Blockchain Papers

Amer Kareem, Rejwan Bin Sulaiman, Muhammad Umer Farooq

No abstract is available for this record.

Simon Shadman, Linus Roxbergh

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.

Jung Mann Lee

No abstract is available for this record.

Frederick Anning

No abstract is available for this record.

Hamza Abusalah

A proof system is a protocol between a prover and a verifier over a common input in which an honest prover convinces the verifier of the validity of true statements. Motivated by the success of decentralized cryptocurrencies, exemplified by Bitcoin, the focus of this thesis will be on proof systems which found applications in some sustainable alternatives to Bitcoin, such as the Spacemint and Chia cryptocurrencies. In particular, we focus on proofs of space and proofs of sequential work. Proofs of space (PoSpace) were suggested as more ecological, economical, and egalitarian alternative to the energy-wasteful proof-of-work mining of Bitcoin. However, the state-of-the-art constructions of PoSpace are based on sophisticated graph pebbling lower bounds, and are therefore complex. Moreover, when these PoSpace are used in cryptocur- rencies like Spacemint, miners can only start mining after ensuring that a commitment to their space is already added in a special transaction to the blockchain. Proofs of sequential work (PoSW) are proof systems in which a prover, upon receiving a statement χ and a time parameter T, computes a proof which convinces the verifier that T time units had passed since χ was received. Whereas Spacemint assumes synchrony to retain some interesting Bitcoin dynamics, Chia requires PoSW with unique proofs, i.e., PoSW in which it is hard to come up with more than one accepting proof for any true statement. In this thesis we construct simple and practically-efficient PoSpace and PoSW. When using our PoSpace in cryptocurrencies, miners can start mining on the fly, like in Bitcoin, and unlike current constructions of PoSW, which either achieve efficient verification of sequential work, or faster-than-recomputing verification of correctness of proofs, but not both at the same time, ours achieve the best of these two worlds.

Håkon Ohma Solberg, Thomas Hagen

Cryptocurrency and blockchain has conjointly become trending buzzwords in the business\nworld today. As the blockchain technology has become older and more researched, its areas\nof usage have broadened far beyond payment solutions like Bitcoin. In venture financing,\nblockchain has been used to establish a prominent fundraising tool, called initial coin offerings\n(ICO). An ICO is a crowdfunding method resembling initial public offerings, where ventures\nissue a blockchain based token, subject to public sale. ICO has become a lucrative financing\nmethod for blockchain affiliated ventures.\nThe hype around cryptocurrency has led to increased ICO attention. Everyone can invest in an\nICO, and thus, it has become a popular investment opportunity. This thesis looks at ICOs as\ninvestment objects, with the aim to find out what an investor should consider before investing.\nAdditionally, we assess whether ICOs are profitable financial instruments relative to its close\nsubstitutes, and evaluate measures to avoid scams.\nThe study is based on 104 companies that have had ICOs, and analyzes what factors influence\nboth ICO success rate, and post-ICO capital gains. Our results indicate that hype and pricing\nis influential on the outcome of an ICO, which in turn is important for subsequent price\nmovements. We have also observed that venture capital seed funded companies performed\nbetter in the ICO aftermath. By further using the results, we have also found that investors\nmay use these parameters when investing in an ICO to outperform both our benchmark\ncryptocurrency Ethereum, and other ICOs.

Anup Kumar Yadava

The virtual currencies or cryptocurrencies are growing rapidly in developed economies like UK, USA,and Japan. The motives of these currencies to create an efficient method of digital payment system which is globally accepted and their traders’ belief that these coins have some value, either a physical value or have a money value in terms of their native currency. The first cryptocurrency, Bitcoin (BTC) is facing competition today with newly launched ‘Altcoins’ or ‘Alternative coins”, like Ripple (XRP), Ethereum (ETH) etc., the market captured (market cap) by BTC is continuously decreasing and ranging between 30 to 35% of the total market cap. The newly launched ‘Altcoins’ are technically efficient and have an audience with different motives compare to BTC, also these coins have a huge potential of growth level within a time compare to BTC, Because BTC prices are very high and its growth level is low compares with newly genesis coins. This article deals some important aspects of cryptocurrency worldwide with an addition to explore its role in the Indian Economy because India is not apart from this emerging trend. Many Indian trading exchanges are started within last few years, rather Government of India is not in favor of crypto trading. The aim of this article to critically examine working features of cryptocurrencies, eg; Mining, how crypto Initial Coin Offerings (ICOs) are working, their exchange markets, and how this peer-to-peer (P2P) currency blockchain works. This article also critically evaluate Indian crypto traders’ motives and try to find out a way to deal with the related issues of cryptocurrencies for Indian Economy.

