Decentralized cryptocurrencies have gained a lot of attention over the last decade. Bitcoin was introduced as the first cryptocurrency to allow direct online payments without relying on centralized financial entities. The use of Bitcoin has vastly grown as a financial asset rather than just a tool for online payments. A lot of cryptocurrencies have been created since 2011 with Bitcoin dominating the cryptocurrencies' market. With plenty of cryptocurrencies being used as financial assets and with millions of trades being executed through different exchange services, cryptocurrencies are susceptible to trading problems and challenges similar to those traditionally encountered in the financial domain. Price and trend prediction, volatility prediction, portfolio construction and fraud detection are some examples related to trading. In addition, there are other challenges that are specific to the domain of cryptocurrencies such as mining, cybersecurity, anonymity and privacy. In this paper, we survey the application of artificial intelligence techniques to address these challenges for cryptocurrencies with their vast amount of daily transactions, trades and news that are beyond human capabilities to analyze and learn from. This paper discusses the recent research work done in this emerging area and compares them in terms of used techniques and datasets. It also highlights possible research gaps and some potential areas for improvement.
Guglielmo Maria Caporale, Woo-Young Kang, Fabio Spagnolo, Nicola Spagnolo
This paper examines mean and volatility spillovers between three major cryptocurrencies (Bitcoin, Litecoin and Ethereum) and the role played by cyber-attacks. Specifically, trivariate GARCH-BEKK models are estimated which include suitably defined dummies corresponding to different types, targets and number per day of cyber-attacks. Significant dynamic linkages (interdependence) between the three cryptocurrencies under investigation are found in most cases when cyber-attacks are taken into account, Bitcoin appearing to be the dominant cryptocurrency. Further, Wald tests for parameter shifts during episodes of turbulence resulting from cyber-attacks provide evidence that the latter affect the transmission mechanism between cryptocurrency returns and volatilities (contagion). More precisely, cyber-attacks appear to strengthen cross-market linkages, thereby reducing portfolio diversification opportunities for cryptocurrency investors. Finally, the conditional correlation analysis confirms the previous findings.
Stablecoins are digital currencies whose value is pegged to fiat currencies like the dollar or other assets. They were created as a more flexible alternative to fiat currencies for cryptocurrency exchanges and constitute an increasingly important aspect of cryptocurrency markets and alternative finance. We analyze the influence of stablecoin issuances on the returns of major cryptocurrencies across 565 issuance events of $1 million or more for seven different stablecoins on four different blockchains between April 2019 and March 2020. Our event study reveals cryptocurrency market downturns in the week before a stablecoin issuance and positive abnormal returns for major cryptocurrencies in the twenty-four hours before and after the issuance. Effect sizes differ across stablecoins. Counterintuitively, we find that issuance size does not significantly affect the abnormal returns. We conclude that stablecoin issuances contribute to price discovery and market efficiency of cryptocurrencies.
Shaen Corbet, Yang Hou, Yang Hu, Charles Larkin · 5 authors
Controlling for the polarity and subjectivity of social media data based on the development of the COVID-19 outbreak, we analyse the relationships between the largest cryptocurrencies and such time-varying realisation as to the scale of the economic shock centralised within the rapidly-escalating pandemic. We find evidence of significant growth in both returns and volumes traded, indicating that large cryptocurrencies acted as a store of value during this period of exceptional financial market stress. Further, cryptocurrency returns are found to be significantly influenced by negative sentiment relating to COVID-19. While not only providing diversification benefits for investors, results suggest that these digital assets acted as a safe-haven similar to that of precious metals during historiccrises.
Literature suggests assets become more correlated during economic downturns. The current COVID-19 crisis provides an unprecedented opportunity to investigate this considerably further. Further, whether cryptocur-rencies provide a diversification for equities is still an unsettled issue. Additionally , the question of whether cryptocurrency futures are safe havens has received very little attention. We employ several econometric procedures , including wavelet coherence, copula principal component, and neural network analyses to rigorously examine the role of COVID-19 on the paired co-movements of six cryptocurrencies, as well as bitcoin futures, with fourteen equity indices and the VIX. We find co-movements between cryptocurrencies and equity indices gradually increased as COVID-19 progressed. However, most of these co-movements are positively correlated, suggesting that cryptocurrencies do not provide a diversification benefit during downturns. Exceptions, however, are the co-movements of bitcoin futures and tether being negative with equities. Results are consistent with investment vehicles that attract either more informed or more speculative investors differentiating themselves as safe havens.
The COVID-19 pandemic provided the first widespread bear market conditions since the inception of cryptocurrencies. We test the widely mooted safe haven properties of Bitcoin, Ethereum and Tether from the perspective of international equity index investors. Bitcoin and Ethereum are not a safe haven for the majority of international equity markets examined, with their inclusion adding to portfolio downside risk. Only investors in the Chinese CSI 300 index realized modest downside risk benefits (contingent on very limited allocations to Bitcoin or Ethereum). As Tether successfully maintained its peg to the US dollar during the COVID-19 turmoil, it acted as a safe haven investment for all of the international indices examined. We caveat the latter findings with a warning that Tether's dollar peg has not always been maintained, with evidence of impaired downside risk hedging properties earlier in our sample.
