MACHINE LEARNING IN FINANCE (PhD Course)

Apr 10 2019

This course aims at providing an introductory and broad overview of the field of Machine Learning (ML) with the focus on applications on Finance.

Detailed Program:

1.Introduction to Financial problems and their classical solutions

2.Introduction to Machine Learning

Supervised Learning

  – Overview of regression and classification techniques

  – Financial applications: price prediction, modeling bank failures

Unsupervised Learning

  – Overview of clustering and dimensionality reduction techniques

  – Financial applications: stock returns, estimation of equity correlation matrix

Reinforcement Learning

  – Overview of value-based and policy-based techniques

  – Financial applications: option pricing, stock trading


Venue: Department of Mathematics, Politecnico di Milano

Time Table:

Introduction to Financial applications (Baviera, Marazzina, Rroji):

June 13: 9:30-12:00, 14:30-17:00 (Prof. Marazzina)

June 17: 9:30-12:00 (Prof. Baviera), 14:30-17:00 (Prof. Rroji)

June 18: 9:30-12:00 (Prof. Baviera), 14:30-17:00 (Prof. Rroji)

Machine Learning (Restelli, Baviera):

June 20, 21, 25, 27, 28: 10:00-13:00 (Prof. Restelli)    

July 1: 15:00-17:00 (Prof. Baviera)

For information: daniele.marazzina@polimi.it

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