Mark Holub, Jackie Johnson

No abstract is available for this record.

Alexander Karzov

The purpose of this research is to investigate is it possible to receive extra profit in crypto market by using technical analysis methods. The oldest and the most famous cryptocurrency bitcoin has been selected as a subject. A test was executed during two-year period from 1.10.2016 to 1.10.2018.
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\n The research describes a nature of bitcoin and explains why it raises interest as an investment. Then from technical analysis methods are selected widely used indicators and developed three strategy based on them. First strategy is based on the moving average crossover, second one is based on the crossover of the RSI and the Bollinger Bands and third one is based on stochastic oscillator. Every strategy is tested with a trend filter and without it. A benchmark in the test is traditional buy & hold strategy.
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\n According to empirical test, every strategy can show greater return compared to buy & hold strategy. It was also observed that if both “Only Long” and “Only Short” versions are profitable, combined “Long & Short” version shows much higher profit, than the simple sum of the results of “Only Long” and “Only Short” versions. Strategy 1 provided the best performance and Strategy 3 the worst both in terms of profit and in terms of risk. The results of adding the trend filter were ambivalent in terms of profit, but totally worthwhile in terms of risk.

Angelos Kalaitzis

In this thesis, an analysis of Bitcoin, Monero price and volatility is conducted with respect to S&P500 and the VIX index. Moreover using Python, we computed correlation coefficients of nine cryptocurrencies with two different approaches: Pearson and Spearman from July 2016 -July 2018. Moreover the Pearson correlation coefficient was computed for each year from July2016 - July 2017 - July 2018. It has been concluded that in 2016 the correlation between the selected cryptocurrencies was very weak - almost none, but in 2017 the correlation increased and became moderate positive. In 2018, almost all of the cryptocurrencies were highly correlated. For example, from January until July of 2018, the Bitcoin - Monero correlation was 0.86 and Bitcoin - Ethereum was 0.82.

Lars Klöhn, Nicolas Parhofer

No abstract is available for this record.

Niklas Grundström

Cryptocurrencies has become a very hot topic recently, with Bitcoin being the most popular. The increase in interest has led to an incentive to create payment systems for the currency that makes it easier to use for day-to-day shopping. A lot of companies are inves- tigating possible solutions for credit cards that are used for cryptocurrencies. This thesis aims to present and perform a security analysis on an already created concept of a credit card payment system for Bitcoin. The security analysis is done in a systematical approach where the modules were analyzed with predetermined restrictions and assumptions. The restricitons and assumptions are then removed one-by-one to find potential threats in the system. The outcome of the analysis is then evaluated in an attempt to find possible im- plementation methods that would mitigate or prevent the discovered threats. The possible implementations are also evaluated in terms of how they would affect the system.

Ewelina Marcińczyk, Bartosz Borowik

The paper discusses cryptocurrencies both in terms of their applicability to everyday financial transactions as well as in terms of criminogenic factors. The Authors will present practical ways to settle in virtual currency, institutions in which bitcoin payments can be made and the possibility of converting them into traditional currencies. Also factors conducive to combine cryptocurrencies with the criminal world, such as the anonymity of both the Internet and cryptocurrencies will be analysed. In addition, the paper presents the real impact of cryptocurrencies on the increase in crime worldwide, both related to financing of terrorism and in connection with taxation of income. The data and conclusions contained in this study are a contribution to the discussion on the sense of investing in cryptocurrencies, and above all on the opportunities and threats that entail the widespread introduction of this method of payment.

Hakan Uçak

No abstract is available for this record.

M. N . Makhonina, Olga Zinisha

No abstract is available for this record.

