https://www.um.edu.mt/library/oar/handle/123456789/140860 Sun, 05 Apr 2026 02:49:01 GMT 2026-04-05T02:49:01Z https://www.um.edu.mt/library/oar/handle/123456789/141258 Title: Hawkes-Heston models and their application to high frequency financial data Abstract: This dissertation investigates the modelling of financial time series through the integration of two well-established frameworks: the Hawkes process and the Heston stochastic volatility model. The resulting Hawkes-Heston diffusion model captures both the continuous evolution of asset prices and the discrete, self-exciting nature of jumps, offering a more flexible structure for analysing high-frequency financial data. Using Tesla Inc. as a case study—due to its pronounced volatility and eventdriven price behaviour this work applies multiple variations of the Hawkes-Heston model, where jumps may appear in the price process, the volatility process, or both. The parameters of each model are estimated using high-frequency intraday data, with jumps detected and removed using the non-parametric L-estimator. Simulations based on the fitted models are used to compute risk measures such as Value at Risk (VaR) and Expected Shortfall (ES), allowing for performance comparisons across the model variations. For benchmark comparisons, VaR and ES results based on an estimated Heston model are also considered. The results provide insights into the dynamic interplay between continuous volatility and discrete jumps and demonstrate the practical utility of Hawkes-driven diffusions in financial risk modelling. It also is concluded that Hawkes-driven diffusions provide similar measures of risk while, surprisingly, Heston model-based risk measures are more conservative due overcompensation in the diffusion term. Description: B.Sc. (Hons)(Melit.) Wed, 01 Jan 2025 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/141258 2025-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/141112 Title: Applications of Markov decision processes to investment-related problems Abstract: Markov Decision Processes (MDPs) offer a powerful framework for solving sequential decision making problems under uncertainty, where each decision influences the future state of a system. This dissertation investigates the application of MDPs to investment related problems, focusing on portfolio optimization and consumption-investment decisions within dynamic financial markets. The dissertation begins by defining MDPs and highlighting their relevance to financial optimization problems. An important objective of this research is to explore the existence of optimal portfolios under various conditions in both investment-only and consumption-investment scenarios. The investment-only case is primarily concerned with maximizing the expected utility of the terminal wealth, while the consumption-investment case seeks to optimize the expected utility of the terminal wealth along with the expected utility of intermediate consumption throughout the investment period. Both scenarios are modelled as utility maximization problems. The dissertation presents the necessary financial market framework, followed by a detailed analysis of MDPs and the Bellman optimality equations. This is then extended to investment problems for the power and exponential utility functions for the investment only and consumption-investment scenarios. The theory presented is then applied to a simulated dataset to demonstrate how an optimal portfolio strategy for both scenarios can be found using a binomial model for the financial market. Description: B.Sc. (Hons)(Melit.) Wed, 01 Jan 2025 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/141112 2025-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/141110 Title: Bayesian hidden Markov models and strategies for buying and selling stocks Abstract: Predicting stock market behavior is a highly sought-after area of research, offering valuable insights for both individual investors and corporations. This dissertation aims to address this challenge by utilizing Bayesian Hidden Markov Models to determine underlying stock market regimes in order to inform trading decisions. By working under a Bayesian framework, uncertainty in parameters is described through posterior distributions, allowing for a more uncertainty-aware and reliable approach when compared to traditional point estimates. This study utilizes the daily closing prices of three financial assets, varying in their inherent volatility, and uses results to implement regime-based trading strategies. The findings showed that the Bayesian hidden Markov model was able to identify regime shifts successfully, and implement trading strategies that outperformed a passive buy-and-hold trading approach. Moreover, results suggested that higher volatility assets yielded a greater return on investment by allowing the model to fully leverage its regime identification ability in more dynamic markets. Lastly, the implications that transaction costs have on the trading strategies were assessed, further simulating a real life trading scenario. Description: B.Sc. (Hons)(Melit.) Wed, 01 Jan 2025 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/141110 2025-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/141107 Title: Rhythms of identity : musical omnivorousness, cultural capital, and social stratification through SEM analysis Abstract: In recent decades, a dominant hermeneutic approach in the study of taste has been to conduct a parallel analysis on distinctions in social demographics and human experiences. Taste then, particularly musical taste, is socially construed, influenced by the rapid digitisation of mass media, and externally imbued aesthetic dispositions resulting from personalised upbringings, early exposures, and economic and financial conditions. In this dissertation, a survey was designed with the aim of understanding the general musical taste profile of the Maltese population, pointing at disparities between those who listen to a variety of musical genres (musical omnivores) and those who restrict themselves to just a few (musical univores), whilst also commenting on cultural capital and motivations for listening to music. Additionally, focus is placed on current and childhood exposures to music, studying whether surrounding communities or, on a more pedagogical note, educational institutions, condition one’s tastes in any particular way. Exploratory Factor Analysis and Reliability Analysis were employed on the survey data obtained, revealing a nine factor internally consistent solution. This factor structure was further validated by a well-fitted Confirmatory Factor model (CFI: 0.962, TLI: 0.956, RMSEA: 0.057, SRMR: 0.093). Structural Equation modelling was then utilised, pointing at interesting covariances and predictive effects of certain demographic variables (e.g. sex, age, education) and musical omnivorousness (the number of genres one enjoys) on the factors attained (e.g. cultural participation, appeal to classical and opera, childhood exposure to music). Goodness of fit tests indicated that the structural equation model fits well (CFI: 0.943, TLI: 0.958, RMSEA: 0.048, SRMR: 0.097), suggesting that social stratification with respect to tastes and lifestyles is indeed tenable. In order to methodically point at differences in musical tastes and tendencies between those with high musical omnivorousness (listen to three or more genres) and those with low musical omnivorousness (listen to two or less genres), a Multi-Group Structural Equation model was developed (CFA: 0.969, TLI: 0.978, RMSEA: 0.046, SRMR: 0.108). Although similarities were observed across the groups, vastly distinct covariance and regression structures were obtained, with certain tendencies of each group deviating from the normative behaviours observed in the total sample. Description: B.Sc. (Hons)(Melit.) Wed, 01 Jan 2025 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/141107 2025-01-01T00:00:00Z