This study aims to explore the Coronavirus disease (COVID-19) effects on gold and bitcoin prices variabilities and on the relationship between each of them, both prices are denominated in USD.The study period is divided into two groups, first group included 120 workdays before 30 January 2020 when WHO first declared COIVD-19 outbreak as a public health emergency of international concern, and the second group included 120 observations post that date. The period as a total extends from June. 24, 2019 to 22 of May 2020.To this end, the study used the appropriate statistical tools including stationery and unit root test, Levene's test for the equality of variances, correlation, least squares regression, and pairwise Granger causality test.The results of testing the equality of variances and homogeneity between each of the study groups before and after COVID 19 revealed a strong rejection of the null hypothesis of equal variances for gold but not bitcoin which was accepted. The results also indicate a significant relationship between gold and bitcoin before and after COVID-19, but the sign changed from negative to positive respectively.Finally, the study concludes that there were significant effects of COIVD-19 on gold but not bitcoin prices. These results are consistent with gold’s traditional role as a safe-haven in crises, and bitcoin as a ‘virtual gold’ which has some similarities, and likely to be complementary rather than in a competion with gold.
In this study, a web model which provides price estimation in terms of Turkish Lira for Bitcoin, Ethereum and Ripple which are popular cryptocurrencies, is developed. Using the relevant model, the price estimation of these three crypto currencies between 21.09.2019 and 20.11.2019 is carried out on the web with dynamic data. Artificial intelligence methods such as adaptive neural fuzzy inference system, artificial neural networks, polynomial curve fitting and long short-term memory are used for price estimation. The aim of this study is to provide periodic forecasts to individuals or institutions interested in cryptocurrencies and to test the success of the exemplary model of the use of artificial intelligence in finance. When the forecastings that haven't yet been realized at the relevant dates and the actual values are compared, the successful results show that the model is well established.
We test various volatility models using the Bitcoin spot price series. Our models include HIST, EMA ARCH, GARCH, and EGARCH, models. Both of our in-sample-fit and out-of-sample-forecast results suggest that GARCH and EGARCH models perform much better than other models. Moreover, the EGARCH model's asymmetric term is positive and insignificant, which suggests that Bitcoin prices lack the asymmetric volatility response to past returns. Finally, we formulate an option trading strategy by exploiting the volatility spread between the GARCH volatility forecast and the option's implied volatility. We show that a simple volatility-spread trading strategy with delta-hedging can yield robust profits.
Complementing increasing concerns that cryptocurrency could be used to finance terror networks, in this paper we investigate the effect of monthly terrorist attacks outcomes – success, injuries, and fatalities – on monthly returns of 1,178 cryptocurrencies representing 18,016 cryptocurrency-year-months between 2014 and 2018. The monthly percentage of successful terror attacks Granger causes the monthly cryptocurrency returns and lowers the monthly cryptocurrency returns. Increasing success in terror attacks is negatively associated with cryptocurrency returns, the count of wounded is negatively associated with cryptocurrency returns, however, the count of dead is positively associated with cryptocurrency returns. The success in terror attacks has the largest effect on returns, relative to the count of wounded and dead. The estimates are consistent when controlling for cross-sectional correlation among major cryptocurrencies, and cryptocurrencies could be a weak hedge against successful terrorist attacks. The findings are robust to cryptocurrencies in the top three quartiles of the market capitalization and the mediation analysis shows that terror attacks lower returns through the decline in the short-term macroeconomic cycle.
Market Dynamics and Volatility
Terrorism, Counterterrorism, and Political Violence
Purpose: The purpose of this paper is to examine empirically the spillover impacts between Bitcoin and the major energy commodities. Design/methodology/approach: To do so, we employ an asymmetric multivariate VAR-BEKK-AGARCH model to study spillover effects between Bitcoin and three energy commodities during the period from July 18, 2010 to June 30, 2018. Findings: The empirical findings show return spillovers from energy stock indices to Bitcoin. We find unilateral return and volatility spillovers and bidirectional shock influences and demonstrate portfolio management implications of dynamic conditional correlation. The little correlation of Bitcoin with the stock indices offers portfolio benefits. Our findings imply the importance of Bitcoin in portfolio construction and reflects the importance of diversification of portfolio between energy commodities and the crypto-currencies, mainly Bitcoin. Practical Implications: Bitcoin has qualified a fast development while across a time and several shareholders and investors are demonstrating importance in its possibility as a consolidative component of portfolio variation. Originality/value: The significant extension is the using of a recently established multivariate econometric method, VAR-BEKK-AGARCH, which is utilized to study the degree of incorporation in rapports of instability and return among Bitcoin and energy commodities.