At the beginning of the 2020 global COVID-2019 pandemic, Chinese financial markets acted as the epicentre of both physical and financial contagion. Our results indicate that a number of characteristics expected during a "flight to safety" were present during the period analysed. The volatility relationship between the main Chinese stock markets and Bitcoin evolved significantly during this period of enormous financial stress. We provide a number of observations as to why this situation occurred. Such dynamic correlations during periods of stress present further evidence to cautiously support the validity of the development of this new financial product within mainstream portfolio design through the diversification benefits provided.
In the Ethereum network, miners are incentivized to include transactions in a block depending on the gas price specified by the sender. The sender of a transaction therefore faces a trade-off between timely inclusion and cost of his transaction. Existing recommendation mechanisms aggregate recent gas price data on a per-block basis to suggest a gas price. We perform an empirical analysis of historic block data to motivate the use of a predictive model for gas price recommendation. Subsequently, we propose a novel mechanism that combines a deep-learning based price forecasting model as well as an algorithm parameterized by a user-specific urgency value to recommend gas prices. In a comprehensive evaluation on real-world data, we show that our approach results on average in costs savings of more than 50% while only incurring an inclusion delay of 1.3 blocks, when compared to the gas price recommendation mechanism of the most widely used Ethereum client.
This paper evinces the ability of gold to avoid risks during periods with great fluctuations in the Bitcoin market. We apply bootstrap full- and subsample rolling-window Granger causality tests to explore the causal relationship between Bitcoin price (BCP) and gold price (GP). The empirical results show that an increase in BCP can cause GP to decrease, indicating that the prosperity of the Bitcoin market undermines the hedging ability of gold. However, a decrease in BCP causes GP to increase, and it also emphasizes that the ability of gold to avoid risks persists. Hence, the status of gold will not be completely threatened by Bitcoin, and they are complementary to each other instead of in competition. In turn, both positive and negative influences of GP on BCP suggest that fluctuations in BCP can be predicted through the gold market. In situations of severe global uncertainty and complicated investment environments, investors can benefit from complementary markets to optimize their asset allocation. Additionally, countries can grasp the trends in Bitcoin and gold prices to prevent large fluctuations in both markets and to reduce the uncertainty of the financial system.
Κωνσταντίνος Γκίλλας, Elie Bouri, Rangan Gupta, David Roubaud
We extend existing studies by considering the higher-order moments relationships among crude oil, gold, and Bitcoin markets. Using high-frequency data from December 2, 2014 to June 10, 2018, we analyze spillovers in jumps and realized second, third, and fourth moments among crude oil, gold, and Bitcoin markets via Granger causality and generalized impulse response analyses. Results suggest evidence of predictability and emphasize, among others, the need of jointly modeling linkages across those three markets with higher-order moments; otherwise, inaccurate risk assessment and investment inferences may arise. The responses of realized volatility shocks are generally positive. Further analyses indicate evidence of a weaker relationship between gold and crude oil and Bitcoin and crude oil compared to the relationship between Bitcoin and gold. Practical implications are also discussed.
Shaen Corbet, Charles Larkin, Brian M. Lucey, Andrew Meegan · 5 authors
This paper examines the relationship between news coverage and Bitcoin returns. Previous studies have provided evidence to suggest that macroeconomic news affects stock returns, commodity prices and interest rates. We construct a sentiment index based on news stories that follow the announcements of four macroeconomic indicators: GDP, unemployment, Consumer Price Index (CPI) and durable goods. By controlling for a number of potential biases we determine as to whether each of the series' have a significant impact on Bitcoin returns. While an increase in positive news surrounding unemployment rates and durable goods would typically result in a corresponding increase in equity returns, we observe the opposite to be true in the case of Bitcoin. Increases in positive news after unemployment and durable goods announcements result in a decrease in Bitcoin returns. Conversely, an increase in the percentage of negative news surrounding these announcements is linked with an increase in Bitcoin returns. News relating to GDP and CPI are found not to have any statistically significant relationships with Bitcoin returns. Our results indicate that this developing cryptocurrency market is further maturing through interactions with macroeconomic news.
The Covid-19 bear market presents the first acute market losses since active trading of Bitcoin began. This market downturn provides a timely test of the frequently expounded safe haven properties of Bitcoin. In this paper, we show that Bitcoin does not act as a safe haven, instead decreasing in price in lockstep with the S&P 500 as the crisis develops. When held alongside the S&P 500, even a small allocation to Bitcoin substantially increases portfolio downside risk. Our empirical findings cast doubt on the ability of Bitcoin to provide shelter from turbulence in traditional markets.
