This research aims to identify how Bitcoin-related news publications and\nonline discourse are expressed in Bitcoin exchange movements of price and\nvolume. Being inherently digital, all Bitcoin-related fundamental data (from\nexchanges, as well as transactional data directly from the blockchain) is\navailable online, something that is not true for traditional businesses or\ncurrencies traded on exchanges. This makes Bitcoin an interesting subject for\nsuch research, as it enables the mapping of sentiment to fundamental events\nthat might otherwise be inaccessible. Furthermore, Bitcoin discussion largely\ntakes place on online forums and chat channels. In stock trading, the value of\nsentiment data in trading decisions has been demonstrated numerous times [1]\n[2] [3], and this research aims to determine whether there is value in such\ndata for Bitcoin trading models. To achieve this, data over the year 2015 has\nbeen collected from Bitcointalk.org, (the biggest Bitcoin forum in post\nvolume), established news sources such as Bloomberg and the Wall Street\nJournal, the complete /r/btc and /r/Bitcoin subreddits, and the bitcoin-otc and\nbitcoin-dev IRC channels. By analyzing this data on sentiment and volume, we\nfind weak to moderate correlations between forum, news, and Reddit sentiment\nand movements in price and volume from 1 to 5 days after the sentiment was\nexpressed. A Granger causality test confirms the predictive causality of the\nsentiment on the daily percentage price and volume movements, and at the same\ntime underscores the predictive causality of market movements on sentiment\nexpressions in online communities\n
This paper is deeply motivated by the need to explore the impressive Bitcoin price development by addressing Bitcoin as money in its essential attribute as a medium of exchange. We adopt a monetary economics viewpoint and resort to a representative agent modelling strategy within a money-in-the-utility function (MIUF) framework. First, we show that the impressive Bitcoin price development observed since its inception can be interpreted as a hyperdeflation when we focus on Bitcoin role as a medium of exchange. Second, we show that specific monetary features of Bitcoin, its asymptotical fixed nominal stock and divisibility down to eight decimal places, account for a strong possibility of speculative hyperdeflationary paths. It is shown that those paths are fully consistent with the medium of exchange monetary role of Bitcoin and the representative agent optimizing behavior.
In this article, we attempt to delineate the relationship between bitcoin prices and global factors such as stock index, economic policy uncertainty, gold spot prices, implied volatility and crude oil prices in a time-frequency domain. We resort to wavelet-based analysis to capture the multiscale interactive behavior of bitcoin with global factors. We primarily show that bitcoin is insulated from global factors in the short run. However, the existence of a significant relationship of bitcoin with global factors cannot be denied in the medium to long run, which could be attributed to the endogenous and intertwined economic system. Among the global factors considered in the study, we find the impact of economic policy uncertainty and crude oil prices to be more prominent on bitcoin. Our study offers some interesting insights on multiscale sensitivity of bitcoin to global factors, which may be useful for investors for taking informed decisions
In the present paper, we investigate connectedness within cryptocurrency markets as well as across the Bitcoin index (hereafter, BPI) and widely traded asset classes such as traditional currencies, stock market indices and commodities, such as gold and Brent oil. A spill over index approach with the spectral representation of variance decomposition networks, is employed to measure connectedness. Results show no significant spillover effects between the nascent market of cryptocurrencies and other financial markets. We suggest that cryptocurrencies are real independent financial instruments that pose no danger to financial system stability. Concerning the connectedness within the cryptocurrency markets, we report a time–frequency–dynamics connectedness nature. Moreover, the decomposition of the total spill over index is mostly dominated by a short frequency component (2–4 days) leading to the conclusion that this nascent market is highly speculative at present. These findings provide insights for regulators and potential international investors.
Bitcoin is an established cryptographic digital currency whose value lays in the computational complexity rather than a physical commodity. Bitcoin is an open source software program with three aspects. (i) Peer-to-Peer networklow barrier entry; (ii) Mininginevitable concentration of power; (iii) Software upgrades. The nodes on the network follow a decentralized consensus for establishing the value of ledger and updating the blockchain which serves as a single source of truth for all transactions. As cryptocurrencies are developing more compelling utilities, creating ever faster and safer payment systems they are shifting the "money paradigm". Bitcoins are an evolution in money and provide a unique opportunity to forecast their price unlike the existing fiat currencies. The goal of this paper is to implement, train and evaluate several machine learning models in order to predict the price of the most popular cryptocurrency -Bitcoins. The various machine learning algorithms employed are -Linear Regression, K-Nearest Neighbors, Ridge Regression, Lasso Regression,
Frode Kjærland, Aras Khazal, Erlend Aune Krogstad, Frans B. Gyllenhammar Nordstrøm · 5 authors
This paper aims to enhance the understanding of which factors affect the price development of Bitcoin in order for investors to make sound investment decisions. Previous literature has covered only a small extent of the highly volatile period during the last months of 2017 and the beginning of 2018. To examine the potential price drivers, we use the Autoregressive Distributed Lag and Generalized Autoregressive Conditional Heteroscedasticity approach. Our study identifies the technological factor Hashrate as irrelevant for modeling Bitcoin price dynamics. This irrelevance is due to the underlying code that makes the supply of Bitcoins deterministic, and it stands in contrast to previous literature that has included Hashrate as a crucial independent variable. Moreover, the empirical findings indicate that the price of Bitcoin is affected by returns on the S&P 500 and Google searches, showing consistency with results from previous literature. In contrast to previous literature, we find the CBOE volatility index (VIX), oil, gold, and Bitcoin transaction volume to be insignificant.
The paper analyzes the relationship between the most popular cryptocurrencies and a range of selected fiat currencies, in order to identify any pattern and/or causality between the series. Cryptocurrencies are a hot topic in Finance due to their strict relationship with the Blockchain system they originate from and therefore are normally considered as part of the ongoing, world-wide financial revolution. This innovative study investigates this relationship for the first time by thoroughly investigating the data, their features, and the way they are interconnected. Results show very interesting results in terms of how concentrated the causality effect on some specific cryptocurrencies and fiat currencies is. The outcome is a clear and possibly explainable relationship between cryptocurrencies and Asian markets, while envisioning some kind of Asian effect.
The authors assess the impact of the emotional tonality of bitcoin news on its exchange rate. In particular, we studied the hypothesis of the impact of the readability index of the news text on the volatility of bitcoin. Despite the fact that excessive volatility threatens bitcoin not to become a successful currency, many scientists are interested in the determinants of such volatility. Factors such as speculative investments or the attention of the society are the drivers of the volatility of the exchange rate of bitcoin. In this regard, the question of studying the impact of news on the bitcoin exchange rate is relevant. The purpose of this paper is to assess the impact of the emotional tonality of bitcoin news on its exchange rate. The empirical base of the study was quite extensive since it includes more than 1330 news from the Thomson Reuters information base for the period from 19.08.2011 to 16.08.2016 on the bitcoin market. The research methodology includes the sentiment analysis conducted by using the dictionary MacDonald and Loughran and also the analysis of the interdependence of time series-based causal analysis using the test of Granger causation. We present three hypotheses about the impact of news on the bitcoin exchange rate. During the study, two of them were confirmed. We proved the first hypothesis that the negative news had a more significant impact than positive ones, taking into account the five time-lags. The second hypothesis about the impact of positive tonality in the news on the bitcoin exchange rate, using the Granger test for causation, was not confirmed, since the positive values of this test were obtained in two time-lags out of five. We can confirm that the third hypothesis was proved — the high readability index has an impact on the bitcoin volatility for the entire studied period, taking into account all five time-lags. Thus, the assumption about the impact of the emotional tonality of news on the bitcoin exchange rate can be confirmed.
