The course provides students in Finance with an introduction to machine learning methods. The course will concentrate on the application of the methods in Finance by minimising mathematical and statistical details. It is a complement and not a substitute to courses in Statistics and Econometrics.
Contents:
Introduction to Statistical Learning/Machine Learning
Subset Selection
Regularisation Methods: Ridge Regression and Lasso
Bootstrap
Tree-Based Methods
Tree-Based Methods for Classification
Unsupervised Learning: PCA, PCR and Clustering
Neural Networks
Articles using ML in Finance (NM)
Practical advice about Machine Learning
Ethics in Machine Learning
After completing the course, you will be able to:
Analyse financial data using machine learning methods
Use machine learning methods for prediction and decision making in Finance
Apply machine learning methods to solve research problem in Finance
Contents:
Introduction to Statistical Learning/Machine Learning
Subset Selection
Regularisation Methods: Ridge Regression and Lasso
Bootstrap
Tree-Based Methods
Tree-Based Methods for Classification
Unsupervised Learning: PCA, PCR and Clustering
Neural Networks
Articles using ML in Finance (NM)
Practical advice about Machine Learning
Ethics in Machine Learning
After completing the course, you will be able to:
Analyse financial data using machine learning methods
Use machine learning methods for prediction and decision making in Finance
Apply machine learning methods to solve research problem in Finance
- Teacher: Niklas Ahlgren
- Teacher: Theogene Habimana
- Teacher: Christian Johansson
- Teacher: Niclas Meyer