Abeer ElBahrawy, Laura Alessandretti, Anne Kandler, Romualdo PastorâSatorras · 5 authors
The cryptocurrency market surpassed the barrier of \$100 billion market capitalization in June 2017, after months of steady growth. Despite its increasing relevance in the financial world, however, a comprehensive analysis of the whole system is still lacking, as most studies have focused exclusively on the behaviour of one (Bitcoin) or few cryptocurrencies. Here, we consider the history of the entire market and analyse the behaviour of 1,469 cryptocurrencies introduced between April 2013 and June 2017. We reveal that, while new cryptocurrencies appear and disappear continuously and their market capitalization is increasing (super-)exponentially, several statistical properties of the market have been stable for years. These include the number of active cryptocurrencies, the market share distribution and the turnover of cryptocurrencies. Adopting an ecological perspective, we show that the so-called neutral model of evolution is able to reproduce a number of key empirical observations, despite its simplicity and the assumption of no selective advantage of one cryptocurrency over another. Our results shed light on the properties of the cryptocurrency market and establish a first formal link between ecological modelling and the study of this growing system. We anticipate they will spark further research in this direction.
In recent years a new type of tradable assets appeared, generically known as cryptocurrencies. Among them, the most widespread is Bitcoin. Given its novelty, this paper investigates some statistical properties of the Bitcoin market. This study compares Bitcoin and standard currencies dynamics and focuses on the analysis of returns at different time scales. We test the presence of long memory in return time series from 2011 to 2017, using transaction data from one Bitcoin platform. We compute the Hurst exponent by means of the Detrended Fluctuation Analysis method, using a sliding window in order to measure long range dependence. We detect that Hurst exponents changes significantly during the first years of existence of Bitcoin, tending to stabilize in recent times. Additionally, multiscale analysis shows a similar behavior of the Hurst exponent, implying a self-similar process.
Bitcoin is attracting a steadily increasing interest since its first appearance in 2008. Bitcoin price forecasting would be of great practical interest given its role as a relatively new virtual âcurrencyâ. This presupposes the modeling and verification of some kind of relation, causal or not, connecting bitcoin price to other âestablishedâ factors of economic interest. Towards this goal, cross-correlation analysis is used in this work to investigate relations between bitcoin price and a set of other factors of economic interest. The years 2013 to 2015 are selected as the temporal basis of this research, because earlier bitcoin prices were practically zero. Results reveal a strong correlation between bitcoin and stock market indices or other economical factor values. SWOT analysis for bitcoin is carried out for the same period of time, based on cross-correlation as well as on existing research results. Bitcoin is seen to possess more benefits than risks, while its strong temporal correlations with other economic indices or prices constitute an opportunity to be further explored towards the goal of bitcoin price forecasting.
We provide an extreme value analysis of the returns of Bitcoin. A particular focus is on the tail risk characteristics and we will provide an in-depth univariate extreme value analysis. Those properties will be compared to the traditional exchange rates of the G10 currencies versus the US dollar. For investors, especially institutional ones, an understanding of the risk characteristics is of utmost importance. So for Bitcoin to become a mainstream investable asset class, studying these properties is necessary. Our findings show that the bitcoin return distribution not only exhibits higher volatility than traditional G10 currencies, but also stronger non-normal characteristics and heavier tails. This has implications for risk management, financial engineering (such as bitcoin derivatives) â both from an investor's as well as from a regulator's point of view. To our knowledge, this is the first detailed study looking at the extreme value behavior of the cryptocurrency Bitcoin.
Cryptocurrencies have become increasingly popular since the introduction of bitcoin in 2009. In this paper, we identify factors associated with variations in cryptocurrencies' market values. In the past, researchers argued that the "buzz" surrounding cryptocurrencies in online media explained their price variations. But this observation obfuscates the notion that cryptocurrencies, unlike fiat currencies, are technologies entailing a true innovation potential. By using, for the first time, a unique measure of innovation potential, we find that the latter is in fact the most important factor associated with increases in cryptocurrency returns. By contrast, we find that the buzz surrounding cryptocurrencies is negatively associated with returns after controlling for a variety of factors, such as supply growth and liquidity. Also interesting is our finding that a cryptocurrency's association with fraudulent activity is not negatively associated with weekly returns-a result that further qualifies the media's influence on cryptocurrencies. Finally, we find that an increase in supply is positively associated with weekly returns. Taken together, our findings show that cryptocurrencies do not behave like traditional currencies or commodities-unlike what most prior research has assumed-and depict an industry that is much more mature, and much less speculative, than has been implied by previous accounts.
