This paper analyzes cryptocurrencies as financial instruments. Firstly, we introduced the main features of cryptocurrencies and summarized the brief history. We found out that price of the most famous cryptocurrency Bitcoin follows the hypothesis of efficient markets and it immediately react on publicly announce information. Furthermore, Bitcoin can be seen as standard economic good that is priced by interaction of supply and demand on the market. These factors can be driven by macro financial development or by speculative investors, but there weren't found any significant impact of these factors on price of Bitcoin. CAPM shows the high risk of cryptocurrencies, but it could be still good instrument for diversification.

Over the past few years, bitcoin has become a globally successful and much followed project. It is a kind of decentralized digital currency, which functions based on mathematical-cryptographical principles and is created using a computationally intensive process called mining. Thousands of other alternative crypto currencies exist, which have so far stayed unnoticed by the media, even though they outperform bitcoin in many aspects. The central topic of this paper is the extensive ecosystem of alternative crypto currencies and an analysis of their mining process. The goal is to demonstrate, by means of a practical example, how alternative crypto currencies are mined and also to find out, if it's possible to mine crypto currencies profitably with specific type of a graphic card. To successfully reach this goal I had to first analyse the ecosystem of crypto currencies. Subsequently I compared different crypto currencies to one another and eventually successfully implemented the mining operation and evaluated its results. The main contribution of this paper is to answer the question of whether and how alternative crypto currencies can be profitably mined. I believe the particular benefit of this work rests not only in the practical demonstration of how alternative crypto currencies are mined but also in the summary description of the crypto currency ecosystem's composition and the factors that influence the price of these crypto currencies. Structurally, this paper is divided in three main parts. The first part is dedicated to the explanation of the term crypto currency, what it comprises and according to which principles it functions. The second part contains an analysis of the ecosystem as well as a comparison of a fixed sample of alternative crypto currencies. The third part is the practical part, during which I undertook a real mining operation.

Proyecto de Actividad formativa equivalente a tesis (AFET) / Programa de magíster en derecho tributario / El objetivo del presente trabajo es determinar el régimen tributario aplicable a las criptomonedas. Para ello, se analizará la normativa administrativa y legislación comparada en la materia, como también la legislación nacional civil vigente. Como resultado, determinaremos la naturaleza jurídica de las criptomonedas y las consecuencias tributarias que de ello derivan. / The purpose of this work is to determine the cryptocurrencies’ applicable tax regime. For this purpose, we will analyze the relevant legal and administrative regulation, as well as the Chilean civil legislation. As a result, we will determine the legal nature of cryptocurrencies and the proper tax treatment derived from it.

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Memoria para optar al título de Ingeniero Civil en Computación / CryptoMarket es una empresa chilena que nace con el objetivo de acercar a las personas al mundo de las criptomonedas de manera sencilla, dándole la capacidad a sus usuarios de transar en diversas criptomonedas en su moneda local. Actualmente en CryptoMarket, cerca del 40% de sus usuarios de un total de más de 40.000, acceden a la plataforma web por su dispositivo móvil. Esta plataforma si bien tiene diversas adaptaciones para utilizarse mediante un navegador móvil, no está totalmente adaptada para usarse desde dispositivos móviles. Al inicio de esta memoria, CryptoMarket contaba con una aplicación móvil en que solo se podían ver los precios de sus mercados y los gráficos de precios correspondientes a cada mercado. El objetivo general del trabajo realizado fue desarrollar una solución móvil para la empresa CryptoMarket, en la cual los usuarios pueden hacer diversas acciones de tradingd​ecriptomonedasdescargandolaaplicación.Estaaplicacióndebesercapaz de entregar una buena experiencia para los usuarios, dándoles la comodidad que esperan al tener una aplicación móvil, pero también la simplicidad y seguridad que acostumbran tener en la plataforma web. Se logró desarrollar la aplicación móvil, que a día de hoy está lanzada en la App Store de iOS de diversos países. La aplicación posee inicio de sesión, evitando que el usuario tenga que ingresar su correo electrónico y contraseña de CryptoMarket cada vez que quiera usar la plataforma. El usuario puede realizar todas las operaciones básicas de ​trading de criptomonedas como lo son; ver los precios de las criptomonedas en los diferentes mercados, vender y comprar criptomonedas, ver gráficos y datos, historiales de transacciones, cancelar órdenes, etc. Todas estas funcionalidades se lograron conectándose a un servidor ya existente en la empresa mediante ​API​ y ​WebSockets.​ Se hizo un estudio de usabilidad en donde se encontraron algunos problemas, como la dificultad para encontrar las órdenes de mercado abiertas. Actualmente se está viendo cómo resolver estos problemas en una futura actualización de la aplicación. Desde que se lanzó la aplicación ya se cuenta con cerca de 4.000 usuarios los cuales están agradecidos por entregarles esta solución, como también otorgan ​feedback para las futuras funcionalidades y pequeños errores que encuentran.

