Follow blockchain research across journals, conferences, and preprint repositories.
4,843 results · page 187 of 202
Gerrit Köchling, Janis Müller, Peter N. Posch
No abstract is available for this record.
Alexandre Sokic
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.
Ouael El Jebari, Abdelati Hakmaoui
We propose in this article to study the behavior of investors in the bitcoin market in order to test whether investors' overconfidence is a driver of excess volatility, often associated with the aforementioned market. This paper presents an attempt to deepen the previously published studies by adopting a new ARMA(p,q)-FIEGARCH(1,d,k,1) parametrization capable of capturing the overconfidence element as well as simultaneously accounting for possible long memory effect. The data used in this study consists of daily closing prices along with daily exchange volume of Bitcoin, spanning the period ranging from 01/01/2012 up to 31/05/2018. The results and conclusions drafted in this research paper could help to understand the formation of volatility in the Bitcoin market. Therefore, this kind of studies will enable investors to better predict bubbles and irrational exuberances. The main contribution of the present article is drawn from the broadening of previous studies by adopting a newly constructed model, which combines capturing asymmetric response, long memory along with the overconfidence element.
Jules Clément, Edson Pindza, Ur Koumba
No abstract is available for this record.
Debojyoti Das, M. Kannadhasan
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
Burcu Kapar, José Olmo
No abstract is available for this record.
Theodore Panagiotidis, Thanasis Stengos, Orestis Vravosinos
We review the literature and examine the effects of shocks on bitcoin returns. We assess the effects of factors such as stock market returns, exchange rates, gold and oil returns, FED's and ECB's rates and internet trends on bitcoin returns. Alternative VAR and FAVAR models are employed and generalized as well as local impulse response functions are produced. Our results reveal (i) a significant interaction between bitcoin and traditional stock markets, (ii) a weaker interaction with FX markets and the macroeconomy and (iii) an anemic importance of popularity measures. Lastly, we reveal the increased impact of Asian markets on bitcoin compared to other geographically-defined markets, which however appears to have waned in the last two years after the Chinese regulatory interventions and the sudden contraction of CNY's share in bitcoin trading volume.
Chih‐Hung Wu, Chih-Chiang Lu, Yu-Feng Ma, Ruei-Shan Lu
Long short-term memory (LSTM) networks are a state-of-the-art sequence learning in deep learning for time series forecasting. However, less study applied to financial time series forecasting especially in cryptocurrency prediction. Therefore, we propose a new forecasting framework with LSTM model to forecasting bitcoin daily price with two various LSTM models (conventional LSTM model and LSTM with AR(2) model). The performance of the proposed models are evaluated using daily bitcoin price data during 2018/1/1 to 2018/7/28 in total 208 records. The results confirmed the excellent forecasting accuracy of the proposed model with AR(2). The test mean squared error (MSE), root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) for bitcoin price prediction, respectively. The our proposed LSTM with AR(2) model outperformed than conventional LSTM model. The contribution of this study is providing a new forecasting framework for bitcoin price prediction can overcome and improve the problem of input variables selection in LSTM without strict assumptions of data assumption. The results revealed its possible applicability in various cryptocurrencies prediction, industry instances such as medical data or financial time-series data.
Thomas Dimpfl, Franziska J. Peter
No abstract is available for this record.
Max J. Krause, Thabet Tolaymat
No abstract is available for this record.
Nader Trabelsi
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.
Amitha Raghava-Raju
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.
Pedro Chaim, Márcio Poletti Laurini
No abstract is available for this record.
Faisal Nazir Zargar, Dilip Kumar
No abstract is available for this record.
Angelo Corelli
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.
Dimitrios Koutmos
No abstract is available for this record.
Gregor Dorfleitner, Carina Lung
No abstract is available for this record.
Paraskevi Katsiampa
No abstract is available for this record.
Елена Федорова, K. Z. Bechvaya, Oleg Y. Rogov
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.
Ravi Kishore Kodali, Subbachary Yerroju, Borra Yatish Krishna Yogi
In 21stcentury one of the revolutionary technologies is Blockchain. It can bring regularity ideas to public and private sectors which improve the present management failures. To permit peer-to-peer transactions, Blockchiain maintains continuously growing list of records as a distributive database. In future, the existing conventional energy sources cannot meet the electricity demand. The renewable electricity generation is growing to balance supply and demand and accounts to share in the overall power supply. In the concept of smart cities development, The energy distribution without any intermediaries has a major concern. This emerging blockchain technology provides distributive and decentralized solutions for energy transactions. In this paper, a permissioned blockchain that uses hyperledger fabric to provide a peer-to-peer energy transacting network in order to accommodate the growing volume of renewable energy supply.
Е. Надырова
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.
NashirahAbu Bakar, Sofian Rosbi
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.
Emrah Öget, Ersin Kanat
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.