Steffen Günther, Christian Fieberg, Thorsten Poddig
<abstract xml:lang="eng"> Summary: We analyze the cross-section of more than 1200 cryptocurrencies derived from 350 exchanges in the time period from January 2014 to June 2020. Specifically, we investigate whether well-known cross-sectional characteristics like beta (Fama/MacBeth (1973)), size (Banz (1981)) or momentum (Jegadeesh/Titman (1993)) – which have been intensively investigated in the equities literature – explain the cross-section of cryptocurrency returns. We apply the monotonic relationship (Mr.) test developed by Patton and Timmermann (2010) to test for dependencies between characteristics and average portfolio returns and standard deviations. We extend the existing literature on cryptocurrencies showing that there are various characteristics which are able to explain cryptocurrency risk and return. Zusammenfassung: Wir untersuchen den Querschnitt von über 1200 Kryptowährungen, gesammelt von 350 Handelsplätzen, in der Zeitspanne von Januar 2014 bis Juni 2020. Im speziellen untersuchen wir, ob weit verbreitete Charakteristika, wie Beta (Fama/MacBeth (1973)), Size (Banz (1981)) oder Momentum (Jegadeesh/Titman (1993)) – die bereits intensiv in der Aktienliteratur untersucht werden – den Querschnitt der Kryptowährungsrenditen erklären können. Wir verwenden den Monotonic Relationship (MR) Test von Patton und Timmermann (2010) um auf Abhängigkeiten zwischen Charakteristika und durchschnittlichen Portfoliorenditen sowie Standardabweichungen zu testen. Wir erweitern die bestehende Literatur, indem wir zahlreiche Charakteristika identifizieren, die Risiko und Renditen von Kryptowährungen erklären können.
Purpose In this paper, our aim is to estimate the time varying correlations between Bitcoin, VIX futures and CDS indexes and to examine in what ways these assets can act as beneficial hedge and safe haven mechanisms, useful for facing, or attenuating, the major world equity markets related risks and volatilities. Design/methodology/approach Our methodology consists to model each pair equity/asset indices by bivariate symmetric and asymmetric dynamic conditional models (A) DCC to evaluate the portfolio design associated implications on both daily and weekly collected data base, with regard to the period ranging from July, 2010 to January 2018. To assess the extent to which the Bitcoin, VIX futures and sovereign CDS may stand as diversifiers, i.e. as hedging or safe haven instruments against the various stock indexes, we adopt the same method applied by Baur and Lucey (2010). Findings Empirical results show that the hedging and safe haven roles associated with the three hedging instruments tend to differ noticeably across time horizons and model used. The interest brought about by treating this issue is twofold. On the one hand, it should provide useful guidelines to investors through helping them opt for the most effective and beneficial strategies, whereby they could efficiently hedge the equity markets related extreme risks and volatilities. On the other hand, it is intended to highlight the applied models' specifications associated impacts. Research limitations/implications The interest brought about by treating this issue is twofold. On the one hand, it should provide useful guidelines to investors and financial advisors through helping them opt for the most effective and beneficial of the strategies, whereby they could efficiently hedge the equity markets related extreme risks and volatilities. On the other hand, it is intended to highlight the applied models' specifications associated impacts. Originality/value Study of Bitcoin can be considered as safe haven or hedge or diversifier instrument. Compare between Bitcoin, VIX and CDs.