<div>This dissertation consists of three essays that study problems that decision-makers face when hitherto niche technologies scale up. Typically, scaling up involves market expansion with participation from a variety of agents with complex preferences, using the technology to maximize their utility. A major problem for the decision maker then is either one or a combination of the following: deciding policy for optimal business or social outcomes, implementing effcient demand allocation mechanisms or improving market design.</div>

Syftet med studien var att undersöka konsumenters kunskap kring och inställning till bitcoin som betalningsmedel. För att uppnå syftet konstruerades forskningsfrågan: ” Vilka faktorer påverkar acceptansen av bitcoin hos svenska konsumenter?”.För att besvara forskningsfrågan genomfördes en kvantitativ enkätundersökning med en grupp respondenter begränsad till åldersspannet 20 till 50 år. 100 personer tillfrågades varav 76 valde att delta. Frågorna i denna enkätundersökning baserades på befintlig teori och forskning kring ämnet, vilken också ligger till grund för analysen av resultatet. En regressionsanalys genomfördes på resultatets utfall, vilken påvisade en signifikant korrelation mellan svenska konsumenters acceptans av bitcoin och sysselsättning. Svårigheten låg i att hitta förklaringar till detta utfall och de potentiella sådana som diskuterats är rent spekulativa. Detta trots att resultatet styrkts av befintliga teorier. Det är därför upp till framtida forskare att svara på VARFÖR sysselsättning påverkar svenska konsumenters acceptans av bitcoin med hjälp av de riktlinjer som presenteras i uppsatsens slutsats. / The purpose of this report was to investigate consumers' knowledge and attitude towards bitcoin as a payment method. In order to achieve this purpose the following research question was formed: “What factors affect the acceptance of bitcoin amongst swedish consumers?”.To answer this research question, a quantitative survey study including a group of respondents limited to an age span of 20 to 50 years was conducted. 100 people were asked to participate, of which 76 chose to do so. The questions in this survey were based on existing theory and research in this field, which was also used as a basis for the analysis of the result. A regression analysis was performed on the outcome of the result, which indicated a significant correlation between swedish consumers acceptance of bitcoin and occupation. The difficulty lay within finding potential explanations to this outcome and the ones that have been discussed are based on pure speculation. This in spite of the outcome being strengthened by existing theory. It is therefore up to future researchers to answer WHY occupation affect swedish consumers acceptance of bitcoin, using the guidelines presented in the conclusion of this essay.

This study discusses the acceptance level of cryptocurrency in countries of the world. Study takes a deep dive on what does affect the acceptance level of cryptocurrency and what should be expected if same changes would to happen in countries income level, technological level, financial level, and education level. The study gives an overview of current up to date situation of cryptocurrency. In this research we have conducted a cross-sectional data analysis of cryptocurrency acceptance level for year 2021. Study is focused on both decentralized and centralized acceptance level thus why the research has treated both transactions volume on exchanges and Defi. The study found that countries with higher income could have higher acceptance level of cryptocurrency, but the effect is not that immense. Other factors such as education, financial access and internet access had an inconclusive effect on the acceptance level. The study also shows that there is no prove of that pervious qualitative research result upholds or have any systematic relation with quantitative research results.

Background: Due to its decentralized nature and opportunity for substantial gains, cryptocurrency has become a popular investment opportunity. However, the highly unpredictable and volatile nature of the cryptocurrency market poses a challenge for investors looking to predict price movements and make profitable investments. Time series analysis, which recognizes trends and patterns in previous price data to create forecasts about future price movements, is one of the prominent and effective techniques for price prediction. Integrating Machine learning (ML) techniques and technical indicators along with time series analysis can enhance the prediction accuracy significantly. Objectives: The objective of this thesis is to identify an effective ML algorithm for making long-term predictions of Bitcoin prices, by developing prediction models using the ML algorithms and making predictions using the technical indicators(RelativeStrength Index (RSI), Exponential Moving Average (EMA), Simple Moving Average (SMA)) as input for these models. Method: A Systematic Literature Review (SLR) has been employed to identify effective ML algorithms for making long-term predictions of cryptocurrency prices and conduct an experiment on these identified algorithms. The selected algorithms are trained and tested using the technical indicators RSI, EMA, and SMA calculated using the historic price data over a period of May 2017 to May 2023 taken fromCoinGecko API. The models are then evaluated using various metrics and the effect of the indicators on the performance of the prediction models is found using permutation feature importance and correlation analysis. Results: After conducting SLR, the ML algorithms Random Forest (RF), GradientBoosting (GB), Long Short-Term Memory (LSTM), and Gated Recurrent Unit(GRU) have been identified as effective algorithms to conduct our experiment on. Out of these algorithms, LSTM has been found to be the most accurate model out of the 4 selected algorithms based on Root Mean Square Error (RMSE) score(0.01083), Mean Square Error (MSE) score (0.00011), Coefficient of Determination (R2) score (0.80618), Time-Weighted Average (TWAP) score (0.40507), and Volume-Weighted Average (VWAP) score (0.35660) respectively. Also, by performing permutation feature importance and correlation analysis it was found that the moving averages EMA and SMA had a greater impact on the performance of all the prediction models as compared to RSI. Conclusion: Prediction models were built using the chosen ML algorithms identified through the literature review. Based on the dataset built from the data collected through the CoinGecko database and taking technical indicators as the input features, models were trained and tested using the chosen ML algorithms. The LSTM prediction algorithm was found to be the most accurate out of the chosen algorithms based on the RMSE, R2, TWAP, and VWAP scores obtained.

No / This book provides an interdisciplinary critical perspective regarding risk, uncertainty, and governance challenges of cryptocurrencies. It considers the perspectives of several disciplines including accounting, cybersecurity, cyberlaw, economics, ethics, finance, financial regulation, shariah (Islamic) law and technology. Distinguished from other books on similar topic, our in-depth analysis and critical discourse on cryptocurrency risk categories are supplemented by research evidence gathered from surveys and interviews with stakeholders. The inclusion of an Islamic insight matters given mixed views at present regarding the permissibility of cryptocurrencies albeit some countries have imposed somewhat restricted function of cryptocurrencies for non-religious reasons. It is envisaged that this book will help enlighten stakeholders on this aspect of uncertainty and inspire fit and proper governance strategies for the public interest.