Saudi Cultural Missions Theses & Dissertations
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Item Restricted Return Spillovers and Market Integration in Islamic Finance: Return Spillovers and Market Integration in Islamic Finance: Empirical Evidence from Sukuk and Sectoral Indices Empirical Evidence from Sukuk and Sectoral Indices(Saudi Digital Library, 2026) Alangari, Sultan; Hassan, MohammadThis study investigates the return spillovers and their underlying determinants in nineteen sukuk markets from 4 regions. Using the Diebold and Yilmaz (2014) and wavelet coherence approaches, this study quantifies the dynamic spillover index (DSI) and identifies the key determinants for aggregate and regional Sukuk markets. The findings reveal that the sukuk market return is moderately vulnerable to exogenous economic shocks, providing potential diversification benefits for investors. Though the collective spillovers follow a downward trend, as the markets mature, the total spillover intensity increases significantly throughout the COVID-19 period. Wavelet coherence further indicates that the global Islamic equity market (MSCI_I) and European currency volatility (EVZ) are the key driver of full-sample Sukuk spillovers. However, regional decomposition discloses systematic heterogeneity in spillover determinants: crude oil volatility (OVX) and EVZ dominate for GCC markets, EVZ for Asian markets, VIX for African markets, and VIX and OVX for European sukuk market — underscoring that a uniform monitoring framework is insufficient across structurally distinct Islamic market environments. The findings are of intrinsic interest and offer practical insights to Islamic portfolio managers and policymakers towards ethical investment in the light of intensified market integration.8 0Item Restricted What Makes Markets Work: A Structural Analysis of Political Attributes Driving Capital Market Strength Across Regimes(Saudi Digital Library, 2025) Jamalallail, Abdullah; Ventouri, AlexiaThis study examines the political and institutional determinants of capital market strength across democratic and autocratic regimes. While existing literature often contrasts regime type in isolation, this research integrates governance quality and regime classification within a unified empirical framework to assess their relative and interactive effects on market development. Using a panel dataset of 11 countries, both advanced and emerging, observed between 2014 and 2024, the analysis evaluates how institutional variables drawn from the World Governance Indicators influence capital market depth and resilience. Two dependent variables are employed: the log of stock market capitalisation relative to GDP as a measure of market depth, and a newly constructed Composite Strength Market Index (CSMI) capturing size, liquidity, and stability. Panel regression techniques with clustered standard errors are applied to test four hypotheses concerning the roles of rule of law, regulatory quality, state capacity, regime type, and macroeconomic fundamentals. The findings demonstrate that governance quality, particularly rule of law and regulatory quality, is positively associated with capital market development. Economic size, proxied by GDP, emerges as a strong predictor of market depth. Regime type alone is not a statistically significant determinant once institutional quality is controlled for. Interaction analysis reveals that democratic accountability strengthens market outcomes within democracies, while in autocracies, state capacity and institutional effectiveness can partially substitute for democratic mechanisms. Across both regime types, political stability significantly enhances market resilience. Overall, the results suggest that capital market strength depends less on regime classification and more on institutional soundness, legal protections, and policy consistency. Effective governance, rather than political ideology alone, forms the structural foundation upon which resilient financial markets are built.12 0Item Restricted Analyzing the Impact of Economic Policy Uncertainty and Investor Sentiment on Stock Market Dynamics (Returns & Volatility)(University of Liverpool, 2024-09-12) Alahmare, Reem; Hizmeri Canales, RodrigoThis dissertation investigates the joint effects of Economic Policy Uncertainty (EPU) and investor sentiment on stock market dynamics, particularly focusing on the S&P 500 index. The study integrates sentiment analysis from real-time news and social media data with EPU indices to develop predictive models for stock returns and volatility over a 10-year period (2013-2023). By employing econometric techniques, such as LASSO regression, Ordinary Least Squares (OLS) regression, and GARCH models, the study aims to provide a more comprehensive understanding of how these psychological and macroeconomic factors influence market behavior. The findings highlight that investor sentiment plays a stabilizing role in periods of positive sentiment, reducing market volatility and enhancing stock returns. In contrast, negative sentiment amplifies volatility, especially when combined with high levels of policy uncertainty. EPU, particularly as measured by the News-Based Policy Uncertainty Index, emerges as a critical driver of volatility, affecting market stability during periods of fiscal and trade policy uncertainty. The interaction between sentiment and EPU is shown to provide better predictive accuracy for stock market