Previous studies have shown that cryptocurrencies could hedge equities. However, most of those studies did not take into account the recent cryptocurrencies bubbles in 2018 and domestic currencies. Therefore, this research aimed to study whether the hedge effectiveness of cryptocurrencies still exists. This research used five cryptocurrencies (bitcoin, ethereum, monero, ripple, and litecoin), equity indices (Indonesia, Malaysia, Vietnam, Thailand, and the Philippines), and iShares ETF MSCI World (developed world). Commodities-based hedging using iShares S&P GSCI Commodity-Indexed Trust was also analyzed as a comparison. The asymmetric generalized dynamic conditional correlation (AG-DCC) GARCH showed that one cryptocurrency could not significantly and consistently hedge equities while five equally weighted cryptocurrencies could marginally hedge equities. Meanwhile, the classical minimum variance model also showed that the hedge effectiveness of cryptocurrencies was insignificantly positive. Equity traders could add cryptocurrencies into portfolios when the purpose was to maximize the Sharpe ratio instead of hedging. Overall, commodities were the better hedge for Southeast Asia emerging markets.
Purpose This paper examines the impact of cryptocurrency market on the stock market performance in Middle East and North Africa (MENA) region. A comparative analysis is extended to distinguish this impact between Gulf countries and other economies in the region. Design/methodology/approach The analysis uses the information of cryptocurrencies and the stock market indices of the Gulf countries for the period 2014–2018 on a daily basis. Two strategies have been implemented to fulfill the goal of the study: first, the tests strategy, which is applied using the cointegration analysis and panel-specific forms of Granger causality; second, the regression strategy, which is applied mainly using the instrument variable with generalized method of moments (IV-GMM) method. Findings The results show that there is a significant relationship between the cryptocurrency market and the stock market performance in the MENA region. On the one hand, for the Gulf countries that claim full obedience to the Islamic Sharia rules, each 1% increase in the cryptocurrency returns reduces the stock market performance by 0.15%. On the other hand, for the non-Gulf (other MENA) countries that have flexibility in applying the Islamic Sharia rules or do not follow it, the stock market performance increases by 0.13%, for each 1% increase in the cryptocurrency returns. Originality/value The paper proposes two main contributions: First, the paper introduces the cryptocurrency returns as one of the determinants of the stock market performance in the MENA region. This impact is distinguished based on the degree of applying the Islamic Sharia rules and the vision of the government to the stock market. Second, the paper provides an empirical guideline for governments in the MENA region for efficient measures in their stock market, given the important expansion of the cryptocurrency market and the government type.
This paper proposes and discusses the idea of using nascent blockchain hosted prediction markets as a decentralised crowd sourcing method for renewable energy forecasting. This method is further used as a risk management and hedging tool against volatility in weather variables they depend on. While existing approaches have been centralised by nature, with limited sources of input data and models, prediction markets allow anyone to participate in forecasting by betting on an outcome and earning profits for correct results. Since they have mercenary motivations, these participants are most likely to provide reliable and accurate information. Moreover, renewable energy producers can participate in these prediction markets to hedge against low-income periods due to poor weather conditions. This paper delivers a conceptual framework to exploit prediction markets in a blockchain platform with the aim of forecasting and hedging of renewable energy sources. The potential financial gain from applying this approach has been demonstrated through a case study for a typical small wind power producer.
