Machine Learning in Finance

Machine learning has been revolutionizing the financial industry, offering the potential to disrupt traditional structures and practices. This subject is meticulously organized around several real-world issues to introduce fundamental economic and financial problems and demonstrate how machine learning can provide transformative solutions to these problems. Throughout the course, case studies will be used to illustrate these core concepts, allowing students to see the practical application of theoretical knowledge. The emphasis is on building a strong foundation in machine learning techniques and their financial applications, ensuring that students can confidently apply these concepts in novel situations they may encounter in their professional careers. Additionally, students will engage in hands-on projects and exercises that reinforce the material covered in lectures. This practical approach ensures that they not only understand the theoretical underpinnings but also gain the skills needed to implement machine learning solutions in real-world financial contexts. By the end of the course, students will have a comprehensive understanding of how machine learning can address various economic and financial challenges, preparing them to drive innovation and improvement in the financial industry.

• 1identify fundamental economic and financial real‐world problems in the society;
• 2determine how major advances in artificial intelligence and machine learning are applicable to finance problems;
• 3demonstrate basic knowledge of techniques in artificial intelligence and machine learning;
• 4distinguish disruption from mere computerisation;
• 5acquire skills to solve practical financial problems using Machine Learning;
• 6learn to think outside the box;
• 7critically evaluate new ideas and their implementation;
• 8recognise opportunities to innovate.