MSc Artificial Intelligence in Finance

Program Overview

The MSc Artificial Intelligence in Finance program at the University of Essex combines financial theory with AI technologies to equip students with the skills necessary to transform traditional finance practices. The program emphasizes quantitative finance, computational methods, and machine learning, preparing graduates for careers in investment firms, banks, and fintech startups where they can drive innovation in areas like automated trading and fraud detection.

Program Outline

Degree Overview:

The MSc Artificial Intelligence in Finance program at the University of Essex offers a comprehensive curriculum that blends financial theory with cutting-edge AI technologies. The program aims to equip students with the skills necessary to revolutionize traditional finance practices and drive innovation in areas such as automated trading strategies and fraud detection.

Objectives:

• To provide students with a strong foundation in both finance and AI.
• To develop essential operational skills for state-of-the-art computational methods for financial modeling.
• To equip students with the ability to use financial market simulators for stress testing trading strategies and designing electronic trading platforms.
• To prepare students for roles in investment firms, banks, fintech startups, and other related fields.

Program Description:

The program covers a wide range of topics, including:

• Algorithmic trading
• Risk management
• Financial modeling
• Machine learning
• Natural language processing
• Statistical and computational methods
• Machine learning models for finance
• Modeling trading strategies and predictive services deployed by hedge funds
• Algorithmic trading groups
• Analysis of derivatives
• Risk management
The program also emphasizes the following areas:
• Quantitative finance and microeconomics
• Computational skills
• Financial econometrics
• Market microstructure theory

Outline:

Year 1

• Component 01: CORE
• CCFEA MSc Dissertation (60 CREDITS)
• Component 02: COMPULSORY
• Machine Learning for Finance (15 CREDITS)
• Component 03: COMPULSORY
• Introduction to Financial Market Analysis (15 CREDITS)
• Component 04: COMPULSORY
• Quantitative Methods in Finance and Trading (15 CREDITS)
• Component 05: COMPULSORY
• Machine Learning (15 CREDITS)
• Component 06: COMPULSORY
• Computational Market Microstructure for FinTech and the Digital Economy (20 CREDITS)
• Options from list (30 CREDITS)
• Option from list (15 CREDITS)

Module Descriptions:

• CCFEA MSc Dissertation: This dissertation is worth 60% of the program and is submitted in week 48.
The presentation is worth 10% and takes place in weeks 49/50.
• Machine Learning for Finance: This module combines theory and practice with big data cases in finance.
Modern machine learning and data mining algorithms are introduced with specific case studies on the financial industry. Students will be introduced to financial markets such as equities, bonds, interest rates, forwards, futures, and foreign exchange. Applications of calculus and statistical methods to finance are also presented.
• Quantitative Methods in Finance and Trading: This module focuses on quantitative methods in finance and economics and their application to investment, risk management, and trading.
• Machine Learning: This module explores the study and application of methods to learn algorithms automatically from sets of examples.
It covers topics such as optical character recognition, dictation software, language translators, fraud detection in financial transactions, and more. It covers topics such as auction design, market microstructure of the stock market, liquidity provision in electronic financial markets, and capital adequacy of centralized clearing platforms. The module also explores complexity economics of self-organization, network modules, and strategic proteanism.

Teaching:

• The program is taught over one year on a full-time basis.
• Taught modules are delivered in the first two terms, followed by a dissertation in the summer.
• The program is highly practical and involves both lectures and hands-on laboratory sessions.
• Students analyze and model real-world financial data.
• Lectures are given by practitioners, including senior staff from HSBC, Olsen Ltd, Royal Bank of Scotland, and the Financial Services Authority.

Assessment:

• Courses are awarded based on the results of written examinations, together with continual assessments of practical work and coursework.
• A dissertation is required for the program.
• Many dissertations have formed the basis of published research papers.
• Students have been invited to present at international conferences and renowned institutions, such as the Bank of England.

Careers:

• The program prepares students for careers as quantitative analysts, portfolio managers, and software engineers at various institutions, including:
• HSBC
• Mitsubishi UFJ Securities
• Old Mutual
• Bank of England
• The University's Employability and Careers Centre provides support with career advice, planning, work experience, internships, placements, and voluntary opportunities.

Other:

• The program is supported by the University of Essex's highly rated Department of Economics, School of Computer Science and Electronic Engineering, and Essex Business School.
• The University of Essex is ranked 6th in the UK for research power in computer science (Times Higher Education research power measure, Research Excellence Framework 2021).
• The program is taught by experts with both academic and industrial expertise in the financial and IT sectors.
• The program offers a range of postgraduate research degrees (such as a PhD) in areas of computer science and electronic engineering, and computational finance.
• The University of Essex has specialist facilities for research into areas including non-invasive brain-computer interfaces, intelligent environments, robotics, optoelectronics, video, RF and MW, printed circuit milling, and semiconductors.
• Students have access to Bloomberg virtual trading floor in the Essex Business School.
• The University of Essex is one of the largest and best-resourced computer science and electronic engineering schools in the UK.
• The University of Essex has extensive networked computer facilities and software aids, together with a wide range of test and instrumentation equipment.
• The University of Essex has six laboratories that are exclusively for computer science and electronic engineering students.
Three are open 24/7, and students have free access to the labs except when there is a scheduled practical class in progress.
• All computers run either Windows 10 or are dual boot with Linux.
• Software includes Java, Prolog, C++, Perl, Mysql, Matlab, DB2, Microsoft Office, Visual Studio, and Project.
• Students have access to CAD tools and simulators for chip design (Xilinx) and computer networks (OPNET).
• Students use Matlab to implement quantitative methods in finance and economics, and their application to investment, risk management, and trading, as well as Python to model and develop machine learning algorithms with emphasis on the financial industry.

• Home/UK fee £11,550
• International fee £22,400