Cutting edge technology behind cryptocurrency can revolutionize payment systems and transform the global economy. However, data shows cryptocurrencies major limitation, such as the significant energy consumption due to the high computing power requirement (De Vries, 2018). Moreover, recent study published in Nature claims that increasing carbon dioxide emissions from Bitcoin mining alone could lead to a 2° C increase in global mean average temperatures within 30 years (CRS, 2019). The definition of the circumstances under which cryptocurrencies evolution could be beneficial, or scenarios when it becomes a dramatic burden on society is needed. This research aims to estimate cryptocurrencies’ benefits by comparing its market value against its electric costs and associated social and environmental externalities in ten years from now. My research examines cryptocurrencies true profitability through cost-benefit analysis and evaluates its environmental footprint, utilizing a range of scenarios and various models. To address my research questions, I test two hypotheses. First, if cryptocurrencies’ adoption rate follows the broadly used technologies growth pattern scenario, then in ten years, cryptocurrency’s mining will require more electricity than consumed by the entire United States in 2018. Secondly, if the penetration of renewable energy into the electricity supply mix used by mining remains at current levels, I project that cryptocurrencies’ fossil fuels consumption growth will lead to carbon dioxide emissions reaching 2018 United States CO2 emissions mark (5,269MMmt) (EIA, 2019). The findings of this study show that by 2028, amount of cryptocurrencies market value needed to support economic activities will expand from current $240 billion to a range between 2.4 trillion USD to 2.9 trillion USD. The rising electricity requirements to produce cryptocurrencies could lead to likely electricity consumption of 293TWh (equivalent to 1 % of US energy consumed in 2018). This electricity consumption level would generate electricity costs ranging between 23 to 57 billion USD per year and carbon emissions ranging between 53 to 63.6 MtCO2. The research results do not suggest that cryptocurrency is “burning down the planet”, but the negative externalities identified in the research should be considered. For example, the results illustrate a scenario where each 1 USD of cryptocurrency coin value created would be responsible for 0.66 UDS in health and climate damages. The externalities discussed in this study can be valuable for the development of standards around disclosure practices and in setting the right rules concerning adoption of blockchain and encrypted currencies.
This study investigates the connectedness between Bitcoin prices and major stock indices in the Asia-Pacific region from February 2012 to August 2019. Based on the wavelet transform framework, we find evidence of significant unidirectional association from Bitcoin to the selected markets in the short, medium, and long-run in the Asia-Pacific region. Overall, Asia-Pacific equity markets and Bitcoin cryptocurrency are weakly correlated at higher frequencies throughout the sample period, but the dependence of Bitcoin on the equity markets steadily increases at lower frequencies. Further, we construct the wavelet-based Granger causality test at different time scales to provide additional support to our connectedness results. Our findings provide important implications for policymakers, portfolio managers, and investors who are invited to take into account the dynamic linkages between Bitcoin and equity markets.
BITCOIN has a different criterion than traditional systems that pay in states’ currencies. This payment system is a complex scheme designed to facilitate the transfer of value between the parties. In this study, firstly, brief information about technical analysis, BITCOIN and behavioral finance is given. Then, in the literature part of the study, studies on BITCOIN prices in the context of behavioral finance and technical analysis are given. In this study, it is examined Relative Strength Index (RSI) availability in Bitcoin transactions and evaluate in the context of behavioral finance findings. For describing the risk of trading in Bitcoin, were chosen Value at Risk (VaR) ratio. In application part of the study it is supposed 1 Bitcoin “Buy” orders were opened when RSI was under 30 and closed when RSI was above 70. And also, 1 Bitcoin “Sell” orders were opened when RSI was above 70 and closed when it was under 30. All obtained data from trades was used for revealing results on accuracy, total profitability. Positive trades were divided by total trades and multiplied by 100 for calculation of accuracy. Period of research is 2015-01-01 till 2019-08-31. As a result of the study we see the effects of biases in Bitcoin transactions. It is observed the examples of conservatism, over and underreaction, status quo effect and loss aversion. And also it is determined in this study that RSI works better in stable market when traders play safer. In other words, RSI works better when conservatism wins over overreaction.
Bu çalışmada, kripto para birimleri arasında piyasada en yüksek hacime sahip olan Bitcoin para biriminin BİST 100, BİST Banka ve BİST Teknoloji endeksi arasında kısa ve uzun dönemde bir ilişkiye sahip olup olmadıkları zaman serisi analiz yöntemleri ile incelenmiştir. Bu amaçla 21/04/2011 ile 11/02/2020 tarihleri arası Bitcoin, BİST 100, BİST Banka ve BİST Teknoloji endeksi değişlerin günlük verileri kullanılmıştır. Çalışmada elde edilen bulgulara göre %5 anlamlılık seviyesinde uzun dönemde Bitcoin fiyatı ile BİST 100 endeksi arasında denge ilişkisine sahipken BİST Banka ve BİST Teknoloji endeksi ile bir ilişkiye rastlanılmamıştır. Buna ilaveten Bitcoin fiyatı ile BİST 100, BİST Banka ve BİST Teknoloji endeksleri kısa dönemde %5 anlamlılık seviyesinde değerlendirildiğinde herhangi bir nedensellik ilişkisine rastlanılmamıştır. Bu bulgular doğrultusunda BİST 100 ile Bitcoin fiyatları arasında uzun dönemde bir ilişkiye sahip olmasından dolayı yatırımcılar açısından Bitcoin’in portföy çeşitlendirilmesinde şu an için riskli bir yatırım tercihi olduğu söylenebilirken bunun yanında uzun dönemde Bitcoin fiyatları ile BİST Banka ve BİST Teknoloji endeksi arasında uzun dönemde ilişkinin olmaması, Bitcoin’in portföy çeşitlendirilmesinde risksiz bir yatırım tercihi olabileceği söylenebilmektedir.
