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3,636 results · page 126 of 152
VinÃcius Luiz Amaral, Emmanuel T. Affonso, Alisson Marques da Silva, Gray Farias Moita · 5 authors
No abstract is available for this record.
Maximilian-Benedikt Koehn, Andrejs Cekuls
In 2008 a group of programmers, alias Satoshi Nakamoto, introduced bitcoin. Bitcoin is a cryptocurrency \nor virtual money derived from mathematical cryptography and is conceived as an alternative to government authorised \ncurrency. The founder anticipated, through bitcoin’s construction and his digital mining processes, that bitcoin prices \nwould be relatively stable. However, the recent bitcoin price decline proves that bitcoin is extraordinarily volatile and is \nnot that stable as hoped. Although some scientists have already shown that the fundamental value of bitcoin is zero, the \nprice of bitcoin has reached over 19.000$ in December 2018. Since then, bitcoin prices dropped nearly 70% from their \npeak value and showed in addition to that the typical trends of a speculative bubble. \nHyman Minsky and Charles Kindleberger discussed three different patterns of speculative bubbles. One is when price \nrises in an accelerating way and then crashes very sharply after reaching its peak. Another is when the price rises and is \nfollowed by a more similar decline after reaching its peak. The third is when the price rises to a peak, which is then \nfollowed by a period of gradual decline known as the period of financial distress, to be followed by a much sharper crash \nat some later time. One of the key findings of this study is that all these three patterns occurred during 2017-18 for the \nbitcoin price. \nTherefore, the purpose of this paper is to analyse the historical bitcoin prices in context with the typical five-step \ncharacteristics of a speculative bubble. Furthermore, each phase of a speculative bubble is explained by a behavioural \nfinance approach and answer the price development of this cryptocurrency. The result is frightening, bitcoin can be seen \nas a perfect textbook example of a speculative bubble.
Anil Savio Kavuri, Alistair Milne, Justine Wood
No abstract is available for this record.
Sanghyun Bai, Fred C. Robinson
This project uses software development to investigate the link between software and finance. The focus of the work is developing and implementing a trading algorithm which seeks to make profit by making trades based on arbitrage opportunities between currencies. Specifically, the sets of currencies examined are two fiat currencies and one cryptocurrency. Trades are made by combining a blockchain system, which maintains the cryptocurrency, and the live foreign exchange market, which enables fiat currency exchange. The main methodologies for carrying out the research are test-driven development and the use of a simulation to facilitate trades. By passing all of the unit tests, the software is verified. In addition, data gathered during runs of the simulation show that the algorithm successfully identifies arbitrage opportunities and turns a profit on average over many runs. This project proposes an interesting topic for further research in the field of blockchain technology used for financial trading.
Hélyette Geman, Henry Price
No abstract is available for this record.
Paulo VÃtor Jordão da Gama Silva, Augusto F.C. Neto, Marcelo Cabús Klötzle, Antônio Carlos Figueiredo Pinto · 5 authors
Research has shown that behavioral anomalies affect investors' choices and decisions in the financial markets. One such behavioral anomaly is feedback trading, a phenomenon wherein the investor uses past data to make future decisions. Using Sentana and Wadhwani's (1992) methodology, the 50 most liquid digital currencies (with the most extensive daily data reporting) were analyzed during the period 2013–2018. Results analysis suggests negative feedback trading in Tether Dollar and positive feedback trading in Bitcoin, Ethereum, CassinoCoin and ECC.
Paulo VÃtor Jordão da Gama Silva, Marcelo Cabús Klötzle, Antônio Carlos Figueiredo Pinto, Leonardo Lima Gomes
In the 21st century, digital currencies have become a disruptive technology that is shaking up both financial markets and academic environment. Investors, politicians, companies, and academics are attempting to improve their understanding of these currencies for future investment possibilities and technological applications. This study aims to evaluate changes in different volatility states of eight digital currencies (BTC, ETH, LTC, XRP, XMR, NEM, LISK, and STEEM) that showed the highest liquidity and market capitalisation from 2013 to 2017. The methodology involved the MSGARCH model, using SGARCH, EGARCH, GJRGARCH, and TGARCH models. Our study demonstrated that two volatility regimes, that is, one with a larger volatility and another with a smaller one, clearly exist for all the analysed cryptocurrencies. What differs between the currencies is the probability of a second regime occurring. Moreover, we concluded that for both the first and second state, the asymmetry coefficient (gamma) is positive for all currencies.