behavior compared to traditional financial models. The research contributes to the growing body of literature by developing models that integrate real-time sentiment data with EPU, offering more nuanced insights into stock market volatility and returns. The practical implications are significant for both investors and policymakers, providing tools to improve risk management and decision-making. Investors are advised to consider sentiment and policy uncertainty together when assessing market risks, while policymakers are encouraged to ensure transparent communication to minimize uncertainty and stabilize markets. This study advances our understanding of the roles of sentiment and policy uncertainty in financial markets, highlighting their combined influence on stock market volatility and returns, and offering practical strategies for navigating periods of economic uncertainty.26 0Item Restricted Enhancing Stock Price Prediction Using Machine Learning Models: A Comparative Study of SVM, LSTM, and GRU(University College London, 2024-08) AlMohamdy, Razan; Andrea, DucciThis study evaluates the effectiveness of three machine learning models—Support Vector Machine (SVM), Long Short-Term Memory (LSTM) networks, and Gated Recurrent Units (GRU)—in predicting the stock prices of Saudi Aramco. Using historical stock price data and technical indicators, the models were assessed based on their accuracy in both long-term and short-term predictions. The findings reveal that LSTM and GRU significantly outperform SVM, with LSTM showing superior performance in capturing long-term dependencies and GRU offering a balance between accuracy and computational efficiency. Specifically, LSTM achieved a Root Mean Squared Error (RMSE) of 0.0516 and a Mean Absolute Error (MAE) of 0.0323, while GRU recorded an RMSE of 0.0539 and an MAE of 0.0234. In contrast, SVM exhibited a much higher RMSE of 0.1712 and an MAE of 0.1079, indicating its struggles with market volatility. The 30-day prediction analysis further highlighted the strengths of LSTM and GRU in short-term forecasting, with both models maintaining an R² value above 0.993, while SVM lagged behind at 0.9332. Despite their advantages, the study identified limitations such as the exclusion of external economic factors and the models' varying effectiveness across different time horizons. These findings contribute to the growing field of financial forecasting, offering practical insights for investors and analysts on model selection. Future research is recommended to incorporate broader economic indicators, explore cross-market validation, and enhance the models' responsiveness to short-term market fluctuations.32 0Item Restricted The Role of Oil Prices, and Inflation on Gold Prices in the Middle East(University of Sussex, 2024) Abudawood, Ruwa; Klein, AlexanderThis study investigates the dynamic relationship between oil prices, inflation, and gold prices within the context of Middle Eastern economies. Using advanced econometric techniques, including Vector Error Correction Models (VECM) and cointegration tests, the analysis reveals that fluctuations in oil prices significantly influence gold prices in the region, overshadowing the impact of inflation. Given the heavy reliance of Middle Eastern countries on oil exports, understanding these interconnections is crucial for policymakers, investors, and economic planners. The findings underscore the role of gold as a strategic hedge against oil price volatility and provide actionable insights for improving economic resilience and investment strategies. This research contributes to the broader discourse on commodity markets and macroeconomic stability in oil-dependent regions.7 0Item Restricted The effect of making investment decisions for individual investors in the Saudi stock market(Saudi Digital Library, 2023-08-24) Alsulami, Dalal; Scherrer, CristinaBehavioural finance plays a significant role in financial markets because it has a positive and negative impact on the financial results of individual investors and even investment institutions. Although conventional financial theory asserts that investors act logically, modern finance theory has shown that individual investors make irrational decisions when it comes to investing. In addition, the factors that affect investment decisions change over time, depending on the situation, the investment environment, the person, the security, etc. For this reason, this study is conducted in Saudi Arabia with the goal of investigating many different perspectives, such as the factors that influence individual investors, the behavioural factors influencing individual investment decisions on the Saudi stock market, and the extent to which behavioural factors influence individual investment decisions in the Saudi stock market. The study uses random sampling to select 70 investors for the primary data, which was collected using questionnaires. The survey has been divided into four sections covering the theory of behavioural finance: herding effect, prospect theory, market effect, and, lastly, anchoring and availability bias. The findings of this study show that behavioural biases (heuristics, prospect theory, herding, market effect, anchoring, and availability bias) have a statistically and hypotheses-tested significant effect on investor decisions in the Saudi stock market (SSM), which suggests that behavioural factors have a substantial impact on SSM investor decisions.313 0