MSc in Financial Risk Management Timetable and Modules

Michaelmas Term	Hilary Term	Trinity Term
Credit Risk  Market Risk Measurement & Modelling Operational Risk Financial Econometrics  Corporate Finance	30 ECTS of elective modules	Dissertation

Michaelmas Term (September to December)

• Credit Risk 
• Market Risk Measurement & Modelling
• Operational Risk
• Financial Econometrics
• Corporate Finance

Hilary Term (January to April)

30 ECTS of elective modules from list below

Electives 

• Advanced Data Analysis
• Energy Finance and Trading
• Financial Markets and Institutions
• Fintech in Banking, Insurance & Asset Management
• Mathematics of Contingent Claims
• Sustainable Finance
• Trading Psychology and Behavioural Analysis
• Treasury Management & Derivatives

Module Descriptions

Credit Risk (5 ECTS)

This course analyses credit risk management in the modern global economy – how it arises, how it is managed and the critical impact that effective and ineffective management can have on the Global financial system and hence on the Global Economy. Fundamental Credit Analysis is examined as well as market based measures and how these measures interact. The development of credit modelling both for regulatory and IFRS9 purposes is examined and the differences between the regulatory and accounting approaches to deteriorating asset quality debated. The evolving regulatory landscape is also examined in the context of mitigating the risk of future shocks. 

Having successfully completed this module, the student should be able to:

• Understand the nature of credit risk, the types of transactions in which it arises and how it is typically managed.
• Understand the critical importance of how credit risk is managed in the main international financial institutions and the principles of good governance.
• Understand measurement issues including exposure measurement, probability of default, expected loss.
• Understand how modelling techniques can be used to estimate these measures and gain a detailed insight into current modelling methods.
• Compare and contrast fundamental credit analysis and market measures such as Moody’s KMV, bond prices and Credit Default Swap prices.
• Appreciate how regulatory measures are intended to mitigate risks in the system and how they are currently being implemented in practice.
• Understand the principles of IFRS 9, how modelling approaches are developed and the key differences to regulatory models.

Market Risk Measurement & Modelling (10 ECTS)

This module provides an overview of market risk, focussing on the market risk measurement and management for financial institutions. The module intends to provide both theoretical underpinning and some understanding of practical issues which may face market risk managers at commercial or investment banks, fund managers (traditional and alternative) or pension funds. We will discuss different definitions of risk, and approaches to its measurement, quantification, and forecasting of risk.

The theoretical aspects of the course will be taught in parallel with an introductory course on financial modelling with Python. The objective of the modelling aspect of the course is develop financial modelling skills and to apply these to practical problems in market risk measurement.

Having successfully completed this module, the student should be able to:

• Understand the nature of market risk and the principal measures used to quantify this risk; price-sensitivities, Value at Risk (VaR) and Expected Shortfall.
• Understand the principles of modern portfolio theory.
• Describe the three principal approaches to the estimation of VaR; variance covariance, historic simulation, and Monte Carlo simulation.
• Describe the use of Cholesky decomposition of correlation matrices, and principal component analysis (PCA) to generate correlated random numbers for Monte Carlo VaR models.
• Understand the principal approaches to back-testing risk measures such as VaR.
• Gain familiarity with the principles of coding in Python, applying these principles to practical problems related to market risk.

Operational Risk (5 ECTS)

This module will explore the fundamentals of Operational Risk Management. It will assist participants in understanding and implementing effective tools, policies and frameworks. Using interactive sessions and real-life case studies, participants will be helped to apply the knowledge gained in the sessions to real life situations.  They will be shown how to design effective operational risk policies which are integrated with the firm’s risk culture, appetite, and tolerance.

The intention is to demonstrate how effective operational risk management can truly add value to enterprises. The current best practice frameworks will be discussed, and extensive case studies drawn from not only financial services but also organizations that operate in the “real” economy will be used.

