In recent years, Bitcoin has gained global mass adoption as an asset class. However, due to its characteristics of peer-to-peer direct borderless payment, anonymity and limited supply, Bitcoin has a special application in regions experiencing political and economic turmoil. It serves two functions: store of value and secure channel of transferring assets abroad. In this paper, I will only investigate the correlation between Bitcoin adoption and fiat default in Venezuela due to a limitation on empirical data. Time series FGLS regressions are employed to examine such correlation. The two Bitcoin metrics, Real Bitcoin Price in Venezuelan Bolivar (VEF) and Real Bitcoin Trading Volume in VEF, are included as independent variables. The two economic indicators, the Black Market Exchange Rate (VEF/USD) and Monthly Moving Inflation Rate, are included as explanatory variables. I find a relatively weak correlation between Bitcoin adoption and the well-being of the Venezuelan Economy. The Black Market Exchange Rate has a stronger positive impact on Real Bitcoin Price and Real Bitcoin Trading Volume while Inflation Rate has little impact. In addition, Real Bitcoin Volume responses to the changes the Venezuelan Economy approximately one week slower than Real Bitcoin Price.

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The Bitcoin currency relies on a transaction verification system run by a decentralized network of miners. This paper evaluates the long-term economic stability of Bitcoin mining. Specifically, I analyze the incentive structure surrounding transaction fees, which are part of the reward miners earn for verifying transactions in the Bitcoin network. My method of investigation is to first construct a visual model representing miner incentives, then input current and estimated data into that model, and finally determine how individual miners and pools will behave based on the key variables included in the model and industry trends. I conclude, under the current protocol rules, Bitcoin mining is not economically sustainable in the long-term due to the impending centralization of the network. Centralization in itself will not necessarily destroy the network. However, it will lead to unsatisfactory outcomes that will greatly lower the value of the entire system. Therefore, I recommend two potential solutions to the centralization issue, namely the requirement of either P2Pools or a proof-of-stake mechanism. The development of future applications on the Bitcoin protocol depends on the success of the Bitcoin currency application. These future technologies, along with the Bitcoin currency, have the potential to disrupt many industries. But, if miner incentives are not aligned with maintaining decentralization, then none of this potential will be realized.

Bitcoin, a virtual currency invented in 2009, was created as a peer-to-peer currency that eliminated the need for a third party authority, such as banks or government, to be involved in monetary transactions. Having no intrinsic value but carrying no government guarantees relegates bitcoin and its competitors to the perpetual role of investment opportunity, deriving value not from a practical use, but from a nominal, dollar value. This will continue to be the case until the U.S. Government sanctions virtual currency as a viable store of value. Because the dollar plays such a large role in the world’s economy, other countries will not adopt virtual currency technology unless the U.S. does so first. Substantial populations around the world must embrace bitcoin as a significant source of value before any monetary authority will relinquish the power associated with fiat currency. There are, however, many aspects of the virtual-currency model created by bitcoin that could be useful in improving the efficiency of money movement around the United States and the globe, through transaction memory, low transaction cost, and secure account information.

Bitcoin has become notorious as the first cryptocurrency to gain widespread media attention, however, despite its many benefits over the existing financial system it remains a volatile fringe currency. This thesis examines the validity of bitcoin as a currency and whether it can play a role in circumventing extractive economic and political institutions in developing countries. The analysis compares bitcoin usage to the level of financial openness, the inflation rate, and the percentage of the population with a bank account in 21 different countries. The correlation is found to be both statistically and economically significant for all of these variables, which suggests that bitcoin is being used in countries with underdeveloped financial systems and detrimental monetary policies. A regression run on these variables indicates that a one-percentage-point increase in inflation leads to a 44.48% increase in bitcoin usage, a one-percentage-point increase in the percentage of people in a country that have a bank account leads to an 8.65% decrease in bitcoin usage and a one unit increase in financial openness leads to a 216% decrease in bitcoin usage. Throughout this analysis the positive and negative implications of widespread bitcoin adoption are discussed with respect to economies in the developing world.

Studiens syfte är att undersöka om uppmätt sentiment på Twitter kan vara en förutsägande faktor för priset på Bitcoin. En kvantitativ undersökning genomförs med regressionsmodeller där data inhämtas från Twitter i realtid. Resultatet indikerar ett svagt samband där bäst resultat erhölls med en tidsfördröjning av sentiment på 16 timmar, vilket tyder på att det kan finnas möjligheter att använda Twitter för att förutspå förändringar av priset på Bitcoin. Variationen av resultat för olika tidsperioder gör dock att det är svårt att dra generella slutsatser av studien.

