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2,335 results · page 68 of 98
Victoria Dobrynskaya
No abstract is available for this record.
Nicolás Cachanosky
This chapter studies the challenges a cryptocurrency faces to become a common means of exchange. In particular, the paper discusses the scalability constraint that limits the number of transactions a cryptocurrency may be able to verify per unit of time, the network effect in goods that function as money that increases the cost of new currencies to gain market share, and the implications of the fixed monetary rule present in most cryptocurrencies that departs from an elastic optimal monetary policy. Potential solutions for each case are also discussed.
Stéphane Goutte, Benjamin Keddad
No abstract is available for this record.
Chuanhai Zhang, Huan Ma
No abstract is available for this record.
Nora Chiriță, Ionuț Nica
The global economy can be regarded as a complex global adaptive system, which adapts and evolves according to the environment and the behavior of the agents existing on the market. A topic that is topical and can even affect the welfare of a country is the field of cryptocurrencies. Today, the most well-known phenomenon by people in this field is the emergence of bitcoin. Cryptocurrencies or virtual currencies are an emanation of the financial crisis that started in 2008, a crisis that had led to a decline in confidence of traditional bank. In this paper, we discussed the creation of possible speculative bubbles, we presented the virtual currencies, we applied techniques of multidimensional analysis of the data for their analysis, and we evaluated the effects that the appearance of the cryptocurrencies had on the cybernetic economic system in Romania. Also, the paper deals with a section on identifying risks in the field of cryptocurrencies. In the last part of this paper, we focus our attention on the viability of these coins and their future prospects.
Alexander Chang, William Herrmann, Wlliam Cai
No abstract is available for this record.
Sanja Dončić
The paper examines the existence of a causal relationship in Grangers' sense between the movement of Bitcoin prices and the price of gold at the global financial market, in order to answer the question whether it is possible to predict the movement of the Bitcoin price based on the movement of the price of gold in the world market, but also vice versa. The survey was conducted from January 1, 2019 to December 1, 2019. In the research was used the Granger causality test (1969). The research results show that historical data on the movement of gold prices in the world market cannot be used to predict the change in value and price movements of Bitcoin. On the other hand, the survey results indicate the possibility of a reliable application of the use of historical data on the movement of value and price of Bitcoin.
Nektarios Aslanidis, Aurelio F. Bariviera, Christos S. Savva
This paper adopts a versatile multivariate conditional correlation model to estimate daily seasonality in the returns, the volatility, and the correlations between stocks, bonds, gold and Bitcoin. Besides the well known seasonality in stocks and bonds, the day-of-the-week effect is also present in Bitcoin. Mondays are associated with higher Bitcoin returns, while Wednesdays with higher Bitcoin volatility. As opposed to previous literature, our results indicate strong evidence of Bitcoin’s leverage effect. Moreover, we show that daily correlations between Bitcoin and traditional assets are higher at the beginning of the week, while the volatility of these correlations decreases over the week. Our results offer interesting insights in terms of investment and portfolio diversification, that can be applied to the analysis of systematic risk asset allocation and hedging. Keywords: Day-of-the-week effect; dynamic conditional correlation; Bitcoin; volatility seasonality. JEL codes: G01; G10; G12; G22
Kwok Ping Tsang, Zichao Yang
Bitcoin is traded in a number of exchanges, and there is a large and time-varying price dispersion among them. We identify the sources of price dispersion using a standard time-varying vector auto-regression model with stochastic volatility. Using weekly data over the past 3 years, we find that shocks to transaction fees and bitcoin price growth explain on average 20%, and sometimes more than 60%, of the variation of price dispersion. We argue that the two variables are related to the profitability and risk of trading across the exchanges, and the impulse response functions are consistent with our interpretation.
Dirk G. Baur, Thomas Dimpfl
No abstract is available for this record.
Brian Kachnowski
No abstract is available for this record.
