Wayback Machine, which reports data for May 9, 2013. On that date, Bitcoin had a price of $112 per unit, and a cap of $1.2 billion. The two largest altcoins at that time, Litecoin and Peercoin (aka PPCoin), had caps respectively 4.7 percent and 0.4 percent as large. Only 13 altcoins were listed. Jointly their cap was about 6 percent of Bitcoin's, giving Bitcoin 95 percent of the market. Since then, the share of altcoins has doubled, and their cap has grown ninefold. Trading volumes then were not reported. At $4.05 billion, the cap of Bitcoin, as of March 2015, was slightly smaller than the dollar value of the September 2014 monetary bases of the Lithuanian litas ($5.8 billion) and the Guatemalan quetzal ($5.5 billion), but larger than those of the Costa Rican colon ($3.3 billion) and the Serbia dinar ($3.3 billion). (2) The August 2014 figures from the Central Bank of the Bahamas do not provide the monetary base, but count Bahamian dollar currency in circulation at $210 million, less than two-thirds of Ripple's recent cap of around $344 million. Medium of Exchange, Store of Value, and Medium of Remittance Functions The retail use of Bitcoin as a medium of exchange for goods and services is small date, but is growing. In December 2014, Microsoft began accepting bitcoin payments to buy content such as games and videos on Xbox game consoles, add apps and services Windows phones or buy Microsoft software (BBC 2014). …
We study the economics of Bitcoin transaction fees in a simple static partial equilibrium model with the specificity that the system security is directly linked to the total computational power of miners. We show that any situation with a fixed fee is equivalent to another situation with a limited block size. In both cases, we give the optimal value of the transaction fee or of the block size. We also show that making the block size a non binding constraint and, in the same time, letting the fee be fixed as the outcome of a decentralized competitive market cannot guarantee the very existence of Bitcoin in the long-term.
Florian Glaser, Kai Zimmermann, Martin Haferkorn, Moritz Weber · 5 authors
Digital currencies are a globally spreading phenomenon that is frequntly and also prominently addressed by media, venture capitalists, financial and governmental institutions alike. As exchange prices for Bitcoin have reached multiple peaks within 2013, we pose a prevailing and yet academically unaddressed qustion: What are users' intentions when changing their domestic into a digital currency? In particular, this paper aims at giving empirical insights on whether users´ interest regarding digital currencies is driven by its appeal as an asset or as a currency. Based on our evaluation, we find strong indications that especially uninformed users approaching digital currencies are not primarily interested in an alternative transaction system but seek to participate in an alternative investment vehicle.
Bitcoin is a digital currency that was launched in 2009, and it has attracted much attention recently. This article reviews the mechanics of the currency and offers some thoughts on its characteristics.
Dániel Kondor, Márton Pósfai, István Csabai, Gábor Vattay
The possibility to analyze everyday monetary transactions is limited by the scarcity of available data, as this kind of information is usually considered highly sensitive. Present econophysics models are usually employed on presumed random networks of interacting agents, and only macroscopic properties (e.g. the resulting wealth distribution) are compared to real-world data. In this paper, we analyze BitCoin, which is a novel digital currency system, where the complete list of transactions is publicly available. Using this dataset, we reconstruct the network of transactions, and extract the time and amount of each payment. We analyze the structure of the transaction network by measuring network characteristics over time, such as the degree distribution, degree correlations and clustering. We find that linear preferential attachment drives the growth of the network. We also study the dynamics taking place on the transaction network, i.e. the flow of money. We measure temporal patterns and the wealth accumulation. Investigating the microscopic statistics of money movement, we find that sublinear preferential attachment governs the evolution of the wealth distribution. We report a scaling relation between the degree and wealth associated to individual nodes.
Cryptocurrencies are digital alternatives to traditional government‐issued paper monies. Given the current state of technology and skepticism regarding the future purchasing power of existing monies, why have cryptocurrencies failed to gain widespread acceptance? I offer an explanation based on network effects and switching costs. In order to articulate the problem that agents considering cryptocurrencies face, I employ a simple model developed by Dowd and Greenaway (1993) (Dowd, K., and D. Greenaway. “Currency Competition, Network Externalities, and Switching Costs: Towards an Alternative View of Optimum Currency Areas.” The Economic Journal , 103(420), 1993, 1180–89). The model demonstrates that agents may fail to adopt an alternative currency when network effects and switching costs are present, even if all agents agree that the prevailing currency is inferior. The limited success of bitcoin—almost certainly the most popular cryptocurrency to date—serves to illustrate. After briefly surveying episodes of successful monetary transition, I conclude that cryptocurrencies like bitcoin are unlikely to generate widespread acceptance in the absence of either significant monetary instability or government support. ( JEL E40, E41, E42, E49)
This paper analyses 26 time series that measure daily data for different attributes of the Bitcoin network and studies how the virtual currency behaves compared to a basket of currencies containing the Brazil Real (BRL), the Chinese Yuan (CNY), the Euro (EUR), and the Japan Yen (JPY) against the US Dollar (USD). \nBasic statistics about the time series have been taken and stationarity has been studied in order to build sterilized fact data and meaningful cointegrations have been found among them. By applying a Vector Autoregressive (VAR) model, a regression has been built among the currencies and the Granger causality test has been applied in order to determine whether one time series (of a given currency) is useful in forecasting another and to observe causal relationships among the currencies studied.
Abstract. The Bitcoin scheme is a rare example of a large scale global payment system in which all the transactions are publicly accessible (but in an anonymous way). We downloaded the full history of this scheme, and analyzed many statistical properties of its associated transaction graph. In this paper we answer for the first time a variety of interesting questions about the typical behavior of users, how they acquire and how they spend their bitcoins, the balance of bitcoins they keep in their accounts, and how they move bitcoins between their various accounts in order to better protect their privacy. In addition, we isolated all the large transactions in the system, and discovered that almost all of them are closely related to a single large transaction that took place in November 2010, even though the associated users apparently tried to hide this fact with many strange looking long chains and fork-merge structures in the transaction graph.