Machine Learning applications in Market Finance - Theory and Feedback

The aim of artificial intelligence is to have computers perform tasks that require human intelligence.

One of its many fields of study is Machine Learning, which uses statistical approaches to make machines learn, from a large amount of data, models that enable them to improve their own performance on tasks - without having been explicitly programmed to perform these tasks!

Data Science covers the design, analysis, development and implementation of these Machine Learning methods. Other professions are closely related to Data Science, such as Data Engineering, whose aim is to store high-quality, relevant data in a Big Data-oriented environment, and Data Visualization, which enables results to be displayed on dashboards.

The aim of this White Paper is to give you an overview of 6 families of Machine Learning algorithms that could have uses in Market Finance, and to provide you with concrete feedback on the subject.