İhsan Erdem Kayral
Finansal zaman serilerinde görülen değişen varyans sorununun (ARCH etkisi) sonucu olarak otoregresif koşullu değişen varyans modelleri bulunmuştur. Çalışmamızda, piyasa değeri en yüksek üç kripto paranın [Bitcoin (BTC), Ethereum (ETH) ve Ripple (XRP)] getirileri incelenmiş ve söz konusu getirilerde finansal zaman serilerine benzer şekilde ARCH etkisi bulunmuştur. Söz konusu üç kripto paranın volatiliteleri için en iyi modelin hesaplanmasında altı GARCH modelini karşılaştırılmıştır. Bu modeller sırasıyla GARCH (1,1), EGARCH (1,1), TGARCH (1,1), APARCH (1,1), CGARCH (1,1) ve ACGARCH (1,1) modellerinden oluşmaktadır. Çalışma kapsamında 01.10.2015 - 01.10.2018 tarihleri arasında Bitcoin (BTC), Ethereum (ETH) ve Ripple (XRP) kripto paralarının günlük kapanış verilerinden elde edilen getiriler kullanılmıştır. Volatilite tahminlerinde Bitcoin (BTC) ve Ethereum (ETH) için en iyi model EGARCH (1,1), Ripple (XRP) için ise APARCH (1,1) modeli bulunmuştur. Çalışma kapsamında bu modeller kullanılarak volatiliteler üzerinde negatif şokların pozitif şoklardan daha fazla etkisinin bulunduğunu gösteren kaldıraç etkisi incelenmiştir. Bitcoin (BTC) ve Ethereum (ETH) modellerinde kaldıraç etkisi bulunmamış, bununla birlikte pozitif şoklar negatif şoklara göre daha fazla volatiliteye neden olmuştur. Ancak, Ripple (XRP) volatilite modelinde kaldıraç etkisi belirlenmiştir.
Audil Rashid Khaki, Somar Al-Mohamad, Walid Bakry
No abstract is available for this record.
Yimiao Chen, Leh-chyan So
Recently, cryptocurrencies have drawn considerable attention from investors around the world. Such digital assets have also raised numerous hot issues in academic fields. Among them, Bitcoin is the most well-known and most notorious. After it was created in 2009, Bitcoin kept rising in price and reached its peak in late 2017. After that, it plunged dramatically. Coincidentally, Bitcoin futures also launched in December 2017. We are curious about the role Bitcoin futures play in the Bitcoin market. In this study, we investigate the relationship between Bitcoin and Bitcoin futures. First, we compare the optimal hedge ratios using three different hedge strategies, the na?ve hedge, the ordinary least squares (OLS) method, and dynamic hedging with the bivariate BEKK-GJR-GARCH model. Dynamic hedging is the most effective of the three methods; the level of risk reduction is around 59%. Then we test whether the volatility of Bitcoin would be significantly different before and after Bitcoin futures (BTC) launched. Our results support the hypothesis.
Jürgen E. Schatzmann, Bernhard Haslhofer
Investors tend to sell their winning investments and hold onto their losers. This phenomenon, known as the \\emph{disposition effect} in the field of behavioural finance, is well-known and its prevalence has been shown in a number of existing markets. But what about new atypical markets like cryptocurrencies? Do investors act as irrationally as in traditional markets? One might suspect this and hypothesise that cryptocurrency sells occur more frequently in positive market conditions and less frequently in negative market conditions. However, there is still no empirical evidence to support this. In this paper, we expand on existing research and empirically investigate the prevalence of the disposition effect in Bitcoin by testing this hypothesis. Our results show that investors are indeed subject to the disposition effect, tending to sell their winning positions too soon and holding on to their losing position for too long. This effect is very prominently evident from the boom and bust year 2017 onwards, confirmed via most of the applied technical indicators. In this study, we show that Bitcoin traders act just as irrationally as traders in other, more established markets.
Evans Rozario, Samuel Holt, James West, Shaun Ng
Cryptocurrency markets have many of the characteristics of 20th century commodities markets, making them an attractive candidate for trend following strategies. We present a decade of evidence from the infancy of bitcoin, showcasing the potential investor returns in cryptocurrency trend following, 255% walkforward annualised returns. We find that cryptocurrencies offer similar returns characteristics to commodities with similar risk-adjusted returns, and strong bear market diversification against traditional equities. Code available at https://github.com/Globe-Research/bittrends.
Soon Hyeok Choi, Robert A. Jarrow
No abstract is available for this record.
Hamed Ghoddusi, Mohammad Morovati, Nima Rafizadeh
No abstract is available for this record.
Q. K. N. Chan, Wenzhi Ding, Chen Lin, Alberto G. Rossi
No abstract is available for this record.
Vladimir Soloviev, Oleksandr SERDIUK
The possibility of constructing dynamic measures of complexity as quantum econophysical behaving in a proper way during actual pre-crash periods has been shown. This fact is used to build predictors of crashes and critical events phenomena on the examples of all the patterns recorded in the time series of the key cryptocurrency Bitcoin, the effectiveness of the proposed indicatorsprecursors of these falls has been identified. From positions, attained by modern theoretical physics the concept of economic Plank's constant has been proposed.
