Are cryptocurrencies indeed currencies? Anecdotal evidence on the volatility of cryptocurrency prices suggest that these βcurrenciesβ 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 β 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>
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
The aim of this work is to study the pricing in the cryptocurrency market and applying cryptocurrencies by the Bank of Russia for its monetary policy. The research objectives are to identify the cyclical nature of price dynamics, to study market maturity and potential risks that have a long-term positive relationship with the financial stability of the cryptocurrency market. The author uses the Hurst method with the Amihud illiquidity measure to study the resistance of four cryptocurrencies (Bitcoin, Litecoin, Ripple and Dash) and their evolution over the past five years. The study results in the authorβs conclusion that the cryptocurrency market has entered a new stage of development, which means a reduced possibility to have excess profits when investing in the most liquid cryptocurrencies in the future. However, buying new high-risk tools provides opportunities for speculative income. The author concludes that illiquid cryptocurrencies exhibit strong inverse anti-persistence in the form of a low Hurst exponent. A trend investing strategy may help obtain abnormal profits in the cryptocurrency market. The Bank of Russia could partially apply digital currency to implement monetary policy, which would soften the business cycle and control the inflation. If Russia accepts the law ββOn Digital Financial Assetsββ and legalizes cryptocurrencies after the economic crisis caused by the COVID-19 pandemic, the Bank of Russia might act as a lender of last resort and offer crypto loans. Π¦Π΅Π»ΡΡ Π΄Π°Π½Π½ΠΎΠΉ ΡΠ°Π±ΠΎΡΡ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΈΠ·ΡΡΠ΅Π½ΠΈΠ΅ ΡΠ΅Π½ΠΎΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΡ Π½Π° ΡΡΠ½ΠΊΠ΅ ΠΊΡΠΈΠΏΡΠΎΠ²Π°Π»ΡΡ ΠΈ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠ΅ΠΉ ΠΈΡ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΠΠ°Π½ΠΊΠΎΠΌ Π ΠΎΡΡΠΈΠΈ ΠΏΡΠΈ ΠΎΡΡΡΠ΅ΡΡΠ²Π»Π΅Π½ΠΈΠΈ ΡΠ²ΠΎΠ΅ΠΉ ΠΌΠΎΠ½Π΅ΡΠ°ΡΠ½ΠΎΠΉ ΠΏΠΎΠ»ΠΈΡΠΈΠΊΠΈ. ΠΠ°Π΄Π°ΡΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ: Π²ΡΡΠ²Π»Π΅Π½ΠΈΠ΅ ΡΠΈΠΊΠ»ΠΈΡΠ½ΠΎΡΡΠΈ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ ΡΠ΅Π½, ΠΈΠ·ΡΡΠ΅Π½ΠΈΠ΅ ΡΡΠ΅ΠΏΠ΅Π½ΠΈ ΡΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½Π½ΠΎΡΡΠΈ ΡΡΠ½ΠΊΠ° ΠΈ ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»ΡΠ½ΡΡ ΡΠΈΡΠΊΠΎΠ², ΠΈΠΌΠ΅ΡΡΠΈΡ Π΄ΠΎΠ»Π³ΠΎΡΡΠΎΡΠ½ΡΡ ΠΏΠΎΠ»ΠΎΠΆΠΈΡΠ΅Π»ΡΠ½ΡΡ ΡΠ²ΡΠ·Ρ Ρ ΡΠΈΠ½Π°Π½ΡΠΎΠ²ΠΎΠΉ ΡΡΠ°Π±ΠΈΠ»ΡΠ½ΠΎΡΡΡΡ ΡΡΠ½ΠΊΠ° ΠΊΡΠΈΠΏΡΠΎΠ²Π°Π»ΡΡ. ΠΠ²ΡΠΎΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΠ΅Ρ ΠΌΠ΅ΡΠΎΠ΄Ρ Π₯Π΅ΡΡΡΠ° Ρ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠΎΠΌ Π½Π΅Π»ΠΈΠΊΠ²ΠΈΠ΄Π½ΠΎΡΡΠΈ ΠΠΌΠΈΡ ΡΠ΄Π°, ΡΡΠΎΠ±Ρ ΠΈΠ·ΡΡΠΈΡΡ ΡΡΠ΅ΠΏΠ΅Π½Ρ ΡΡΠΎΠΉΠΊΠΎΡΡΠΈ ΡΠ΅ΡΡΡΠ΅Ρ ΠΊΡΠΈΠΏΡΠΎΠ²Π°Π»ΡΡ (BitCoin, LiteCoin, Ripple ΠΈ Dash) ΠΈ ΠΈΡ ΡΠ²ΠΎΠ»ΡΡΠΈΡ Π² ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ ΠΏΠΎΡΠ»Π΅Π΄Π½ΠΈΡ ΠΏΡΡΠΈ Π»Π΅Ρ. Π ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π°Π²ΡΠΎΡ Π²ΡΡΡΠ½ΠΈΠ», ΡΡΠΎ ΡΡΠ½ΠΎΠΊ ΠΊΡΠΈΠΏΡΠΎΠ²Π°Π»ΡΡ Π²ΡΡΠ΅Π» Π½Π° Π½ΠΎΠ²ΡΡ ΡΡΠ°Π΄ΠΈΡ ΡΠ°Π·Π²ΠΈΡΠΈΡ, ΡΡΠΎ ΠΎΠ·Π½Π°ΡΠ°Π΅Ρ ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΠ΅ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈ ΠΏΠΎΠ»ΡΡΠ΅Π½ΠΈΡ ΡΠ²Π΅ΡΡ Π½ΠΎΡΠΌΠ°Π»ΡΠ½ΡΡ Π΄ΠΎΡ ΠΎΠ΄ΠΎΠ² ΠΏΡΠΈ ΠΈΠ½Π²Π΅ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΠΈ Π² Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π»ΠΈΠΊΠ²ΠΈΠ΄Π½ΡΠ΅ ΠΊΡΠΈΠΏΡΠΎΠ²Π°Π»ΡΡΡ Π² Π±ΡΠ΄ΡΡΠ΅ΠΌ. ΠΠ΄Π½Π°ΠΊΠΎ ΠΎΡΡΠ°ΡΡΡΡ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈ Π΄Π»Ρ ΠΏΠΎΠ»ΡΡΠ΅Π½ΠΈΡ ΡΠΏΠ΅ΠΊΡΠ»ΡΡΠΈΠ²Π½ΠΎΠ³ΠΎ Π΄ΠΎΡ ΠΎΠ΄Π° ΠΏΡΠΈ ΠΏΠΎΠΊΡΠΏΠΊΠ΅ Π½ΠΎΠ²ΡΡ Π²ΡΡΠΎΠΊΠΎΡΠΈΡΠΊΠΎΠ²Π°Π½Π½ΡΡ ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠΎΠ². Π‘Π΄Π΅Π»Π°Π½ Π²ΡΠ²ΠΎΠ΄, ΡΡΠΎ Π½Π΅Π»ΠΈΠΊΠ²ΠΈΠ΄Π½ΡΠ΅ ΠΊΡΠΈΠΏΡΠΎΠ²Π°Π»ΡΡΡ ΠΏΡΠΎΡΠ²Π»ΡΡΡ ΡΠΈΠ»ΡΠ½ΡΡ ΠΎΠ±ΡΠ°ΡΠ½ΡΡ Π°Π½ΡΠΈΠΏΠ΅ΡΡΠΈΡΡΠ΅Π½ΡΠ½ΠΎΡΡΡ Π² Π²ΠΈΠ΄Π΅ Π½ΠΈΠ·ΠΊΠΎΠ³ΠΎ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠ° Π₯Π΅ΡΡΡΠ°. ΠΠ»Ρ ΠΏΠΎΠ»ΡΡΠ΅Π½ΠΈΡ Π°Π½ΠΎΠΌΠ°Π»ΡΠ½ΠΎΠΉ ΠΏΡΠΈΠ±ΡΠ»ΠΈ Π½Π° ΠΊΡΠΈΠΏΡΠΎΡΡΠ½ΠΊΠ΅ ΠΌΠΎΠΆΠ΅Ρ Π±ΡΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Π° ΡΡΠ΅Π½Π΄ΠΎΠ²Π°Ρ ΠΈΠ½Π²Π΅ΡΡΠΈΡΠΈΠΎΠ½Π½Π°Ρ ΡΡΡΠ°ΡΠ΅Π³ΠΈΡ. ΠΠ°Π½ΠΊ Π ΠΎΡΡΠΈΠΈ ΠΌΠΎΠ³ Π±Ρ ΡΠ°ΡΡΠΈΡΠ½ΠΎ ΠΏΡΠΈΠΌΠ΅Π½ΡΡΡ ΡΠΈΡΡΠΎΠ²ΡΡ Π²Π°Π»ΡΡΡ ΠΏΡΠΈ ΠΎΡΡΡΠ΅ΡΡΠ²Π»Π΅Π½ΠΈΠΈ Π΄Π΅Π½Π΅ΠΆΠ½ΠΎ-ΠΊΡΠ΅Π΄ΠΈΡΠ½ΠΎΠΉ ΠΏΠΎΠ»ΠΈΡΠΈΠΊΠΈ, ΡΡΠΎ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΎ Π±Ρ ΡΠΌΡΠ³ΡΠΈΡΡ Π΄Π΅Π»ΠΎΠ²ΠΎΠΉ ΡΠΈΠΊΠ» ΠΈ ΠΊΠΎΠ½ΡΡΠΎΠ»ΠΈΡΠΎΠ²Π°ΡΡ ΡΡΠΎΠ²Π΅Π½Ρ ΠΈΠ½ΡΠ»ΡΡΠΈΠΈ. Π ΡΠ»ΡΡΠ°Π΅ ΠΏΡΠΈΠ½ΡΡΠΈΡ Π·Π°ΠΊΠΎΠ½Π° Β«Π ΡΠΈΡΡΠΎΠ²ΡΡ ΡΠΈΠ½Π°Π½ΡΠΎΠ²ΡΡ Π°ΠΊΡΠΈΠ²Π°Ρ Β» ΠΈ Π»Π΅Π³Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΠΊΡΠΈΠΏΡΠΎΠ²Π°Π»ΡΡ Π² Π ΠΎΡΡΠΈΠΈ ΠΏΠΎΡΠ»Π΅ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΊΡΠΈΠ·ΠΈΡΠ°, Π²ΡΠ·Π²Π°Π½Π½ΠΎΠ³ΠΎ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠ΅ΠΉ Covid-19, ΠΠ°Π½ΠΊ Π ΠΎΡΡΠΈΠΈ ΠΌΠΎΠ³ Π±Ρ Π΄Π΅ΠΉΡΡΠ²ΠΎΠ²Π°ΡΡ ΠΊΠ°ΠΊ ΠΊΡΠ΅Π΄ΠΈΡΠΎΡ ΠΏΠΎΡΠ»Π΅Π΄Π½Π΅ΠΉ ΠΈΠ½ΡΡΠ°Π½ΡΠΈΠΈ, ΠΏΡΠ΅Π΄Π»Π°Π³Π°Ρ ΠΊΡΠ΅Π΄ΠΈΡΡ Π² ΠΊΡΠΈΠΏΡΠΎΠ²Π°Π»ΡΡΠ΅.
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 βinvestableβ by conservative investors.
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.
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.
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.
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.