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Machine learning for finance

Supervisors

Suitable for

MSc in Computer Science
Mathematics and Computer Science, Part C
Computer Science and Philosophy, Part C
Computer Science, Part C

Abstract

This project aims to use machine learning techniques such as ensemble learning, convolutional neural networks etc. to predict spot prices for a variety of industries. Machine learning is increasingly used in finance to make predictions as well as to aggregate among existing strategies for making investments over time. We will use various free as well as proprietary data sets to assess the value of our newly developed methods in terms of both profit and risk, and compare them with state of the art techniques. This will also involve developing new “lucky factors” (features) that can be extracted from the data to inform and improve existing and new investment strategies. The expectation is that the work will lead to a conference publication.

Prerequisites: This project is suitable for someone with at least basic knowledge of machine learning.