Anantha Divakaruni, Peter Zimmerman
We show that recent technological innovations have significantly improved the efficiency of Bitcoin as a means of payment. We study three particular innovations: the Lightning Network, a means of netting payments off the blockchain; SegWit, an improvement to the way data are stored on the blockchain; and Bitcoin Cash, a new cryptocurrency forked from Bitcoin. We find a robust and significant association between adoption of the Lightning Network and reduced blockchain congestion. This improvement cannot be explained by other factors, such as changes in speculative demand for Bitcoin. We show that the Lightning Network has become increasingly centralised, with payments channelled through relatively few intermediaries. Finally, we argue that improved functioning of Bitcoin is positive for welfare, and may reduce the environmental footprint of Bitcoin mining.
Ana Fernández Vilas, Rebeca P. Dı́az Redondo, Anton Lorenzo Garcia
There is a consensus about the good sensing characteristics of Twitter to mine and uncover knowledge in financial markets, being considered a relevant feeder for taking decisions about buying or holding stock shares and even for detecting stock manipulation. Although Twitter hashtags allow to aggregate topic-related content, a specific mechanism for financial information also exists: Cashtag (consisting of the company ticker preceded by $) is a supporting mechanism to track financial tweets referring to a company listed in a stock market. However, according to our experiments and due to the lack of conventions in cashtags usage, the irruption of cryptocurrencies has resulted in a significant degradation on the cashtag-based aggregation of posts. Unfortunately, Twitter' users may use homonym tickers to refer to cryptocurrencies and to companies in stock markets, which means that filtering by cashtag may result on both posts referring to stock companies and cryptocurrencies. This research proposes automated classifiers to distinguish conflicting cashtags and, so, their container tweets by analyzing the distinctive features of tweets referring to stock companies and cryptocurrencies. As experiment, this paper analyses the interference between cryptocurrencies and company tickers in the London Stock Exchange (LSE), specifically, companies in the main and alternative market indices FTSE-100 and AIM-100. Heuristic-based as well as supervised classifiers are proposed and their advantages and drawbacks, including their ability to self-adapt to Twitter usage changes, are discussed. The experiment confirms a significant distortion in collected data when colliding or homonym cashtags exist, i.e., the same $ acronym to refer to company tickers and cryptocurrencies. According to our results, the distinctive features of posts including cryptocurrencies or company tickers support accurate classification of colliding tweets (homonym cashtags) and Independent Models, as the most detached classifiers from training data, have the potential to be trans-applicability (in different stock markets) while retaining performance.
Tobias A. Huber, Didier Sornette
Bitcoin represents one of the most interesting technological breakthroughs and socio-economic experiments of the last decades. In this paper, we examine the role of speculative bubbles in the process of Bitcoin's technological adoption by analyzing its social dynamics. We trace Bitcoin's genesis and dissect the nature of its techno-economic innovation. In particular, we present an analysis of the techno-economic feedback loops that drive Bitcoin's price and network effects. Based on our analysis of Bitcoin, we test and further refine the Social Bubble Hypothesis, which holds that bubbles constitute an essential component in the process of technological innovation. We argue that a hierarchy of repeating and exponentially increasing series of bubbles and hype cycles, which has occurred over the past decade since its inception, has bootstrapped Bitcoin into existence.
Aurelio F. Bariviera, Ignasi Merediz‐Solà
This survey develops a dual analysis, consisting, first, in a bibliometric examination and, second, in a close literature review of all the scientific production around cryptocurrencies conducted in economics so far. The aim of this paper is twofold. On the one hand, proposes a methodological hybrid approach to perform comprehensive literature reviews. On the other hand, we provide an updated state of the art in cryptocurrency economic literature. Our methodology emerges as relevant when the topic comprises a large number of papers, that make unrealistic to perform a detailed reading of all the papers. This dual perspective offers a full landscape of cryptocurrency economic research. Firstly, by means of the distant reading provided by machine learning bibliometric techniques, we are able to identify main topics, journals, key authors, and other macro aggregates. Secondly, based on the information provided by the previous stage, the traditional literature review provides a closer look at methodologies, data sources and other details of the papers. In this way, we offer a classification and analysis of the mounting research produced in a relative short time span.