Open access
Market Dynamics and Volatility
Blockchain Technology Applications and Security
Economic, Social, and Public Health Issues in Russia and Globally
In the course of the research, we identified seven risk groups, analyzed their influence, and formulated possible measures of the risk mitigation. For initial coin offerings projects, we formulated a special risk-assessment scoring system based on a 100-point scale. Investment risks (volatility) were one of the main issues. The only effective option of risk-management here is risk aversion - the refusal of any interaction with the cryptocurrency market. On the other hand, traditional risk management method of diversification has proved its worth and viability on empirical studies of portfolio investments. The portfolio should not be mostly “crypto” but rather it should also consist of traditional assets. It is necessary to consider the opportunity to quit the cryptocurrency market for a short period of time, to prevent the harmful consequences of dramatic price shifts.
Main objective of this study is to develop investment portfolio with diversifications using two different assets. Modern portfolio theory develop investment portfolio to maximize expected return based on a given level of market risk. This study selected cryptocurreny (Bitcoin) and stock price (Petronas Gas Berhad) as the combination in developing investment portfolio. In this analysis, mean return for Bitcoin is 9.890 %. Meanwhile, the mean return for stock price of Petronas Gas Berhad is -0.496 %.The value of correlation is between two assets is -0.372. Result shows the portfolio risk can be reduced with the diversification approach for different assets. Therefore, findings of this study are important for assisting investors to maximize their return for given level of investment risk.
Bu çalışmada, isminden son yıllarda sıkça bahsettiren ve kripto paralardan biri olan Bitcoin fiyatı ile Türkiye ve G7 ülkelerine ait borsa endeksleri arasındaki nedensellik ilişkisi incelenmektedir. Bitcoin fiyatlarındaki dalgalanmanın 2013 yılından itibaren başlaması nedeni ile çalışmada 01.01.2013-26.01.2018 arasındaki günlük veriler kullanılmıştır. Çalışmada öncelikle birim kök testleri ve eşbütünleşme analizi gerçekleştirilmiştir. Değişkenler arasındaki ilişkinin uzun dönemde dengede olup olmadığını analiz edebilmek için vektör hata düzeltme modeli (VECM) kullanılmış, kısa dönemli ilişkiler ise Granger Nedensellik/WALD testi yardımıyla incelenmiştir. Yapılan analizler sonucunda, Bitcoin ile diğer ülke borsaları arasında herhangi bir uzun dönemli denge ilişkisinden söz edilemeyeceği bulunurken, kısa dönemde İngiltere borsasının (FTSE) Bitcoin’in nedeni olduğu sonucuna ulaşılmıştır. Ayrıca, Bitcoin’in de S&P 500 ve Kanada Borsasının (STSX) nedeni olduğu görülmüştür. Sonuç olarak, Bitcoin fiyatının dalgalanması hakkında kısa vadede bu üç borsa endeksinin de fikir verebileceği ortaya çıkmaktadır. Yatırımcılar hem araştırmaya konu olan bu borsalar arasında hem de Bitcoin’e yatırım yaparak risklerini çeşitlendirme yoluna gidebilir.
Bitcoin has enjoyed wider adoption than any previous cryptocurrency; yet its success has also attracted the attention of fraudsters who have taken advantage of operational insecurity and transaction irreversibility. We study the risk that investors face from the closure of Bitcoin exchanges, which convert between Bitcoins and hard currency. We examine the track record of 80 Bitcoin exchanges established between 2010 and 2015. We find that nearly half (38) have since closed, with customer account balances sometimes wiped out. Fraudsters are sometimes to blame, but not always. Twenty-five exchanges suffered security breaches, 15 of which subsequently closed. We present logistic regressions using longitudinal data on Bitcoin exchanges aggregated quarterly. We find that experiencing a breach is correlated with a 13 times greater odds that an exchange will close in that same quarter. We find that higher-volume exchanges are less likely to close (each doubling in trade volume corresponds to a 12% decrease in the odds of closure). We also find that exchanges that derive most of their business from trading less popular (fiat) currencies, which are offered by at most one competitor, are less likely to close.
