Abstract
The main objective of this project is to explore the growing need to understand the key factors that drive market capitalisation in today's intricate financial environment. As data, technology and machine learning increasingly shape the financial sector, investors and analysts need more sophisticated tools to better understand the dynamics of successful investments. The project aims to connect conventional financial analysis with modern predictive modeling, establishing a robust framework for assessing the influence of financial indicators on a company's market value. Uhis provides investors valuable insights to inform investment strategies and decision-making.
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Universidad Rey Juan Carlos
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Trabajo Fin de Grado leído en la Universidad Rey Juan Carlos en el curso académico 2024/2025. Directores/as: Juan Enrique Jiménez Fernández-Villamil
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market capitalization , financial indicators , principal component analysis , machine learning , exploratory data analysis , investment , financial prediction , financial analysis , Big Data , linear regression , clustering analysis , unsupervised learning , supervised learning , predictive models , investing , R-Studio , Predictive models , Financial model
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