Ten Financial Applications of Machine Learning (Seminar Slides)
27 Pages Posted: 18 Jun 2018 Last revised: 27 Feb 2020
Date Written: June 16, 2018
Financial ML offers the opportunity to gain insight from data:
* Modelling non-linear relationships in a high-dimensional space
* Analyzing unstructured data (asynchronous, categorical)
* Learning complex patterns (hierarchical, non-parametric)
* Focusing on predictability over parametric adjudication
* Controlling for overfitting (early-stopping, cross-validation)
At the same time, Finance is not a plug-and-play subject as it relates to machine learning. Modelling financial series is harder than driving cars or recognizing faces.
In this presentation, we will review a few important financial ML applications.
For the full paper, see https://ssrn.com/abstract=3365271.
Keywords: machine learning, feature importance, prediction, out-of-sample, investments, risks, portfolio
JEL Classification: C02, D52, D53, G14
Suggested Citation: Suggested Citation