Postgraduate taught 

Financial Technology MSc

Advances in Machine Learning in Finance ACCFIN5229

  • Academic Session: 2021-22
  • School: Adam Smith Business School
  • Credits: 10
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: No
  • Available to Erasmus Students: No

Short Description

The course provides an overview of the latest applications of Machine Learning in Finance.

Timetable

Course is delivered over 2 weeks, comprising of 14 hours of lectures and 2 hours of tutorials.

Excluded Courses

None

Co-requisites

None

Assessment

ILO being assessed

Course Aims

The overall aim of the course is to present, discuss and explain some of the latest application applications of machine learning in Finance. Initially, it will discuss algorithmic and pairs trading. Then, it will move to bootstrapping, multiple hypothesis testing and its significance in Finance. The latest applications of machine learning in variable selection and factor analysis in Finance will be presented along with their importance and how they revolutionizes research in Finance.   

Intended Learning Outcomes of Course

By the end of this course students will be able to:

 

1. Understand, explain and evaluate algorithmic and pairs trading.

2. Understand, explain and compare the Family Wise Error Rate and the False Discovery Rate in the context of Finance

3. Appraise the applications of multiple hypothesis testing in variable selection and factor analysis in Finance

4. Evaluate the importance of machine learning in Finance research and the underlying reasoning of its popularity.

Minimum Requirement for Award of Credits

Students must submit at least 100% by weight of the components of the course's summative assessment.