Blockchain Papers

Thibault Schrepel

No abstract is available for this record.

Brian Kachnowski

No abstract is available for this record.

Luiz Almeida Sampaio Filho

The behavior of the foreign exchange and cryptocurrency markets was studied from the perspective of the theory of dynamical systems. Using the phase space reconstruction procedure under the validity of Takens' theorem (1981). The presence of serial dependence was investigated through the BDS test, the property of sensitivity to initial conditions through the Lyapunov maximum exponent and the distinction between deterministic and stochastic signals observing the behavior of the E2(d) function in Cao's method (1997). Evaluating 17 exchange rate log-return series, evidence of serial dependence, possibly non-linear, was found in 11 of them. As for sensitivity to initial conditions, no series has shown conclusive results on such a property. All series presented evidence that they follow processes of a random nature and non-Gaussian increments, in the same way as the cryptocurrency log-return series. Of the 10 series of cryptocurrencies, the IID hypothesis was rejected for 8 of them, and none presented a conclusive result regarding a positive Lyapunov exponent. As a conclusion, no consistent characteristics of chaotic dynamics were found for the foreign exchange and digital currency markets in the analyzed period.

Antonis Ballis, Κωνσταντίνος Δράκος

No abstract is available for this record.

N. Shashidhar, Sourav Mahmood Sagar, Rachana Patil, Suraj Rk

To assess the Bitcoin cost absolutely considering divergent parameters that effect the Bitcoin esteem. In this work, we indicated grasp and recognize progressively changes in Bit Coin showcase while acquiring observation into most proper qualities encompassing Bitcoin cost. We anticipate the everyday value change with endorsing conceivable precision. The market finances of traded on an open market cryptographic forms of money at present above $230 billion. Bitcoin is most valuable cryptographic money, fills as an advanced store of significant worth, and its value consistency has been well-looked into. These attributes are appeared in the accompanying subdivision; the fundamental subtleties of Bitcoin

Ryuta Sakemoto

This study proposes a method to enhance cryptocurrency portfolios constructed by forecast models. This study forecasts returns on four liquid cryptocurrencies (Bitcoin, Litecoin, Ripple, and Dash) and determines the weights on the cryptocurrencies based upon a dynamic allocation framework. We assess the performances of the portfolios using the performance fee measure. Our results present that the proposed portfolios outperform the benchmark portfolio with the conventional level of the risk aversion parameter. The economic gain for an investor is equivalent to 12% per week. The economic gain is sensitive to a change in the risk aversion parameter, which contrasts with the studies of exchange rates which is due to the high volatility on the cryptocurrencies. Our predictors are related to the price momentum effects and they outperform widely used network factors.

Claude B. Erb

Bitcoin has been described as digital gold. Bitcoin is exactly like gold except when it isn’t. Over millennia, gold has gained a questionable reputation as an inflation hedge, a store of value and a safe haven. Gold’s price can arguably be decomposed into a “golden constant” fair price and a fair price deviation. Bitcoin has no track record as an inflation hedge, a store of value and a safe haven. Bitcoin’s price can arguably be decomposed into a questionable “bitcoin network” fair price and a fair price deviation. Both bitcoin and gold are about 50% above their “fair prices”.

Guglielmo Maria Caporale, Alex Plastun, Viktor Oliinyk

This paper investigates the relationship between Bitcoin returns and the frequency of daily abnormal returns over the period from June 2013 to February 2020 using a number of regression techniques and model specifications including standard OLS, weighted least squares (WLS), ARMA and ARMAX models, quantile regressions, Logit and Probit regressions, piecewise linear regressions, and non-linear regressions. Both the in sample and out-of-sample performance of the various models are compared by means of appropriate selection criteria and statistical tests. These suggest that, on the whole, the piecewise linear models are the best, but in terms of forecasting accuracy they are outperformed by a model that combines the top five to produce “consensus” forecasts. The finding that there exist price patterns that can be exploited to predict future price movements and design profitable trading strategies is of interest both to academics (since it represents evidence against the EMH) and to practitioners (who can use this information for their investment decisions).