Stephanie Riedl

Cryptocurrencies as an investment have received increasing attention by media and international governments over the last years.However, little is known yet about the dynamics that drive these highly volatile alternative assets.This thesis studies the dynamic interdependencies between the volatility of Bitcoin, Litecoin, Ripple, Dogecoin and Feathercoin via the Dynamic Conditional Correlation model by Engle (2002) with the multivariate Student-t distribution.The main question is whether a multivariate approach improves the Value at Risk forecasting accuracy for the conditional heteroscedasticity in comparison to univariate GARCH-type models.Results show that there is a high interconnectedness between the volatility of the currencies.However, the Dynamic Conditional Correlation model can not deliver better forecasting results than the univariate GARCH-type models for the individual cryptocurrency return series. Contents List of Figures iv List of Tables vList of Tables 1 Summary Statistics for daily log returns 100 of cryptocurrencies.Log returns are calculated using: r t = 100ln(P t /P t-1 ).Returns are observed until 14 th of March 2018.Market cap is captured at 14 th of March 2018.Jarque-Bera-Test checks for deviation from normality (skewness S different from zero and kurtosis K different from 3): JB = T (S/6 + (k -3) 2 /24), is distributed as X 2 (2) with 2 degrees of freedom.Its critical value at the five-percent level is 5.99 and at the one-percent it is 9.21. . . . . . . . . . . . . . . . . . . . . . . . . 2 AIC and BIC for the estimated GARCH-type models. t is modelled via an ARMA-(1,1) process. t is modelled via a GARCH-type process of order (1,1).T=1544.Lowest AICs and BICs per group are written in bold letters. . . . . . . . . . . . . . . . . . . . . . . . . . 3 1%-and 5%-Value at Risk results for the univariate GARCH-type models.1-day-ahead rolling forecast with recursive window, model parameters refitted every 300 observations.Model is built on a training data set of 800 observations, which leaves 744 out-of-sample forecasts.% Viol: Percentage of VaR violations at = 1% and = 5%.L uc : p-value for test of unconditional coverage; L cc : p-value for test of conditional coverage.Values printed bold if p < 0.05. . . . . . . 4 Model parameters of the selected GARCH models. t is modelled via an ARMA-(1,1) process.T=1544.*** p-value < 0.001; ** pvalue < 0.01; * p-value < 0.05.Q(10): p-value of Ljung-Box test on squared standardized residuals for lag = 10; ARCH(5): p-value for weighted ARCH LM test for lag = 5. . . . . . . . . . . . . . . . . 5 Lag = 0 sample correlation matrix 0 (Pearson) of the five crypto currency log return series.T = 1554. . . . . . . . . . . . . . . . . .6 Model parameters for the estimated DCC models.T=1544, k=5, *** p-value < 0.001; ** p-value < 0.01; * p-value < 0.05.Model parameters for univariate volatility series are listed in table (4). . .7 Mean and (standard deviation) of the lag = 0 correlations in the multivariate volatility of the currencies estimated by the DCC model in equation (57).T=1544. . . . . . . . . . . .

Hallvard Kristoffer Boland Haugen, Andreas Fougner Engebretsen

The topic of revenue streams in the music industry has been frequently discussed since the transition from sales to streaming started when Spotify launched in 2008. Even though revenues in the industry have reached new heights, musicians express dissatisfaction with lower royalty payouts. Moreover, it has become increasingly more difficult to understand the royalty calculations. With today's complicated licensing agreements, money flows through a complex chain of third parties before it reaches the musicians. The industry struggles with transparency and efficiency, and the musicians are paying the price. Meanwhile, blockchain technology has developed since its first implementation with Bitcoin in 2008. Today, more advanced blockchains can run decentralized transparent applications that utilize the technology's efficient transaction system. With the industry issues and the promises of blockchain in mind, we investigate how blockchain technology can be applied to solve value chain problems within the music space.\n\nIn this thesis, we identify core issues in the music industry, propose a decentralized application (dApp) that attempts to solve these issues and implement the proposed solution. We develop the business logic using smart contracts on the Ethereum blockchain and make an associated web application using a JavaScript framework. The dApp works as a global copyrights database where musicians can register and license musical works. We exploit Ethereum's efficient transactional system to manage license purchases. Furthermore, we discuss the advantages and disadvantages of blockchain based solutions.

