Undergraduate Finance 2026-2027

The module considers the nature and operation of investment markets, focusing on three asset classes; shares, bonds and real estate. It looks at the characteristics of these investment options in terms of their risks and returns. The module introduces basic financial mathematics: time value of money, calculation of present values and investment rates of return. Finally, it considers the role of financial institutions and regulatory bodies in personal finance, where consumers and financial markets interact.

The main aim of this course is to develop a sound understanding of fundamental principles underlying the theory and practice of finance, thereby providing a strong basis for further study of advanced finance theory and cognate disciplines. The course introduces students to important concepts in finance: principles of assets pricing,  concept of risk and return, theory of interest rates and pricing fixed income securities, evaluation of investment project with a focus on embedded real options. It equips students with good analytical skills in order to understand the implications of financial decisions by understanding  the fundamentals that govern them.

This course introduces the statistical and mathematical tools needed to understand empirical research in Finance. Lectures provide the theoretical underpinnings of estimation and statistical inference of models commonly used in financial econometric research. Students will have the opportunity to take the methods to the data in guided computer workshops.

This course aims to build knowledge in financial analysis techniques. It will allow students to understand the key elements of financial analysis by undertaking fundamental and technical analyses. The course helps students understand and use credit analysis. It will also discuss financial distress in depth to build students’ ability to think about the implications of financial performance for investors and financial institutions.

The course combines theoretical valuation models with practical applications to help students prepare themselves for the role of financial analyst in the industry.

Multinational corporations face a range of risks in an international setting, including exchange rate, political and financing risk. The course considers the complexities of financial management in these settings. It aims to develop students understanding and ability to apply finance theory to international financial management. This course will develop student skills in the analysis of issues including globalisation and the multinational corporation; foreign exchange markets and exchange rate determination; international capital markets, debt and banking; risk management and foreign currency derivative securities.

All Accountancy and Finance students must undertake a dissertation. Students taking a joint degree may undertake the dissertation in either discipline, but not both.  It is designed to show that you are able to:

Carry out a substantial piece of research on a chosen subject without close supervision

Critically analyse and evaluate work carried out by others

Reach your own conclusions based upon your analysis and evaluation of relevant evidence, whether this is prior research only or prior research coupled with your own research.  

Write-up the results of your work in a clear, coherent and logical way.

This course aims to build upon the level 3 Corporate Finance courses to develop an advanced understanding of the ideas necessary to analyse the firm’s financing decisions. The class is based mainly on academic research articles that have influenced and directed current understanding in corporate financial and investment theory and policy.

This course aims to introduce students to what is involved in undertaking research with an emphasis on providing students with a clear fundamental base from which to complete their dissertation.

This course introduces machine learning and forecasting with applications in finance. It will explore recent trends in financial technology (FinTech) from academic and industry perspectives, which are based on data analytics and recent advances in machine learning. This course keeps the minimum of math-related content and focuses more on the application perspective. The course is based on Python, the gold-standard programming language for data analytics and machine learning.

This course aims to build upon the level 3 Empirical Methods course to develop an advanced understanding of empirical methods needed to understand and conduct research in finance. The main learning objective is to develop an advanced understanding of econometric methods for time-series data. Applications focus on examples from finance, such as evaluation of fund managers’ performance, the long-run relationship between dividends and stock prices, and time-varying asset price volatility.

This course aims to provide students with a thorough understanding of derivative contracts such as forwards, futures and options written on a variety of underlying instruments. The course will cover important areas in derivatives and will employ both a theoretical and a practical perspective.

This course aims to equip students with the knowledge, skills, and tools to navigate the rapidly evolving field of green and sustainable finance and contribute to the transition towards a more resilient, inclusive, and sustainable global financial system.

It develops an advanced understanding of how green and sustainable finance may be deployed in the real-world policy or business context, thereby contributing to the achievement of UN’s Sustainable Development Goals (SDGs).