In recent decades, the rapid development of information technology in the big data field has introduced new opportunities to explore a large amount of data available online. The Global Database of Events, Location (Language), and Tone (GDELT) is the largest, most comprehensive, and highest resolution open source database of human society that includes more than 440 million entries capturing information about events that have been covered by local, national, and international news sources since 1979 in over 100 languages. GDELT constructs a catalog of human societal-scale behavior and beliefs across all countries of the world, connecting every person, organization, location, count, theme, news source, and event across the planet into a single massive network that captures what is happening around the world, what its context is and who is involved, and how the world is feeling about it, every single day. On the other hand, the stock market prediction has also been a long-time attractive topic and is extensively studied by researchers in different fields with numerous studies of the correlation between stock market fluctuations and different data sources derived from the historical data of world major stock indices or external information from social media and news. Support Vector Machine (SVM) and Logistic Regression are two of the most widely used machine learning techniques in recent studies. The main objective of this research project is to investigate the worthiness of information derived from GDELT project in improving the accuracy of stock market trend prediction specifically for the next days' price changes. This research is based on data sets of events from GDELT database and daily prices of Bitcoin and some other stock market companies and indices from Yahoo Finance, all from March 2015 to May 2017. Then multiple different machine learning and specifically classification algorithms are applied to data sets generated, first using only features derived from historical market prices and then including more features derived from external sources, in this case, GDELT. Then the performance is evaluated for each model over a range of parameters. Finally, experimental results show that using information gained from GDELT has a direct positive impact on improving the prediction accuracy. Keywords: Machine Learning, Stock Market, GDELT, Big Data, Data Mining

Digital currencies (cryptocurrencies) are rapidly becoming commonplace in the global market. Trading is performed similarly to the stock market or commodities, but stock market prediction algorithms are not necessarily well-suited for predicting digital currency prices. In this work, we analyzed tweets with both an existing sentiment analysis package and a manually tailored "objective analysis," resulting in one impact value for each analysis per 15-minute period. We then used evolutionary techniques to select the most appropriate training method and the best subset of the generated features to include, as well as other parameters. This resulted in implementation of predictors which yielded much more profit in four-week simulations than simply holding a digital currency for the same time period--the results ranged from 28% to 122% profit. Unlike stock exchanges, which shut down for several hours or days at a time, digital currency prediction and trading seems to be of a more consistent and predictable nature.