Agata Kliber, Katarzyna WÅ‚osik
The aim of this research is to investigate interdependencies between leading cryptocurrency exchanges (American, European and Japanese ones). We examine price and volume spillovers of daily frequency, to answer the question whether these platforms are integrated one with another or whether they form different isolated clusters. The results show that the big exchanges are indeed closely linked one to another. However, the magnitude of spillovers is higher in the case of prices, compared to volume. We also find that the analysed markets react with the same intensity to the price shocks coming from the other markets as to their own shocks. They are, however, more isolated in terms of volume spillovers.
Angelika Kokkinaki, Svetlana Sapuric, Ifigenia Georgiou
No abstract is available for this record.
David Procházka
No abstract is available for this record.
John Abonongo, Anuwoje Ida Logubayom, Raymond Nero
This paper explores the half-life volatility measure of three cryptocurrencies (Bitcoin, Litecoin and Ripple). Two GARCH family models were used (PGARCH (1, 1) and GARCH (1, 1)) with the student-t distribution. It was realised that, the PGARCH (1, 1) was the most appropriate model. Therefore, it was used in determining the half-life of the three returns series. The results revealed that, the half-life was 3 days, 6 days and 4 days for Bitcoin, Litecoin and Ripple respectively. This shows that, the three coins have strong mean reversion and short half-life and that it takes the respective days for volatility in each of coin to return half way back without further volatility.
Daniel Traian Pele, Niels Wesselhöfft, Wolfgang Karl Härdle, Michalis Kolossiatis · 5 authors
The aim of this paper is to prove the phenotypic convergence of cryptocurrencies, in the sense that individual cryptocurrencies respond to similar selection pressures by developing similar characteristics. In order to retrieve the cryptocurrencies phenotype, we treat cryptocurrencies as financial instruments (genus proximum) and find their specific difference (differentia specifica) by using the daily time series of log-returns. In this sense, a daily time series of asset returns (either cryptocurrencies or classical assets) can be characterized by a multidimensional vector with statistical components like volatility, skewness, kurtosis, tail probability, quantiles, conditional tail expectation or fractal dimension. By using dimension reduction techniques (Factor Analysis) and classification models (Binary Logistic Regression, Discriminant Analysis, Support Vector Machines, K-means clustering, Variance Components Split methods) for a representative sample of cryptocurrencies, stocks, exchange rates and commodities, we are able to classify cryptocurrencies as a new asset class with unique features in the tails of the log-returns distribution. The main result of our paper is the complete separation of the cryptocurrencies from the other type of assets, by using the Maximum Variance Components Split method. More, we observe a divergent evolution of the cryptocurrencies species, compared to the classical assets, mainly due to the tails behaviour of the log-returns distribution. The codes used here are available via www.quantlet.de.
Junjie Hu, Weiyu Kuo, Wolfgang K. Härdle
Cryptocurrency, the most controversial and simultaneously the most interesting asset, has attracted many investors and speculators in recent years. The visibly significant market capitalization of cryptos also motivates modern financial instruments such as futures and options. Those will depend on the dynamics, volatility, or even the jumps of cryptos. We provide a comprehensive investigation of the risk dynamics of the Bitcoin Market from a realized volatility perspective. The Bitcoin market is extremely risky in the sense of volatility, entangled jumps, and extensive consecutive jumps, which reflect the major incidents worldwide. Empirical study shows that the lagged realized variance increases the future realized variance, while the jumps, especially positive ones, significantly reduce future realized variance. The out-of-sample forecasting model reveals that, in terms of forecasting accuracy and utility gain, investors interested in the long-term realized variance benefit from explicitly modelling the jumps and signed estimators, which is unnecessary for the short-term realized variance forecast.
Georgiana-Loredana Schipor
The financial industry is subject to a new technological age through the evolution of the cryptocurrencies, people exploring a continuous rise of interest in investing on alternative basis mechanisms. This paper aims to give an overview of the blockchain technology and its potential, with its applicability on the cryptocurrency market. We illustrate the main challenges that the cryptocurrencis must overcome in order to achieve the customers’ approval, which is strongly related to trust and cybersecurity issues. A comparative analysis of the two major cryptocurrencies emphasizes the risks and the opportunities offered by the cryptocurrency market, but also the main threats that must be addressed. Moreover, the consequences of the cryptocurrencies development for both national and international financial systems are evaluated, leading to the idea of a freedom-associated concept, where the lack of a third-party financial authority requires a significant change of perceptions and has the premises to fundamentally transform the traditional payment methods.
Liuqing Yang, Xiao-Yang Liu, Xinyi Li, Yinchuan Li
No abstract is available for this record.
Siddharth M. Bhambhwani, Stefanos Delikouras, George M. Korniotis
No abstract is available for this record.
Alexander Brauneis, Roland Mestel, Ryan Riordan, Erik Theissen
No abstract is available for this record.
Thabo J. Gopane
No abstract is available for this record.
