Saudi Cultural Missions Theses & Dissertations

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    Verification of Smart Contracts using the Interactive Theorem Prover Agda
    (Swansea University, 2024-07-25) Alhabardi, Fahad; Setzer, Anton
    The goal of this thesis is to verify smart contracts in Blockchain. In particular, we focus on smart contracts in Bitcoin and Solidity. In order to specify the correctness of smart contracts, we use weakest preconditions. For this, we develop a model of smart contracts in the interactive theorem prover and dependent type programming language Agda and prove the correctness of smart contracts in it. In the context of Bitcoin, our verification of Bitcoin scripts consists of non-conditional and conditional scripts. For Solidity, we refer to programs using object- oriented features of Solidity, such as calling of other contracts, full recursion, and the use of gas in order to guarantee termination while having a Turing-complete language. We have developed a simulator for Solidity-style smart contracts. As a main example, we executed a reentrancy attack in our model. We have verified smart contracts in Bitcoin and Solidity using weakest precondition in Agda. Furthermore, Agda, combined with the fact that it is a theorem prover and programming language, allows the writing of verified programs, where the verification takes place in the same language in which the program is written, avoiding the problem of translation from one language to another (with possible translation mistakes).
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    Risk and Uncertainty in Cryptocurrency Markets
    (University of East Anglia, 2024-04-23) Alsamaani, Abdulrahman; Kourtis, Apostolos; Markellos, Raphael
    This dissertation consists of three kinds of research. Each one has its purpose and aim to achieve. The first research tries to discover the most effective approach for forecasting the volatility of cryptocurrency returns utilising high-frequency data that can predict the volatility of dominant and less notable cryptocurrencies. The GARCH, IGARCH, EGARCH, GJR-GARCH, HAR, and LRE models were investigated, and univariate and comprehensive regression were used. Regarding univariate regression results, the HAR model beat the other models when forecasting one day ahead, while the EGARCH model outperformed the other models when forecasting seven and thirty days ahead. In addition, the HAR + EGARCH duo beat the other model couples when forecasting one, seven, and thirty days. Aside from the primary study, the out-of-sample analysis yielded conflicting results. These results will benefit investors, portfolio managers, and other financial professionals. The second study seeks to investigate the relationship between cryptocurrency returns and uncertainty indices along with assessing the impact of the Covid-19 pandemic period on both indices and cryptocurrency returns, determining which index has the most significant influence on cryptocurrency market results, and determining which indices pair has the most significant influence on cryptocurrency market returns. Ten cryptocurrency returns, as well as eight uncertainty indices, were investigated. The Quantile Regression, Multivariate-Quantile Regression, and Granger Causality tests were used. According to the Quantile Regression results, the Cryptocurrency Policy Uncertainty index and the Cryptocurrency Price Uncertainty index considerably impact cryptocurrency returns. On the other hand, the other indices have no influence on cryptocurrency returns. The Multivariate-Quantile Regression findings demonstrated that when the cryptocurrency market experiences a bull wave, the UCRY Policy Index + Central Bank Digital Currency Attention Index combination strongly impacts cryptocurrency returns. Nonetheless, when the cryptocurrency market has a bull run, the UCRY Policy Index and the Cryptocurrency Environmental Attention (ICEA) index combination considerably impact cryptocurrency gains. During the crisis, most of the overall sample findings were verified. These insights will benefit investors, portfolio managers, and policymakers. The third research strives to find the best model for forecasting the covariance matrix of cryptocurrency returns. To achieve this purpose, five models were thoroughly examined: BEKK, Diagonal BEKK, DCC, Asymmetric DCC, and LRE are all examples of BEKK. To assess prediction accuracy and capacity, three essential criteria were used: Euclidean distance (LE), Frobenius distance (LF), and the multivariate quasi-likelihood loss function (LQ). The LRE model outperformed the other models, predicting daily and weekly frequencies more accurately. Furthermore, the Mean Squared Error (MSE) and Mean Absolute Error (MAE) loss functions were used for validation. Except for LQ, the findings were in line with the forecasting criteria. These findings have significant implications for investors and portfolio managers aiming to enhance their risk management techniques. By utilizing the knowledge provided, they may be able to make better-informed decisions to lower portfolio risk.