This thesis is a descriptive statistical analysis of cryptocurrency market and its relation within cryptocurrencies and across asset classes, using correlation functions, orthogonalized impulse response functions and OLS regressions. Consistent with Wang (2014), bitcoin does not suffer from a liquidity trap, even though bitcoin is a decentralized system. This thesis concludes that bitcoin has a lead effect on only 2 out of 8 of the top cryptocurrencies, endowing diversification benefits within cryptocurrency market. This paper provides evidence on cryptocurrency marketâs and US equity marketâs impulse response dynamics which are insignificant, consistent with Gangwalâs (2016) results that adding cryptocurrencies to a diversified portfolio will yield to a higher Sharpe ratio. Lastly, the study reports bitcoin momentum factor having an impact on banking and financial industriesâ excess returns.
This research project investigated the reasons for price fluctuations of cryptocurrencies. Cryptocurrencies are digital currencies that are created over a decentralised, secure network built on the blockchain technology. The current challenges with understanding price fluctuations are that there is limited research in the field and extreme volatility in the environment. \nExploratory research was conducted using semi-structured interviews to understand and analyse the drivers of factors identified in the literature contributing to price fluctuations of cryptocurrencies. Insights were generated for the drivers of user perception, misconceptions that surround cryptocurrency security and the role of regulators in the cryptocurrency space. The research expanded the existing literature and offered propositions for future research that contribute to the theory surrounding price fluctuations of cryptocurrencies. \nThe findings should provoke business and management to reshape the way that cryptocurrencies are received and positioned in the marketplace. In addition, these findings are significant for those making business or social decisions regarding cryptocurrencies or those that are redefining traditional currency transactions.
The rapid advancement in encryption and network computing gave birth to new tools and products that have influenced the local and global economy alike. One recent and notable example is the emergence of virtual currencies, also known as cryptocurrencies or digital currencies. Virtual currencies, such as Bitcoin, introduced a fundamental transformation that affected the way goods, services, and assets are exchanged. As a result of its distributed ledgers based on blockchain, cryptocurrencies not only offer some unique advantages to the economy, investors, and consumers, but also pose considerable risks to users and challenges for regulators when fitting the new technology into the old legal framework. This paper attempts to model the volatility of bitcoin using 5 variants of the GARCH model namely: GARCH(1,1), EGARCH(1,1) IGARCH(1,1) TGARCH(1,1) and GJR-GARCH(1,1). Once the best model is selected, an OLS regression was ran on the volatility series to measure the day of the week the effect. The results indicate that the TGARCH (1,1) model best fits the volatility price for the data. Moreover, Sunday appears as the most significant day in the week. A nontechnical discussion of several aspects and features of virtual currencies and a glimpse at what the future may hold for these decentralized currencies is also presented.
Bitcoin is a peer to peer (p2p) payment cash system and an unregulated digital currency that is primarily designed and developed in 2008 without tender legal status. Bitcoin is so-called cryptocurrency because it uses the cryptographic function in order to secure the creation and transfer of money. During recent years, Bitcoin has been emerging as the well-known electronic currency and gaining popularity worldwide as well as caught the media attention in the area of volume trading. Therefore, Bitcoin will be a potential financial asset for investors due to its extraordinary returns. The purpose of this research is to find out how Bitcoin returns correlate with stock markets and to assess the risk that the electronic currency bears, to conclude whether Bitcoin is a favourable instrument for investors that want to diversify their portfolios. Therefore, daily data from 2013 to 2017 is used to measure correlations with major global stock markets and analyse in a regression to what extend Bitcoin is integrated into financial systems. In addition, Bitcoinâs risk has been measured by estimating value at risk, as well as the volatility and a regression analysis with explanatory variables has been performed to identify the driving factors of the unusually high volatility. Finally, the researchers constructed models to forecast expected returns to identify whether Bitcoin is rather a short or long term instrument. The researchers came to the conclusion that Bitcoin is a favourable instrument to diversify a portfolio as it correlates negatively with most of the analysed stock market indices and the research result showed that Bitcoin is not yet integrated into financial systems. It has however been paid attention to the new types of risk and the questionable image the electronic currency has as it is often used to support criminal activities. The fact that no authority, clearing house or central bank's involvement is present, creates uncertainty for many investors.
Since the creation of Bitcoin in 2009, hundreds of cryptocurrencies have emerged, thus becoming a common fixture of financial news bulletins. With a market capitalization of the five highest-valued cryptocurrencies exceeding $140 billion at the time of writing, these alternative currencies have caught the attention of both financial institutions and central banks with their innovative technological foundations and their potential to disrupt current financial institutional structures. We provide a non-technical overview of the concept and current market structure of cryptocurrencies for researchers in economics, finance, mathematics and computer science.