We use a GARCH dummy model to study the influence of calendar effects on daily conditional returns and volatility of Bitcoin during the period 2013–2019. The Halloween, day-of-the-week (DOW), and month-of-the-year (MOY) effects are analyzed. Our results reveal no evidence of a Halloween calendar anomaly. A classical DOW effect is not present in Bitcoin returns, however, we find significantly lower risk over the weekend whilst in the beginning of the week Bitcoin's volatility is more intense. Moreover, supporting evidence of a reverse January effect is detected. Our results also show that investors’ risk drops substantially in September.
Çalışmada Türkiye’deki seçili bir takım finansal değişkenlerle (USD, EURO, POUND, SDR, BİST 100, Cumhuriyet Altını, M1 ve M2 para arzları) sanal para birimi Bitcoin (BTC) arasındaki ilişki incelenmiştir. Bu kapsamda 2013-2019 dönemine ait aylık veriler kullanılmıştır. Analizler sonucunda değişkenlerin birinci farklarının durağan olduğu tespit edilmiş, diğer taraftan Bitcoin ile diğer finansal değişkenler arasında uzun dönemli bir eşbütünleşmenin varlığı belirlenmiştir. Değişkenler arasında nedenselliğin araştırıldığı Granger Nedensellik testi ile de Bitcoin’in bağımlı değişken olduğu denklemde SDR ve USD ‘den BTC’ye doğru %5 anlamlılık düzeyinde; Euro ve BIST 100 değişkeninden BTC’ye doğru ise %10 anlamlılık seviyesinde bir nedenselliğin varlığı tespit edilmiştir.
Purpose - The purpose of this study was to examine gold and bitcoin hedging against 10 exchange returns.
Design/Methodology/Approach - This study collected financial data on exchange, gold, and bitcoin from FRB, St. Louis. A multiple Vector-BEKK regression analysis was used to analyze the data.
Findings - First, strong negative effects from exchange markets onto gold were found to exist in the EU, Switzerland, Australia, Brazil, Canada, Japan, and Korea, while there were weak effects in the UK. Bitcoin shows the weak hedging against all markets. Second, the paper also revealed that in EU, the cross-shock term significantly decreased gold volatility, but not bitcoin volatility, while in Japan it decreased bitcoin volatility. The significantly negative asymmetries in gold, but insignificant asymmetries in bitcoin, were found in most exchange markets. Exchange market volatility increases gold volatility in Japan while it decreased in the Indian and Korean markets. Cross-terms among three variables with bi-directional causality are valuable.
Research Implications or Originality - The study of the hedging of gold and bitcoin against various exchanges together shows that bi-variate models are useful to reconfirm the strong hedging of gold. Bitcoin, if well prepared to be immune to its deficiencies, might be very carefully used, but not at a magnitude equal to gold as a hedge against exchange. The results may enhance strategic risk management.
The article examines the problem of the ICO (Initial Coin Offering, from English — “initial offer of coins, initial placement of coins”). The information source is the ICO rating data of the return on investment in blockchain startups. The methodological base of the research is a situational comparative analysis of the ICO, DAOICO, IEO and STO and systematization of information. The author analyzes three new ICO models. The first one includes elements of Decentralized Autonomous Organizations (DAO). Its aim is to minimize the difficulties and risks associated with the ICO. The second model (Initial Exchange Offering (IEO), from English — “primary exchange offer”) is designed to minimize risks, liquidity problems and a delay in listing tokens at the end of the token sale. The third model — the Security Token Offering (STO, from English — “offer of security token”) — was designed to support real assets and comply with the SEC requirements. These models are a new direction for small and medium enterprises and investors. The absence of any scientific work emphasizes the relevance and scientific novelty of the study. The article is a follow-up of the empirical work related to the success of the ICO, as well as the basis for its revision using the case study results.
The major reason of performing this study is to examine volatility of the Bitcoin prices. As known, Bitcoin became more popular when its price movements changed radically. It has been increasing for years since the date of first issuance in 2010 and reached highest level in its history by testing 19,345 USD. Based on this price movement, risk and returns are taken together for making investment in Bitcoin since huge decreasing observed in respond to the these increases. Methodology -In this study, Bitcoin prices are analyzed monthly basis through the time series analysis. Data related to closing prices of Bitcoin are obtained from investing.com web site. We established analysis based on sample consist of Bitcoin prices for the period between 2016 and 2019. Augmented Dickey Fuller (ADF) and Phillips Perron (PP) unit root test is applied to find out whether series are stationary or not. Findings-According to test results, the series of Bitcoin prices are not stationary yet. Although different fluctuating degree can be seen by years, generally it can be stated that Bitcoin prices are still volatile. Conclusion-Based on findings, Bitcoin prices may still be considered as volatile instrument. Therefore, investors should be careful when they want to include this investment tool to the portfolio since it represents risky instrument properties.