Follow blockchain research across journals, conferences, and preprint repositories.
3,636 results · page 124 of 152
Darko Stošić, Dušan Stošić, Dušan Stošić, Tatijana Stošić · 6 authors
No abstract is available for this record.
Higor Y. D. Sigaki, Matjaž Perc, Haroldo V. Ribeiro
The efficient market hypothesis has far-reaching implications for financial trading and market stability. Whether or not cryptocurrencies are informationally efficient has therefore been the subject of intense recent investigation. Here, we use permutation entropy and statistical complexity over sliding time-windows of price log returns to quantify the dynamic efficiency of more than four hundred cryptocurrencies. We consider that a cryptocurrency is efficient within a time-window when these two complexity measures are statistically indistinguishable from their values obtained on randomly shuffled data. We find that 37% of the cryptocurrencies in our study stay efficient over 80% of the time, whereas 20% are informationally efficient in less than 20% of the time. Our results also show that the efficiency is not correlated with the market capitalization of the cryptocurrencies. A dynamic analysis of informational efficiency over time reveals clustering patterns in which different cryptocurrencies with similar temporal patterns form four clusters, and moreover, younger currencies in each group appear poised to follow the trend of their 'elders'. The cryptocurrency market thus already shows notable adherence to the efficient market hypothesis, although data also reveals that the coming-of-age of digital currencies is in this regard still very much underway.
Luisanna Cocco, Roberto Tonelli, Michele Marchesi
In this paper, we present an analysis of the mining process of two popular assets, Bitcoin and gold. The analysis highlights that Bitcoin, more specifically its underlying technology, is a “safe haven” that allows facing the modern environmental challenges better than gold. Our analysis emphasizes that crypto-currencies systems have a social and economic impact much smaller than that of the traditional financial systems. We present an analysis of the several stages needed to produce an ounce of gold and an artificial agent-based market model simulating the Bitcoin mining process and allowing the quantification of Bitcoin mining costs. In this market model, miners validate the Bitcoin transactions using the proof of work as the consensus mechanism, get a reward in Bitcoins, sell a fraction of them to cover their expenses, and stay competitive in the market by buying and divesting hardware units and adjusting their expenses by turning off/on their machines according to the signals provided by a technical analysis indicator, the so-called relative strength index.
Z. Mierzwa, З. Межва
The paper deals with the problems of measuring uneven wealth distribution in the bitcoin ecosystem. All existing bitcoin distribution models depend on the analysis of bitcoin wallets and bitcoin addresses. They are based on the Bitcoin Rich List. This approach is insufficient due to the inscrutable relationships between people owning bitcoin, bitcoin wallets, and bitcoin addresses. In this paper, we used the methods of comparative analysis resulted in graphics as represented by Lorentz and Lame curves and distribution of the Gini coefficients and the Kolkata index. We identified empirical cumulative functions of wealth distribution and the number of addresses with positive balance during the bubble and after its explosion. Approximations of the distribution of ‘poor’ and ‘rich’ addresses have been obtained and compared with the other results from the cited literature. The general public views the equality of network members as synonymous with the equal distribution of wealth among them. Emerging financial bubbles, especially in the US financial markets, lead to an increase in income inequality. However, after a bubble explodes, the inequality falls to the initial level. В статье рассматриваются проблемы измерения неравномерности распределения богатства в экосистеме биткоин. Все существующие модели распределения биткоин зависят от анализа биткоин-кошельков и биткоин-адресов. Они основаны на богатом списке биткоинов. Такого подхода недостаточно из-за непостижимых отношений между людьми, владеющими биткоинами, биткоин-кошельками и биткоин-адресами. В работе нами использовались методы сравнительного анализа с графическим изображением результатов в виде кривых Лоренца, Ламе и распределения коэффициентов Джини и индекса Кольката. Авторы определили эмпирические кумулятивные функции распределения богатства и количества адресов с положительным балансом во время пузыря и после его взрыва. Получены аппроксимации распределения «бедных» и «богатых» адресов и сделано их сравнение с другими результатами, представленными в цитируемой литературе. Широкая общественность рассматривает равенство членов сети как синоним относительно равного распределения богатства между ними. Появление финансовых пузырей, в особенности на финансовых рынках США, приводит к увеличению неравенства доходов, но после краха пузыря неравенство падает до начального уровня
У. В. Шилович
The article considers the actual problem of using cryptocurrencies in the sphere of financial relations, also it analyzes the main features of cryptocurrency, as well as legislative assurance of it in the Republic of Belarus.