Mariana Durcheva, Pavel Tsankov
We investigate similarities and differences between stock and cryptocurrency networks obtained from log-return and volatility time series. We constructed correlation and Fast Fourier Transform based graphs and minimum spanning trees from a set of 100 highly capitalized cryptocurrencies and 100 highly capitalized NASDAQ stocks over a time window of fixed length. Our analysis is based on comparison between both economies in terms of network properties. We also examined distributions of node degrees and edge weights. Our results show that cryptocurrencies and companies with high capitalization tend to correspond to central and densely connected nodes. Network topologies for both economies and node degree distributions are rather similar. Nevertheless, the crypto-economy is more correlated and more strongly linked to important nodes, unlike the graphs of NASDAQ stocks, where we observed clusters of nodes having small dissimilarities.
Shaista Bibi, Shahid Hussain, Muhammad Imran Faisal
Cryptocurrency is one of the emerging online currency of the modern era. Big companies are investing in this technology. However, some established companies still hesitate to use it. According to them, it is a volatile trend which will fade up eventually. There is no such authority which will provide them feasibility information. So, investors can be helped by providing them feasibility information about locations for cryptocurrency investment around the world. This paper aims to provide the aforementioned information to the investors. The proposed methodology is based on Topic modeling along with public opinion mining about cryptocurrencies, blockchain network, bitcoin, litecoin, and ethereum. The crawled data for other cryptocurrencies are much insufficient, so that are excluded from the study. In the proposed methodology, the top locations where cryptocurrency is widely used are identified, then in that particular locations' users concerns along with their sentiment analyses are investigated. Top locations are identified such as Australia, Denmark, Netherlands, and the USA etc. Almost 83.7% tweets of Sweden show positive sentiment for cryptocurrency investment which ranks as the highest having friendly environment for cryptocurrency investment. Similarly, the UK shows the least positive perception of cryptocurrency and blockchain technology usage. Some of the noteworthy terms found are legitimacy, authorization rules, volatility, profit, investment, and fluctuations. Which describe the users' concerns/ interests' about cryptocurrency. Investors can focus on all these areas during business. These subtopics can help business experts to evolve their businesses' and to make them more sustainable on the basis of public perception.
Niranjan Sapkota, Klaus Grobys
This paper explores whether asset market equilibria in cryptocurrency markets do exist. In doing so, it distinguishes between privacy and non-privacy coins. Most recently, privacy coins have attracted increasing attention in the public debate as non-privacy cryptocurrencies, such as Bitcoin, do not satisfy some users’ demands for anonymity. Analyzing ten cryptocurrencies with the highest market capitalization in each submarket in the 2016–2018 periods, we find that privacy coins exhibit a distinct market equilibrium. Contributing to the current debate on the market efficiency of cryptocurrency markets, our findings provide evidence of market inefficiency. Moreover, the asset market equilibrium of privacy coins appears to originate from non-privacy coins with highest market capitalizations. We argue that the reason for this finding could be that non-privacy coins may be the first choice for criminals who might prefer cryptocurrencies exhibiting both a high level of anonymity and liquidity.
Amélie Charles, Olivier Darné
In this paper we study the daily volatility of four cryptocurrencies (BitCoin, Dash, LiteCoin, and Ripple) from June 2014 to November 2018. We first show that the cryptocurrency returns are strongly characterized by the presence of jumps as well as structural breaks (except Dash). Then, we estimate four GARCH-type models that capture short memory (GARCH), asymmetry (APARCH), strong persistence (IGARCH), and long memory (FIGARCH) from (i) original returns, (ii) jump-filtered returns, and (iii) jump-filtered returns with structural breaks. Results indicate the importance to take into account the jumps and structural breaks in modelling volatility of the cryptocurrencies. It appears that the cryptocurrency returns are well modelled by infinite persistence (BitCoin, Dash, and LiteCoin) or long memory (Ripple) with a Student-t distribution.
Carey Caginalp, Gunduz Caginalp
We utilize optimization methods to determine equilibria of cryptocurrencies. A core group, the wealthy, fears the loss of assets that can be seized by a government. Volatility may be influenced by speculators. The wealthy must divide their assets between the home currency and the cryptocurrency, while the government decides the probability of seizing a fraction the assets of this group. We establish conditions for existence and uniqueness of Nash equilibria. Also examined is the separate timescale problem in which the government policy cannot be reversed, while the wealthy can adjust their allocation in reaction to the government's designation of probability.
Nader Virk
Integration patterns between five leading conventional currencies after the US dollar and Bitcoin boost the investment potential of the latter relative to its hedging potential. We document that conditional Bitcoin volatility does not influence its dynamic pairwise correlations whereas the change in volatility of conventional currencies do affect the forex market integration patterns.