| Abstract | This course introduces machine learning methods that can be used in finance and insurance applications. |
| Learning objective | The goal is to learn methods from machine learning that can be used in financial and insurance applications. |
| Content | Linear, polynomial, logistic, ridge and lasso regression, dimension reduction methods, singular value decomposition, kernel methods, support vector machines, classification and regression trees, random forests, XGBoost, neural networks, stochastic gradient descent, autoencoders, graph neural networks, transfomers, credit analytics, pricing, hedging, insurance claim prediction. |
| Lecture notes | More information on https://people.math.ethz.ch/~patrickc/mlfi |
| Literature | Matthew F. Dixon, Igor Halperin, Paul Bilokon (2020). Machine Learning in Finance. Springer.
Ian Goodfellow, Yoshua Bengio and Aaron Courville (2020). Deep Learning. MIT Press.
Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani (2021). An Introduction to Statistical Learning. Springer.
Marcos Lopez de Prado (2018). Advances in Financial Machine Learning. Wiley.
Marcos Lopez de Prado (2020). Machine Learning for Asset Managers. Cambridge Elements.
Mario V. Wüthrich and Michael Merz (2023). Statistical Foundations of Actuarial Learning and its Applications. Springer. |
| Prerequisites / Notice | The course requires basic knowledge in analysis, linear algebra, probability theory and statistics. |
Competencies | | Subject-specific Competencies | Concepts and Theories | assessed | | Techniques and Technologies | assessed | | Method-specific Competencies | Analytical Competencies | assessed | | Problem-solving | assessed | | Project Management | assessed | | Social Competencies | Communication | assessed | | Cooperation and Teamwork | assessed | | Leadership and Responsibility | assessed | | Personal Competencies | Adaptability and Flexibility | assessed | | Creative Thinking | assessed | | Critical Thinking | assessed | | Integrity and Work Ethics | assessed | | Self-direction and Self-management | assessed |
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Performance assessment as a semester course