Wenzong Jin

Are cryptocurrencies indeed currencies? Anecdotal evidence on the volatility of cryptocurrency prices suggest that these “currencies” are not a good store of value, and similarly the time delays in validating and publishing crypto-based transactions suggest that they are not a good medium of exchange either. Due to the context it is defined in, it seems to not follow social conventions of fiat currencies. In this thesis, we undertake a systematic evaluation of how much do cryptocurrency prices behave like fiat currency prices, focusing on the predominant cryptocurrency — Bitcoin. We test the usefulness of various time series and structural models to predict future changes in Bitcoin prices and conclude that when predicting out of sample, its price is as unpredictable as fiat currency prices. Since cryptocurrencies generally have no central authority and hence receive no regulation, we explore its country-dependent characteristics, and find that the overall conclusions apply. We also examine if nominal interest rate differentials denominated in fiat currencies versus Bitcoin predict exchange rate movements, and find that in addition to the persistent violation in short-run, interest parity suggest that Bitcoin price has not been rising fast enough. We conclude that we have to refine the definition of monetary parameters on cryptocurrencies to better capture its properties, but as far as our examination indicates, the price of the predominant cryptocurrencies behaves similarly to most fiat currencies. In our point of view, Bitcoin is a currency.<br>

Chuanhai Zhang

No abstract is available for this record.

Qingjie Du, Yang Wang, Chishen Wei, K.C. John Wei · 5 authors

No abstract is available for this record.

Yongqiang Meng, Dehua Shen, Xiong Xiong, Jørgen Vitting Andersen

This paper investigates the relations between multiple measures of investor sentiment and the returns, volatility, trading volume, and liquidity. Using both data outside and inside market, we find that the Bullishness from socio-finance model are significant related to future realized volatility and trading volume, similar to Tweet, which is thought to capture information of well-informed investors in Bitcoin market

Guglielmo Maria Caporale, Woo-Young Kang

No abstract is available for this record.

Carlos César Trucíos Maza, James W. Taylor

No abstract is available for this record.

Omar Gray

No abstract is available for this record.

Mieszko Mazur

Bitcoin market capitalization has recently surpassed $1 trillion. According to the popular belief one of the key characteristics of bitcoin is its excessive volatility. This paper provides evidence that high volatility of bitcoin is largely a misperception. We show that bitcoin return fluctuations are lower than those of roughly 900 different stocks in the S&P1500 and 190 stocks in the S&P500. Moreover, we find that bitcoin is less volatile than commodities such as oil and silver, US Treasuries, AAA-rated corporate bonds, EU carbon credits, and some of the most popular technology and media stocks: Apple, Twitter, and Netflix. Equally important, we find that during the March 2020 stock market crash triggered by COVID-19, bitcoin volatility was lower than most of the above-mentioned asset classes. Significant decline in bitcoin volatility over the last decade renders it more “investable” by conservative investors.

Tetiana Yatsyk

The cryptocurrency market is represented by more than 6,099 different cryptocurrencies with a total market capitalization of USD 354,316 million with Bitcoin dominance over 60%. Despite the increasing amount of scientific research, a comprehensive analysis of factors influencing the price of cryptocurrency is still needed. Previous studies have focused on the Bitcoin capitalization changes, rather than relationships and dependencies between the price of different cryptocurrencies and other factors. The author proposed a multiple linear regression model, which can be used for the cryptocurrency price forecast. The author tested the hypothesis, that Bitcoin's closing price changes likely in response to changes in altcoin prices and Google search index as well. According to the conducted research, the price of Bitcoin depends significantly on Google's search index on the specific cryptocurrency name. The revealed multiple regression equation can be further used for creating operational analytical programs for forecasting the price movement of Bitcoin.

Taurai Muvunza

No abstract is available for this record.

David Vidal-Tomás

No abstract is available for this record.

Kei Nakagawa, Ryuta Sakemoto

No abstract is available for this record.