Submitted by Morgana Silva (morgana_linhares@yahoo.com.br) on 2016-06-29T19:29:16Z No. of bitstreams: 1 arquivototal.pdf: 2567247 bytes, checksum: 1b69ea69689d98843e4c8b25dbf6e8f6 (MD5) / Made available in DSpace on 2016-06-29T19:29:16Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 2567247 bytes, checksum: 1b69ea69689d98843e4c8b25dbf6e8f6 (MD5) Previous issue date: 2015-08-28 / The present essay studied the conceptual, innovative, market-oriented and qualitative aspects of Bitcoin. After the exposure of the key concepts about the Bitcoin, digital currency and currency, there is a contextualization of the Bitcoin as a financial innovation. In regards to the innovative aspects, the birth of Bitcoin represented a radical and paradigmatic innovation with potential of creating a creative destruction. The most modern concepts of the Innovation Theory are also exposed and so it is perceived that the Bitcoin exhibits characteristics of Disruptive Innovation (DI) of two kinds: Low and (DI) and New Market (DI). In regards to the market-oriented and structural aspects it was investigated the existence of similarities between the credit and debit market of Bitcoin and the traditional structure of the payment card's market (two sided market - 2SM). It was verified the adequacy of Bitcoin to the 2SM structure, but only on the debit card's market. The credit system of the Bitcoin market does not fit to the one of the traditional system. This work sought to understand the volatility of determinants of the Bitcoin prices. To attain this objective two different kinds of analysis were made: univariate and multivariate analysis. To estimate the univariate volatility the following models were plotted: ARCH, GARCH, EGARCH and TARCH whose results showed the existence of persistent volatility. The multivariate quantitative analysis aimed to understand the volatilities interaction between Bitcoin the other financial variables. It was applied the DCC M-GARCH methodology which allows the achievement of the statistical parameters using the quasi-correlation of the volatility. The results showed the existence of ARCH and GARCH effects in all cases. While the explanatory variables don't indicate any significance, the multivariate analysis of the subsample realize a convergence movement of the variables. In all cases it was considered the return toward the mean. All models were estimated for a sample considering the period between September 13th of 2011 and June 23th of 2015 and for a subsample that covers the period from March 10th of 2013. / A presente dissertação realizou uma análise sobre aspectos conceituais, inovativos, mercadológicos e quantitativos do Bitcoin. Após expostos conceitos basilares sobre o Bitcoin, moedas digitais e moeda buscou-se contextualizar o Bitcoin como inovação financeira. Com relação aos aspectos inovativos o surgimento do Bitcoin representou uma inovação radical e pré-paradigmática com potencial de destruição criativa. Também foram expostos os conceitos mais modernos da teoria da inovação e percebeu-se que o Bitcoin apresenta características de Inovação Disruptiva (ID) de dois tipos: Low and (ID) e New Market (ID). Quanto aos aspectos mercadológicos e estruturais foi investigada a existência de semelhanças entre o mercado de crédito e débito do Bitcoin e a estrutura tradicional do mercado de cartões conhecida por Mercado de Dois Lados (M2L). Verificou-se a perfeita adequação do Bitcoin à estrutura M2L, mas apenas no mercado de cartões de débito. O sistema de crédito existente no mercado do Bitcoin não se conforma da maneira tradicional. Buscou-se também compreender os determinantes da volatilidade dos preços do Bitcoin. Para atingir este objetivo foram realizados dois tipos de análises: univariadas e multivariadas. Para estimar a volatilidade univariada foram estimados os modelos ARCH, GARCH, EGARCH e TARCH cujos resultados apontaram existência de volatilidade persistente. Já análise quantitativa multivariada apresentou o objetivo de compreender a interação das volatilidades entre o Bitcoin e outras variáveis financeiras. Foi aplicada a metodologia DCC M-GARCH que possibilita a obtenção dos parâmetros por meio das quasicorrelações da volatilidade. Os resultados apontaram a existência dos efeitos ARCH e GARCH em todos os casos. Embora as variáveis explicativas não apontem significância a análise multivariada da subamostra aparentemente realiza movimento de convergência. Em todos os casos foram considerados os retornos das séries. Todos os modelos foram estimados para a amostra considerando o período de 13 de Setembro de 2011 e 23 de Junho de 2015 e para uma subamostra que abrange o período a partir de 10 de Março de 2013.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-05-30T15:34:00Z No. of bitstreams: 1 helderluizpalmiericaldas.pdf: 3093758 bytes, checksum: 78e635406e0664df0546fe72eee1988d (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-05-30T15:37:48Z (GMT) No. of bitstreams: 1 helderluizpalmiericaldas.pdf: 3093758 bytes, checksum: 78e635406e0664df0546fe72eee1988d (MD5) / Made available in DSpace on 2017-05-30T15:37:48Z (GMT). No. of bitstreams: 1 helderluizpalmiericaldas.pdf: 3093758 bytes, checksum: 78e635406e0664df0546fe72eee1988d (MD5) Previous issue date: 2016-03-07 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / O Bitcoin é um sistema de pagamento totalmente digital independente de uma entidade centralizadora como bancos ou governos. O projeto foi criado e publicado em 2008 através da Internet. Entretanto apenas em 2009 a rede tornou-se operacional. O Bitcoin é um protocolo de código aberto e uma rede ponto a ponto de participantes que é responsável pelo funcionamento do sistema. Segurança criptográfica, ausência de taxas e de custos de instalação são fatores que convenceram várias empresas do mundo a adotá-lo como alternativa de pagamento. Apesar dos trabalhos acerca da moeda digital, pouco ainda se sabe sobre sua topologia e características, principalmente pela ótica de ciência de redes. Nesse sentido, o presente trabalho apresenta o estudo da dinamicidade de suas principais variáveis no seu funcionamento diário. No decorrer do trabalho são apresentadas duas formas de extração de dados da rede Bitcoin para futuras análises. / Bitcoin is a fully digital payment system independent of a centralized entity like banks or governments. The Bitcoin project was created and published in 2008. In 2009 the Bitcoin P2P network became operational. The Bitcoin is an open source protocol and a peer-topeer network of participants that is responsible for operating the system. Cryptographic security, absence of exogenous rates and of installation costs convinced several companies in the world to adopt it as a payment alternative. Although, there is an increasing amount of work on digital currencies, little is known about Bitcoin its topology and characteristics, particularly from the viewpoint of network science. In this sense, this paper presents the study of the dynamics of its main variables and their daily functioning. During the work we present two forms of network data extraction Bitcoin for further analysis.