Artur Paździor, Grzegorz Kłosowski

Cel – Celem artykułu jest prezentacja koncepcji systemu informatycznego umożliwiającego prognozowanie kursu kryptowaluty bitcoin (BTC) w odniesieniu do waluty euro. Metodologia badania – Na potrzeby realizacji tak sformułowanego celu opracowano model sztucznej sieci neuronowej – perceptronu wielowarstwowego. W ramach badań dobrano zmienne wejściowe, od których uzależniono kurs BTC. Pozyskano także odpowiednie dane, pochodzące z dziennych notowań kursów wybranych walut i metali. Dane poddano stosownej obróbce matematycznej w celu ich dostosowania do wykorzystania podczas uczenia, walidacji i testowania sztucznej sieci neuronowej. Oryginalność/wartość – Oryginalny był dobór wektora zmiennych wejściowych, umożliwiających prognozowanie kursu BTC. Wyniki przeprowadzonych eksperymentów potwierdziły wysoką skuteczność prognozowania w perspektywie jedno- i dwudniowej. Wysokie wartości współczynnika regresji (R) i mały błąd średniokwadratowy (MSE) świadczą o tym, że opracowany system predykcyjny prawidłowo przewiduje kursy analizowanej kryptowaluty nie tylko w odniesieniu do danych historycznych, lecz także dla wartości bieżących i przyszłych.

Lauren Rhue

No abstract is available for this record.

matthew baldree, paul widhalm, brandon hill, Matteo Ortisi

In this paper, we present a tool that provides trading recommendations for cryptocurrency using a stochastic gradient boost classifier trained from a model labeled by technical indicators. The cryptocurrency market is volatile due to its infancy and limited size making it difficult for investors to know when to enter, exit, or stay in the market. Therefore, a tool is needed to provide investment recommendations for investors. We developed such a tool to support one cryptocurrency, Bitcoin, based on its historical price and volume data to recommend a trading decision for today or past days. This tool is 95.50% accurate with a standard deviation of 0.54%. From our analysis, we conclude that Bitcoin is a unique asset with similarities to gold. As a young asset, it lacks economic fundamentals making it very difficult to predict. By leveraging technical momentum indicators to provide buy, sell, and hold markers or labels, a tool can be developed that performs as good or better than a buy and hold trading strategy in a bear market, bull market or both markets.

Filip Filipović, Joakim Nilgard

Bitcoin is a phenomenon that is new and there is little information on how and why it behaves as volatile as it does. This thesis uses existing data on Bitcoin’s exchange rate to estimate a model that describes the pattern and use it in a financial risk analysis. We also aim to contribute as a foundation for further studies in this field.\nThe statistical properties of the log-return of the exchange rate are analysed and it is deemed to be iid. From the eleven distributional candidates we study is the fitted skew generalised t distribution proven to represent the data best after evaluation by criteria and statistics. The estimated VaR and ES show that the rate is volatile and that the risk from investments is still high.\nThe findings show that it is necessary to describe the exchange rate with complex and flexible distributions, and even if the data shows more stability today than earlier is it important to show caution in interpretations and evaluations on the topic.\nKeywords: Bitcoin, cryptocurrencies, statistical distributions, statistical analysis, exchange rate, modelling

M. A. Volobuev

Развитие обращения криптовалют на примере биткоина Волобуев М.А., студент, Технический институт (филиал

Thomas E. Portegys

The latency and throughput of blockchain-based cyrptocurrencies is a major concern for their suitability as mainstream currencies and as transaction processors in general. The prevalent proof-of-work scheme, exemplified by Bitcoin, is a deliberately laborious effort: the time and energy required to mine blocks makes the blockchain virtually immutable and assists in the consensus-reaching process. Coinspermia (coin=money + spermia=seed) is a different approach: transactions are concurrently seeded throughout a network of peer nodes to an extent sufficient to achieve a high reliability of essential currency operations, including the fast transfer of coins from an owner to a recipient, and the prevention of double spending. A number of Bitcoin features are retained in Coinspermia, including transaction input-outputs and cryptographic addresses and signing, but no special proof-of-work is required to commit transactions. Instead, a client can be assured of an operation completion when a quorum of network nodes acknowledge the operation, which can occur before a transaction operation finishes propagating through the network. Simulation substantiates improved latency and throughput.

Ashish Rajendra Sai, Jim Buckley, Andrew Le Gear

Proof Of Work Blockchains such as Bitcoin and Ethereum exhibit a low Transaction Per Second (TPS) that impacts the scalability of the blockchain. Manipulating the block creation time can yield a higher TPS. A lower block creation rate results in a higher Stale Block rate that has a direct impact on the security of blockchain. We intend on using a novel Proof of Work Classification model under a varying level of difficulty to classify an instance of blockchain with a threshold (Block-time) on the basis of it’s resilience to selfish mining and double-spending attacks. Use of an ideal block creation time can help Proof of Work blockchains scale and attain a higher TPS without trading off security. The classification model can further be extended to find an optimal block-size.