Višnja Jurić, Vanja Šimičević, Domagoj Kajba
No abstract is available for this record.
Zhongxue Chen, Dominic Lewinski, Guoyi Zhang, Yiming Yang
The cryptocurrency market is different from traditional markets due to its unique property, which allows global trading around the clock. It is of interest to investigate if some traditional stock market phenomena still exist in the cryptocurrency markets. In this research, we studied the application of the 75% reversion rule in cryptocurrency markets. Using local linear regression, we identified active markets at certain time and location, and examined government regulations and news' influence on the cryptocurrency markets.
Jun Deng, Huifeng Pan, Shuyu Zhang, Bin Zou
No abstract is available for this record.
Frida Gustafsson, Elias Bengtsson
No abstract is available for this record.
Andrejs Cekuls, Maximilian-Benedikt Koehn
The market of virtual currencies, called cryptocurrency, has grown immensely since 2008 in terms of market \ncapitalisation and the numbers of new currencies. Bitcoin is one of the most famous cryptocurrency with an estimated \nmarket capitalisation of nearly $ 69 billion. The fact that Bitcoin prices have fallen about 70% from their peak value and \nmost indices were down double-digit year to date (2018) with a high daily volatility create the appearance that there has \nto be a correlation. \nThe purpose of this paper is to investigate the contagion effect between Bitcoin prices and the leading American, \nEuropean and Asian equity markets using the dynamic conditional correlation (DCC) model proposed by Engle and \nSheppard (2001). \nContagion is defined in this context as the statistical break in the computed DCCs as measured by the shifts in their \nmeans and medians. Even it is astonishing that the contagion is lower during price bubbles, the main finding indicates the \npresence of contagion in the different indices among the three continents and proves the presence of structural changes \nduring the Bitcoin bubble. Moreover, the analysis shows that specific market indices are more correlated with the Bitcoin \nprice than others.
Jackie Johnson
No abstract is available for this record.
Ruozhou Liu, Shanfeng Wan
No abstract is available for this record.
Usman W. Chohan
No abstract is available for this record.
Carol Alexander, Arben Imeraj
No abstract is available for this record.
Tolga ULUSOY, Mehmet Yunus Çelik
No abstract is available for this record.
Murat AKBALIK, Melis Zeren, Ömer Sarıgül
No abstract is available for this record.
David Suda, Luke Spiteri
No abstract is available for this record.
Kiril Desev, Stanimir Kabaivanov, Desislav Desevn, Kiril Desev · 6 authors
This paper analyses the efficiency of cryptocurrency markets by applying econometric models to different short-term investment horizons. A number of experiments are carried out to demonstrate that small training sets can still be used to build efficient and useful forecasts, which in turn can be transformed into straight-forward investment strategies. It also compares the application of selected models on cryptocurrency and mature stock markets. The forecasting accuracy of the models is explored using different error metrics and different horizons. The results suggest that the variation of the error estimates doesn’t appear to be tightly related to the maturity of the markets, but rather depends on the intrinsic characteristics of the analyzed time series.
Efe Çağlar Çağlı
No abstract is available for this record.
Klaus Grobys, Niranjan Sapkota
No abstract is available for this record.
Aifan Ling, Zhikai Zhu
No abstract is available for this record.
Phan Duy Hung, Tran Quang Thinh
No abstract is available for this record.
Julian Barreiro‐Gomez, Hamidou Tembiné
This paper studies the blockchain cryptographic tokens by means of mean-field-type game theory. It introduces the variance-aware utility function per decision-maker to capture the risk of cryptographic tokens associated with the uncertainties of technology adoption, network security, regulatory legislation, and market volatility. We establish a relationship between the network characteristics, token price, number of token holders, and token supply. Both in-chain diversification and cross-chain diversification among tokens are examined by using a mean-variance approach. The results suggest that the number of tokens in circulation needs to be adjusted in order to capture risk-awareness and self-regulatory behavior in blockchain token economics. The Sharpe and Modigliani ratios for cryptographic tokens are revisited.
Gianna Figà‐Talamanca, Sergio M. Focardi, Marco Patacca
No abstract is available for this record.