This book develops a quantitative stock market investment methodology using financial indicators that beats the benchmark of S&P500 index. To achieve this goal, an ensemble of machine learning models is meticulously constructed, incorporating four distinct algorithms: support vector machine, k-nearest neighbors, random forest, and logistic regression. These models all make use of financial ratios extracted from company financial statements for the purposes of predictive forecasting. The ensemble classifier is subject to a strict testing of precision which compares it to the performance...

This book presents the first practice-based account of Generative AI (GenAI) integration in postgraduate courses, structured across three approaches: course redesign and delivery, assessment redesign, and evaluation adaptations. The book introduces GenAI as a knowledge collaborator and reports the practical approaches, such as redesigning group activities into applied, research-driven tasks, providing detailed GenAI usage instructions, and requiring acknowledgement and reporting tools such as AI Contribution Forms, GenAI Integration Rubrics, and AI Contribution Assessment Forms, while...