The thesis consists of three chapters and studies the role of corporate bond dealers as liquidity providers in decentralized over-the-counter markets. The first two empirical chapters explore the impact of dealers' inventory financing constraints on their ability to act as middlemen in corporate bond markets. Specifically, the first chapter provides empirical evidence that dealers' financing constraints are a crucial determinant of the costs of their liquidity provision. The second chapter demonstrates that bonds handled by dealers with higher financing constraints are associated with substantially larger and abrupt price declines and slower price reversals in case of a rating downgrade from investment to non-investment grades. The third theoretical chapter studies the effects of post-trade disclosure on a dealer's dynamic trading strategy in a two-period dealership market and shows that in terms of customer welfare neither a regime with full nor one without post-trade transparency is universally dominating.
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.
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.
Цель работы: разработка концепции эффективной системы учета и отслеживания продукции, основанной на применении блокчейн-технологии, в связи c изменениями в маркировке табачной продукции. Задачи работы: - изучить принципы блокчейн технологий; - изучить принципы «smart-контракта» технологии; - рассмотреть преимущества и недостатки технологии; - разработать smart-контракт; - оценить экономическую эффективность проекта. Объект исследования – блокчейн-технологии. Предмет исследования - процесс маркировки продукции. В первой главе приведен обзор теоретического материала по технологии блокчейн. Вторая глава посвящена разработке методики использования «smart-контракта» при маркировке табачной продукции. В третьей главе рассмотрено применение смарт - контракта для конкретного бизнес-процесса. Результаты работы: практическим результатом работы является концепция умного контракта, который существенно упростит процесс, а также позволит маркировать продукцию и контролировать сбыт.
Cybersecurity has become a priority for organizations and governments due to the expeditious growth of information systems and networks in daily businesses. In this thesis, I first examine how security could be improved in a business environment. In the first study, I explore the regulatory options in improving the social welfare from a security service market. I identify two major sources of deficiency in such a market: incentive misalignment and information asymmetry. Based on a stylish analytical model, I propose that self-regulation is sufficient to solve the problem of misaligned incentive given the availability of audit trail, and government intervention with taxation is required to tackle the issue of information asymmetry. In the second study, I investigate the effect of a national security measure in the context of China and Australia. The difference-in-difference econometric model shows that implementing the national filter scheme weaken security, and further analysis suggests that the use of circumvention tools from users contributed most to this result. Besides policy analyses in cybersecurity, in the third study, I inspect the economics characteristics in cryptocurrency – a system empowered by cybersecurity in design for value transfer. Extending from the Mussa-Rosen model of choice on product quality, I find that the overwhelming transaction cost of cryptocurrency is caused by network congestion due to the capacity constraint. The empirical analysis with Bitcoin further supports this finding. These results offer important economics insight for firms, lawmakers and developers in designing security policies and solutions.
Modern insurance has been operating in the same business model since its inception while its recent IT improvement is mainly for specific functions without overall structural review. This paper is to incorporate the concept of a cryptocurrency, called Risk Coin, as the foundation of a new model to enhance the risk financing efficiency with capital market. Risk Coin is 1) a shareholding token of the premium fund with benefits from law-of-large-numbers, and 2) a cryptocurrency with benefits from seigniorage as fiat currency anchored at value of coin fund formed by collected premium and refund from loss payments. Applications in current insurance environment of pipeline model as well as in an innovative environment of platform model are simulated. Both results show a self-balancing mechanism that higher coin value from less coin preference, therefore, encouraging coin receivers to keep coins. Overall the new model will enhance the effectiveness of risk funding by keeping risk coins and also turn insurance deal to a win-win situation form zero-sum game through premium payment as gaining ownership of risk fund.
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.
Open access
Advanced Steganography and Watermarking Techniques
An online social media platform for cryptocurrency investor/traders to share ideas and showcase their portfolios. The platform will be able to capture investment information directly from user's cryptocurrency exchanges account and also factor in their crypto-mining asset to form an interactive portfolios for easy investment statistics tracking or show-casing. The platform will also serve as a advertisement platform for upcoming ICO(Initial Coin Offering),requiring minimal effort to set up and start reaching a targeted audience.
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
Virtual machine (VM) measurements data in IaaS cloud play a crucial role in integrity evaluation and decision making. Hence, the secure storage for these data has attracted more attention recently. This paper proposes a novel approach, named Mchain, to enhance the integrity and controllability of the secure storage. Especially, to enhance the integrity, a two-layer blockchain network is introduced. In the first layer, after the production, the data packages are first verified by leveraging a correspondence between a package and a policy, and a one-to-one relation among a VM, a user, and a node. After that, we propose a consensus achievement algorithm to construct a semi-finished block on a candidate block arranged by data packages. Meanwhile, the semi-finished block is distributed to all nodes, which can provide a certain integrity. In the second-layer, tamper-resistant metadata is generated by performing PoW tasks on the semi-finished block, resulting in strong integrity. Further, to enhance the controllability, a revisable user-defined policy-based encryption method with KP-ABE is proposed. It helps to flexibly control the scope of authorized verifiers. The experimental results on six scenarios with simulated data set show that the proposed approach is appealing in integrity and controllability, and the time overhead of data storage.