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    Modelling and Forecasting Volatility of Bitcoin Cryptocurrency: A Comparative Study of Conditional Heteroscedastic Model
    (Queen Mary University of London, 2024-03-27) Alsulami, Amal M Saeed; Koutroumpis, Panagiotis
    This study details three cryptocurrencies: Bitcoin, Ethereum, and Tether. These cryptocurrencies provide a high return but also pose a high degree of risk to investors. The changes in the prices of the currencies impact their return volatility. This report presents the performance of two models employed in forecasting the volatility in the times series data. These models are the ARCH and GARCH. The research presented in this report employs a GARCH suite of models: ARCH (1), GARCH (1,1), as well as GARCH-M and PARCH. The three models are described based on the literature review and their roles. Using the data collected based on these models, prices, and changes in investments are determined. A methodology based on the models was applied to test the data and measure the stationarity and structural breakpoints and the ARCH effects. From the collected data and methods employed to evaluate it, this study concludes that the ARCH (1) model has the best performance for all three cryptocurrencies when it comes to return and risk.
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    Digital Currencies: Approaches to Regulation in International Financial Law
    (The University of Manchester, 2023-11-29) Aljohani, Talal; Arinabo, Fiona
    In an era where the adage 'cash is king' is increasingly challenged by digitalisation, the rise of digital currencies underscores a tectonic shift in international financial systems. From the innovative inception of Bitcoin's decentralised blockchain to the advent of stablecoins and Central Bank Digital Currencies (CBDCs), the landscape of monetary transactions is undergoing unprecedented change. Despite their rapid adoption and potential for reshaping the global financial architecture, digital currencies present unique regulatory conundrums. These challenges range from the inherent decentralisation that disrupts traditional oversight mechanisms to the potential misuse of pseudonymity and cross-border operability challenges. Drawing upon the evolution from Bitcoin to CBDCs, this dissertation interrogates how international financial law can adapt to this burgeoning realm. Exploring various regulatory stances adopted globally reveals the opportunities and pitfalls of differing approaches. While some nations embrace a laissez-faire attitude, fostering innovation but potentially overlooking risks, others tread a restrictive path, prioritising security over potential technological advancements. Amid these divergent pathways lies the necessity for robust, adaptive, and anticipatory regulatory strategies. By juxtaposing legal precedents with current developments, this study offers a holistic view of the digital currency domain, culminating in policy recommendations integrating cutting-edge technology, environmental considerations, and international collaboration. As the world ventures into this digital currency-driven future, the role of international financial law becomes crucial – not just as a guardian of financial stability but as a beacon guiding towards innovation, inclusivity, and systemic harmony.
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    Regulating Bitcoin in Saudi Arabia: the challenge of central bank digital currency
    (Saudi Digital Library, 2022-09-25) Tawfiq, Aghnar; Miglionico, Andrea
    In light of the world's rapidly changing environment, particularly the advent of the digital world and the digital economy, as well as the fast growth of the Internet and electronic engagement, this speed was apparent with the advent of virtual (or digital) currencies, the earliest and most renowned of which was Bitcoin, which expanded extensively and was dealt with by significant corporations. Then came the question of generating electronic currencies that are linked to central banks all over the world, but it is noteworthy that these currencies have not yet received proper regulation. The research is divided as follows: The first chapter provided a summary of past studies on the issue, as well as an introduction to the research, its aims, and methodology. The notions of blockchain and digital currencies, in addition to the common relationship between them, were then defined. The second chapter included a description of Bitcoin and also the positions of several nations, especially Saudi Arabia. Then a comparison of Bitcoin regulation in the United States and Europe. The third chapter also included the benefits and drawbacks of Bitcoin as well as the pros and cons of its regulation in Saudi Arabia; a definition of the central bank's digital currency; and a proposal for a new currency called RiyalCoin for its creation and regulation in Saudi Arabia, with its impact on the Saudi Vision 2030; and finally, the conclusion, results, and recommendations in the final chapter. The descriptive and analytical methodologies were utilised to clarify the problematic aspects of the study.
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