Finance

Core modules:

Corporate Finance

This module will aim to equip you with a comprehensive foundation of the core theoretical principles of corporate finance, along with practical insights into how these principles are applied when formulating investment analysis and financial strategy. You will be provided with a deeper understanding of key financial decisions faced by firms, with a particular focus on investment appraisal methods; risk management techniques; valuation techniques for stocks and bonds; financial statement analysis and modelling; the cost of capital and the capital structure decision. Additionally, the module will explore both the theoretical and empirical aspects of these topics, equipping you to tackle real-world financial challenges. 

15 credits

Econometric Methods

This module will develop your core econometrics skills. The first half of the module provides a grounding in key econometric techniques covering elements such as the classical linear regression model, hypothesis testing and problems of non-spherical disturbances. More advanced topics are then introduced in the second half of the module. Specifically you will focus upon topics in microeconometrics: including modelling discrete binary variables; censoring and sample selection, and then topics in macroeconometrics including: economic forecasting; stationarity; and cointegration. You will also develop a knowledge of using econometric software Stata.

15 credits

Asset Pricing and Portfolio Theory

This module will introduce you to some of the key concepts and methods in modern finance. This is an analytical module, which reflects the quantitative nature of the subject and in which each topic is developed from first principles. The module will cover the theoretical foundations of investor choice and portfolio selection based on utility theory, using these to provide a rigorous foundation for the Capital Asset Pricing Model. You will then examine some of the empirical issues that arise in the practical use of the theory.

15 credits

Behavioural Finance

This module explores the principles of Behavioural Finance, which integrates psychological insights into financial decision-making. Traditional finance models assume rationality, but Behavioural Finance recognizes the role of cognitive biases, emotions, and psychological factors in shaping market outcomes and individual decisions. The module aims to provide you with a deep understanding of how human behaviour impacts financial markets, asset pricing, corporate decision-making, and personal investing.

The following key topics will be covered: Expected Utility Theory; Asset Pricing, Market Efficiency, and Agency Relationships; Prospect Theory, Framing and Mental Accounting; Challenges to Market Efficiency; Heuristics and Biases; Overconfidence; Emotional Foundations; Experimental Behavioural Finance; Behavioural Corporate Finance; Investor Behaviour: The application of Behavioural Finance in Financial Planning and Investing. 

This module will equip you with a comprehensive understanding of how psychological factors influence financial markets and investor behaviour, helping them apply these insights to real-world financial problems.

15 credits

One from:

Applied Econometrics: Cross-sectional and Panel Data Approaches

The module provides examples and experience of applying standard microeconometric techniques to large sample surveys, with practical guidance on how to estimate and interpret results from different models.  The syllabus covers topics such as limited dependent variables, instrumental variables, panel data methods and difference in differences methods. 

15 credits

Applied Econometrics: Time Series Approaches

This module will enable you to understand recent applied literature in core journals of macroeconomics and finance, which uses time series methods, and prepare you for possible later research involving time series. You will learn to identify the empirical features of macroeconomic and financial data, and how to analyse the dynamic interaction of macroeconomic variables over time using key econometric techniques. Throughout use will be made of the Stata econometric software.

15 credits

Optional modules* - three from:

Theory of Banking

This is an advanced module that provides a comprehensive examination of contemporary banking practices and challenges. This module covers both on balance sheet and off balance sheet operations with an emphasis on identifying and managing the main banking risks. You will examine the nuances of financial crises and the workings of bank funding schemes. Important facets of contemporary bank regulation are also covered in the module.

15 credits

Derivatives, Options, and Securities

The aim of this module is to introduce you to advanced principles of asset pricing, focusing on financial derivative instruments. You will gain knowledge of how important derivatives are traded, the pricing models for derivatives, and the principles of risk management using derivatives. This is an analytical module, which reflects the quantitative nature of the subject. The module will cover both the theoretical foundations of asset pricing, and the issues that arise in the practical use of these models and their limitations.

15 credits

Econometrics of Machine Learning

This module provides a comprehensive exploration of machine learning techniques in econometrics, aiming to assess predictions and guide decision-making in practical economic and business scenarios. It covers various machine learning methods, including regression, variable selection, shrinkage techniques, classification, tree-based approaches, ensemble learning, and neural networks. The module equips participants with the skills to discern the most fitting machine learning technique for a specific problem, facilitating the ability to make predictions or informed decisions. The practical application of machine learning techniques will be demonstrated in computer lab sessions, exclusively conducted using the R programming language.

15 credits

Applied Econometrics: Cross-sectional and Panel Data Approaches

The module provides examples and experience of applying standard microeconometric techniques to large sample surveys, with practical guidance on how to estimate and interpret results from different models.  The syllabus covers topics such as limited dependent variables, instrumental variables, panel data methods and difference in differences methods. 

15 credits

Applied Econometrics: Time Series Approaches

This module will enable you to understand recent applied literature in core journals of macroeconomics and finance, which uses time series methods, and prepare you for possible later research involving time series. You will learn to identify the empirical features of macroeconomic and financial data, and how to analyse the dynamic interaction of macroeconomic variables over time using key econometric techniques. Throughout use will be made of the Stata econometric software.

15 credits

*the optional modules available each semester may change

MSc Dissertation

In this module students will complete an extended piece of written work on a topic of their choice. The dissertation will demonstrate their ability to carry out independent research and make an original contribution to the discipline.

60 credits