Ayana T. Aspembitova

Decentralized Finance is the new socioeconomic system growing with an extremely fast pace and changing the way financial interactions are being conducted. In comparison with the growing importance of digital assets and blockchain technology, there is still little understanding of Decentralized Finance as a system. In this thesis we analyze transaction datasets from Bitcoin and Ethereum blockchains to obtain a comprehensive understanding of digital assets -from studying the behaviour of each part to investigating the whole structure and deriving the relations between micro and macro properties of the cryptocurrency systems. Using the Complex Networks approach we explained the system's overall structure and dynamics, and uncovered the mechanism behind network formation. It was found that there is fitness preferential attachment among nodes in the bitcoin network that leads the system to scale-free behaviour. We proposed the quantifiable definition of fitness and supported our finding by simulating a synthetic network and reproducing the main properties of the bitcoin network. After having a good understanding about the structure of the system, we zoom in into its parts by studying the behavioral patterns among the system's users (people). We develop the methodology based on Machine Learning models to define distinct behavioral types in the cryptocurrency systems and find that despite differences between the bitcoin and ethereum systems, there are four common strategies that users follow in both markets. Based on our finding, we model the dynamics of people's behaviour in market as an Absorbing Markov Chain. This approach allowed us to present the behavioral switches in a comprehensive and intuitive way. Moreover, we were able to obtain the predictions on the longevity of users in the system according to their behaviour. Finally, we use the Granger causality test to derive the relations between all system characteristics. We attempt to explain the effect of behavioral switches on the structural properties and price; we find that indeed, switches of users from certain behavioral groups causes a change in price which affects the size of the network as well. We hope that the work and results presented in this thesis will advance the understanding of the new field of Decentralized Finance and expect that the research approach and methodologies developed for this study will be helpful to investigate various complex systems as well.

Luigi Doria

The last years have experienced an effervescence in the field of monetary innovation, concerning both complementary currencies and cryptocurrencies. The scenario of innovation has been intensively investigated with regard to economic and socio-political aspects. Against the peculiar multidimensionality of the phenomenon, the paper argues that the analysis should take the opportunity of grasping a cobelonging between the economic and the social. Whether they seem related to a proliferation of new forms of sociality (as in many experiences of complementary currencies) or to a disquieting desocialization (as in certain domains of the cryptocurrencies' world), the social dimensions of the new monies can be fruitfully analyzed by focusing on how they are consonant with certain basic conceptions of economic life. After a brief discussion of this point with regard to complementary currencies, the above-mentioned theoretical approach is used to investigate the cybernetic ethos of cryptocurrencies. The analysis shows that the socio-technical imaginaries of some cryptocurrencies (with particular regard to Bitcoin) call into question the relationship between human and non-human agency and are complicit with certain ideas of economic life, one of whose main traits concerns the demand for unconditionally "assuring" the economic and for denying the dimension of uncertainty.

Lai T. Hoang, Dirk G. Baur

This paper analyzes the stability of stablecoins and proposes a framework to test for absolute and relative stability of stablecoins. Based on high-frequency data, we find strong evidence of excess price variations. While Bitcoin is a likely source of this excess volatility because stablecoin returns, volatility and volumes are highly correlated with corresponding Bitcoin time-series, we also demonstrate through a quasi-natural experiment that stablecoins increase the trading volume of Bitcoin. The findings suggest stablecoins play a key role in cryptocurrency markets.

Saiful Izzuan Hussain, Nadiah Ruza, Nurulkamal Masseran, Muhammad Aslam Mohd Safari

Dependence structure between financial assets plays an important role in risk management. This research investigates the dependence pattern between the stock market and the potential of cryptocurrency. We employed time- varying copula and Extreme Value Theory (EVT) to model the extreme dependence between the United States (US) index stock market (S&P500) and Bitcoin. Empirical results show risk diversification for holdings of the S&P500 and Bitcoin during extreme events seem to be effective. This paper contributes to a better understanding of the dependence structure of the financial market during extreme events. This information is useful for investors who are seeking for the cross-market diversification.