In this research, the returns of four cryptocurrencies (Bitcoin, Litecoin, Ripple and Ethereum) were analyzed in order to answer the following research question: βHow do the returns of Bitcoin and other altcoins behave over time, and what can we say about extreme values for losses and profits?β With respect to volatility, cryptocurrencies can still be considered extremely volatile. For Bitcoin, the least volatile of the four, we found an annual volatility of approximately 70% based on daily exchange rates. For Ethereum, the most volatile of all four, this percentage was closer to 130%. Also, several distributions were fitted on the returns. It is shown that the Generalized Hyperbolic Distribution is the best fit for all four cryptocurrencies, apart from the tails in some cases.<br/>The tails were investigated seperately by using Extreme Value Analysis and by looking into both empirical and theoretical risk quantities (the Value at Risk and Expected Shortfall). Bitcoin appears to be the least risky of all four cryptocurrencies, but also the least profitable, whereas Ripple appears to be the most risky and also the most profitable.<br/>Compared to previous research, Bitcoin has also become less risky, showing a less fat tail for the losses than before. For Litecoin and Ripple, the reverse is true, as they appear to have become riskier. For Ethereum, no comparisons could be made, as this is a relatively new cryptocurrency that has not been investigated much yet. When tested for Paretianity, the left tails of Litecoin and Ripple appear to Pareto distributed: the losses seem to exhibit heavy tail behavior. For the profits, the tails turned out to be even heavier and can therefore also be considered Paretian. These results were confirmed by Maximum to Sum ratio plots, indicating infinite third and fourth moments for the losses and profits of Litecoin and Ripple, but not for Bitcoin and Ethereum. The results have implications for investment and risk management purposes.
The aim of the paper is to fit a regression model which can be used commonly for the four important crypto currencies: Bitcoin, Litecoin, Ethereum and Ripple to predict the prices. The data has information over the past six years regarding price, transaction volume, transaction count, exchange volume, generated coins etc of these currencies. Understanding the dynamics of crypto currency market can help to a certain extent to take wise investment decisions. Among the variables under consideration the study revealed that transaction volume can be used as an influencing variable to fit a quadratic regression model and predict the prices of the crypto currencies.
Bitcoin is the most radical of the cryptocurrencies which are becoming popular \nnowadays. The advantage of the cryptocurrencies is that they are decentralized \nsystems so do not need central banks. The purpose of this study is to determine if \nthere is a volatility in the returns of Bitcoin and if so, whether it is predictable. \nThe volatility of the Bitcoin returns was investigated using the log-normal \nstochastic volatility model and stochastic volatility model with leverage for daily \ndata covering the period between 19.12.2011 and 29.01.2018. While there is no \nsignificant leverage effect in the Bitcoin returns, it has been revealed that the \nvolatility is permanent and unpredictable. The unpredictability of Bitcoin returnsβ \nfluctuations suggests that it is risky to use it as an investment tool or currency. It \nis increasing day by day that Bitcoin takes place of banknotes or digital money, \nwhich are conventional means of payment. The more widespread the system, the \nsafer and the more resistant to speculations it is. The widespread popularity of \nBitcoin may facilitate its recognition by states and inclusion in traditional \npayment methods.
Bitcoin is the first decentralized cryptocurrency to be traded. There has been drastic increase in the price of bitcoin since 2013. Granger Causality analysis has been carried out to examine whether the price of commodities and the exchange rates helps in predicting the future price of bitcoin. For this study, the price of bitcoin, commodity prices and exchange rates have been considered from Jan 2103-Sep 2017. After the analysis it can be concluded that the price of commodities and the exchange rates does not help in predicting the future price of bitcoin. The past data of the price of bitcoin helps in predicting the future price of copper and British pound exchange rate with that of U.S dollars. Using Regression analysis, it can be determined that when the price increases by 0.0084 dollars there is one unit increase in the volume of transaction. Using variance analysis it can be observed that the price of bitcoin is more volatile compared to the price of commodities and the exchange rates.
OlaOluwa S. Yaya, Ephraim A Ogbonna, Olusanya E. Olubusoye
The present paper investigates persistence and dependence of Bitcoin on other popular alternative coins. We employ fractional integration approach in our analysis of persistence while a more recent fractional cointegration technique in VAR set-up, proposed by Johansen and co-authors is used to investigate dependency of the paired variables. Having segregated the series into periods before crash and those after the crash as determined by Bitcoin pricing, we obtain results of interests. Higher persistence of shocks is expected after the crash due to speculations in the mind of cryptocurrency traders, and more evidences of non-mean reversions, implying chances of further price fall in cryptocurrencies. Cointegration analysis between Bitcoin and alternative coin exists during both periods, with weak correlation observed mostly in the post-crash period. We hope the findings will serve as guide to investors in cryptocurrency.
Julia Reynolds, Leopold SSgner, Martin Wagner, Dominik Wied
This paper applies recently developed procedures to monitor and date so-called "financial marketdislocations", defined as periods in which substantial deviations from arbitrage parities take place. In particular, we focus on deviations from the triangular arbitrage parity for exchange rate triplets from a cointegration perspective. Due to increasing attention on and importance of mispricing in the market for cryptocurrencies, we include the cryptocurrency Bitcoin in addition to fiat currencies. We do not find evidence for substantial deviations from the triangular arbitrage parity when only traditional fiat currencies are concerned, but document significant deviations from triangular arbitrage parities in the newer markets for Bitcoin. We confirm the importance of our results for portfolio strategies by showing that a currency portfolio that trades based on our detected break-points outperforms a simple buy-and-hold strategy.
The appearance of cryptocurrency marks the arrival of a new unlimited global system with no intermediaries and costly intercontinental transactions. Digital money would make it possible for us to have significantly quicker and cheaper transactions, which, along with present technology, is considered inevitable in the future. This paper includes three topics and deals with the bitcoin phenomenon and its influence on economic growth. The paper presents the bitcoin technology, its advantages and some risks to which the systemβs users are exposed. Bitcoin represents an exceptional technical achievement, and specific features of bitcoin present a particular challenge for its users.
During the history there have been different examples of incorporating technology into economics. Some of them include SWIFT, e-banking, mobile payments, and many more. Technology had to be commercialized and put into service of facilitating economic processes. International finances underwent the process of development too. With the globalization process national economies became more interconnected and dependent from each other. Individuals demanded a faster and more convenient way to make international payments. Internet trade is on the rise, social media rule the contemporary world, and then appears the inception of so-called crypto currencies. The most famous is Bitcoin. Where lays its place in the economic science? It looks like that Bitcoin is going towards decentralization of the monetary system known by now. The goal of this paper is to raise the awareness of the changes happening in economy and in economic science.
The aim of this research is to explore the econometric features of Bitcoin-USD rates. Various non-Gaussian models are fitted to daily returns in order to underline the unique characteristics of Bitcoin when compared to other more traditional currencies. Market efficiency hypothesis is tested further, and the main reasons for breaches in efficiency are discussed. The main goal of the paper is to assess the presence of bubble effects in this market with customized tests able to detect the timing of various bubbles. The results show that the Bitcoin prices had two episodes of rapid inflation in 2013 and 2017.