Bitcoin (BTC) is a digital currency that has gained significant attention from researchers. The aim of this paper consists in analyzing some stochastic models of fat-tail returns and risk models. The evidence of fat-tailed returns distribution for the BCH data is investigated, by performing a statistical analysis of Bitcoin Cash (BCH) in the U.S. dollar. By using daily Close, Open, Low, and High returns of BCH data series, the monthly-divided daily returns study describes further properties such as skewness, kurtosis, and correlation analysis. The results obtained prove that variance gamma distribution best fit the close, open and low returns, where high returns follow the generalized hyperbolic distribution. In addition, for the best-fitted fat-tailed returns distributions, several risk measures such as volatility, Value-at-Risk and Expected Shortfall measures are computed, analyzed and compared.
Bu çalışma ile 2019 Aralık ayında Çin Halk Cumhuriyeti’nde ortaya çıkan ve 13 Ocak 2020 tarihinde Covid-19 olarak tanımlanan virüsün tüm Dünya’yı etkilemesi sonucunda, finansal piyasalarda yaşanan kırılma ve değişikliklerin incelenmesi amaçlanmaktadır. Salgın öncesi dönemde yapılan eş bütünleşme analizi sonrası West Texas Ham Petrol fiyatı (WTI), Bitcoin (BTC) ve Euro/Dolar paritesi (EUR) değişkenlerinin aralarında eş bütünleşme ilişkisi olmadığı görülürken, salgın sonrası dönemde ise üç değişken arasında anlamlı bir eş bütünleşme hareketi olduğu belirlenmiştir. Yani, salgın öncesi aralarında eş bütünleşik bir hareket olmayan BTC, EUR ve WTI arasında ortak bir davranış şekli gelişmiş ve eş bütünleşik hareket etmeye başlamışlardır. Salgın öncesi ve sonrası seriler açısından ortalamaların önemli ölçüde değiştiği ve WTI’daki değişimin BTC’de değişimin bir nedeni olduğu, bunun yanı sıra EUR’daki değişiminde WTI fiyatının da bir değişikliğe neden olduğu görülmüştür. Ayrıca yapısal kırılmalı birim kök testlerinden Zivot-Andrews birim kök testi sonucunda, hem WTI hem BTC hem de EUR için covid-19 salgını başlangıcında her hangi bir yapısal kırılma olmadığı sonucuna varılmıştır. İlerleyen dönemde, söz konusu değişkenlerin birbirleriyle olan ilişkilerinin incelenmesi, gerçekleşen dönüşümün devamlılığını anlayabilmek açısından oldukça önemlidir.
This study examines the dynamic nature of return spillover across Bitcoins indices and foreign exchange pairs denominated in 6 major trading currencies. The findings of spillover index, Spillover Asymmetry Measure (SAM) and frequency connectedness methodologies indicate that return spillover across Bitcoin markets and foreign exchange pairs dominated in six major trading currencies is very low. The intra-market return spillover for the Bitcoin markets and foreign exchange pairs is found to be significant. Presence of asymmetry in the return spillover is also found. Evidence indicates that return spillover are dominated in short horizon, with significant spillover occurring within 4 days of an event. The low integration of Bitcoin markets with the foreign exchange markets provide significant implication for portfolio diversification and risk minimization.