Course

Machine Learning in Finance (ESE, code FEM21045)

Teacher(s)

Dick van Dijk, Karel de Wit
Research field

Finance
Dates

Period 1 - Sep 04, 2023 to Oct 27, 2023

Course type

Field
Program year

Second
Credits

3

Course description

This is a course organized by ESE, course code: FEM21045. Please check the exact dates for this course and how to register.

The main topics covered in this course are:

Regularization
Classification and Regression Trees, Forests and Ensemble Methods
Neural Networks
Support Vector Machines
Clustering

Course literature

The course is based on the textbook

Hastie, T., R. Tibshirani, and J. Friedman (2009), The Elements of Statistical Learning - Data Mining, Inference, and Prediction, 2nd Edition, Springer (available online here)

For each topic, the relevant sections of the book will be indicated on Canvas [both compulsory and further reading] For the different topics covered during the course, additional material in the form of recent journal articles and working papers will be provided. Some of these papers you are required to read. For those who want to dig deeper into a certain topic, we will also provide some supplementary material. Note that reading this supplementary material is optional and you will not be tested from that content.