We demonstrate that investors obtain abnormal returns by trading cryptocurrencies daily on the London Stock Exchange from 2014–2017. Excess returns persist once we account for systematic risk, size, value, momentum, profitability and investment. Investor abnormal returns in cryptocurrencies implies inefficiency.
Nino Antulov-Fantulin, Dijana Tolić, Matija Piškorec, Ce Zhang · 5 authors
In this paper, we study the possibility of inferring early warning indicators (EWIs) for periods of extreme bitcoin price volatility using features obtained from Bitcoin daily transaction graphs. We infer the low-dimensional representations of transaction graphs in the time period from 2012 to 2017 using Bitcoin blockchain, and demonstrate how these representations can be used to predict extreme price volatility events. Our EWI, which is obtained with a non-negative decomposition, contains more predictive information than those obtained with singular value decomposition or scalar value of the total Bitcoin transaction volume.
We investigate connectedness within and across two major groups or assets: i) five popular cryptocurrencies, and ii) six major asset classes plus two commonly employed risk factors. Granger-causality tests uncover six direct channels of causality from the elements of the mainstream assets/risk factors group to digital assets. On the other hand there are two statistically significant causal links going in the other direction. In order to provide some perspective on the magnitude of the uncovered linkages we supplement the analysis by estimating networks from forecast error variance decompositions. The estimated connectedness within the groups is relatively large, whereas the linkages across the two groups are small in comparison. Namely, less than 2.2 percent of future uncertainty of any cryptocurrency is sourced from all non-crypto assets combined, while the joint contribution of all digital assets to non-crypto uncertainty does not exceed 1.5 percent.
This article deals with the concepts of social currencies and cryptocurrencies. The objective of the present paper is to identify similarities and differences between to two currency systems which represent a new generation of money that exists alongside the official and legal money system. The paper includes an analysis of the major characteristics of both currencies, their operating mechanisms in global and local contexts, as well as their risks and challenges for the financial markets. The article uses a mainly documentary research method and presents selected contributions of experts on the topics of social currencies and cryptocurrencies. Furthermore, empirical evidence is presented to highlight some important characteristics of the Bitcoin currency. The principal result of the paper is that, indeed there exist similarities between social currencies and cryptocurrencies, as for example the absence of a central bank, a lack of regulation and a limited minting process. However, because of aspects like their different origins, their local vs. global character and their inherent financial risks, the two money systems need to be interpreted as fundamentally different. Especially with reference to globally operating cryptocurrencies, given that there does not exist any public cover of the currency nor sufficient regulation, risk management mechanisms need to be improved in order to diminish the speculative tendencies inherent to this currency.
Pilar Grau Carles, Diego Jaureguizar Arellano, Carlos Jaureguizar Francés
In this paper we examine the characteristics of the daily price series of 16 different cryptocurrencies between July 2017 and February 2018. The methodologies used for the analysis are the so-called Minimum Spanning Tree (MST) and hierarchical analysis by dendrogram, both obtained Pearson correlations between daily returns. This methodology visualizes the market relationships between the assets analyzed, identifying a high correlation between price movements for all the currencies. In addition, it has been possible to identify Ethereum’s position as a benchmark currency in the cryptocurrency market, rather than Bitcoin, as one might expect, due to its popularity and trading volume.
Libing Fang, Elie Bouri, Rangan Gupta, David Roubaud
We assess whether the long-run volatilities of Bitcoin, global equities, commodities, and bonds are affected by global economic policy uncertainty. Empirical results provide evidence supporting that, except for the case of bonds. We further examine whether the correlation between Bitcoin and global equities, commodities, and bonds are affected by global economic policy uncertainty and the results reveal that global economic policy uncertainty has a negative significant impact on the Bitcoin-bonds correlation, and a positive impact on both Bitcoin-equities and Bitcoin-commodities correlations, suggesting a possibility for Bitcoin to act as a hedge under specific economic uncertainty conditions. Interestingly, the hedging effectiveness of Bitcoin for both global equities and global bonds enhances slightly after considering the level of global economic policy uncertainty. Implications for investors and policy-makers are discussed.