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401-3915-DRL 2 Credits DR D-MATH

Machine Learning in Finance and Insurance

Lecturers & Examiners: Prof. Dr. Patrick Cheridito
Only for ZGSM (ETH D-MATH and UZH I-MATH) doctoral students. The latter need to register at myStudies and then send an email to with their name, course number and student ID. Please see
VVZ CR n/a

Last Updated: 2026-02-05 16:14:50

Abstract

This course introduces machine learning methods that can be used in finance and insurance applications.

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.

Resources

Lecture Notes

More information onhttps://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.

Learning Materials (Links)

General Information

Language
English
Levels
DR
Frequency
Yearly recurring

Examination

Type
ungraded semester performance
Doctoral students must obtain a passing grade in the mandatory practical projects.

Registration & Places

Priority: Registration for the course unit is only possible for the primary target group

Course Components

Type Title Time & Place Hours
lecture Machine Learning in Finance and Insurance
  • Tue 16:15-18:00 (HG D 7.1)
2 h weekly
exercise Machine Learning in Finance and Insurance
  • Wed 16:15-17:00 (HG D 1.1)
1 h weekly

Offered In