Having successfully completed this module, the student should be able to:

• Know how to design a comprehensive operational risk framework, devise effective operational risk policies, and implement operational risk best practices.
• Gain insight into implementing and monitoring the operational risk culture, appetite, and tolerance.
• Know how to categorize operational risks effectively.
• Know how to design and employ risk and control self-assessments, key risk indicators and operational risk metrics.
• Understand the benefits associated with effective collection of external and internal operational loss event data
• Implement various measurement approaches to quantify the operational risk regulatory and economic capitals.
• Distinguish between the approaches, outputs, reports and challenges of the Scenario Analysis and Stress Testing techniques.

Financial Econometrics (5 ECTS)

The module is designed to enable students to understand a broad range of models and techniques within the field of financial econometrics. The course will explore the classical model, time series, choice models and panel data components. The module will be both applied and theoretical in nature and students will be exposed to the use of software and academic articles containing econometric output.

Lectures are the mainstay of the teaching approach. However, software such as STATA will be used in class and students will be expected to submit assessments using such software in order to gain familiarity with applying the concepts and methods covered in the lectures. Reference will be made to Journal articles to strengthen the links from theory to practice.

Useful resources such as lecture notes, data sets and revision sheets will be available on Blackboard.

Having successfully completed this module, the student should be able to:

• Reflect upon the classical model, the selection of functional forms and the violations of the classical model.
• Demonstrate the ability to generate various econometric tests across the classical model, time series models and panel data models.
• Hypothesise on the meaning of econometric output from software packages.
• Interpret econometric output as contained in Journal articles.
• Demonstrate the role of econometrics in research.

Corporate Finance (5 ECTS)

Every single business across every single industry in every single economy in the world is trying pull off the same simple but difficult trick; invest funds productively. Those businesses which can do this well, repeatedly, over time, will be successful and grow. Those businesses which cannot, will not flourish. This module will examine and study that trick from a number of different perspectives. Firstly, businesses must decide where to get money from (the capital structure decision). Then they must decide which assets to buy with that money and crucially, how much to pay for them (the capital allocation decision). Businesses need to then manage their assets to generate sufficient return to keep their capital providers happy (cost of capital and financial management). This module will also look at other concepts that are important to maximising firm or business value including corporate governance, working capital management, mergers and acquisitions and risk management.

The module will operate on a “flipped classroom” basis. There will be online lectures on Blackboard which must be viewed prior to each in-person lecture. In-person lecture time will then be used for discussion and case study work based on the online lecture. The lectures will provide the academic theory behind corporate finance concepts and tools as well as their practical application. Online lectures should be viewed before attending in-person lectures by all students and students are encouraged to take active participation in their learning experience. Students should prepare for lectures by viewing online lectures, reading lecture slides and relevant textbook chapters in advance. Lecturer will assign study groups and students are encouraged to meet in their groups to discuss the module content. These groups will also be the groups used for group assignment/presentation. Students should also use resources available in the library and would benefit from regularly reading quality financial press including the Economist, the Financial Times and Barron’s magazine. Students would also benefit from choosing an industry or company that interests them and perusing annual reports paying particular attention to the audited financial statements of these companies.

Having successfully completed this module, the student should be able to:

• Evaluate the financial health of a company and analyse its capital structure.
• Understand working capital dynamics and the working capital cycle of a firm.
• Calculate the cost of capital for a firm and use financial models that incorporate the cost of capital for decision-making.
• Understand capital budgeting techniques and capital allocation decisions.
• Understand the intersection and interactions between capital markets and the firm.
• Critique the corporate governance structure of a firm and its impact on firm value.

Advanced Data Analysis (5 ECTS)

The ability to manage and analyse data is a powerful skill and one which is a prerequisite for many jobs in economic and financial fields.  This module has been designed with two broad objectives in mind: (1) To enhance students’ state-of-the-art knowledge on advanced econometrics and application with a particular emphasis on a rapidly growing field of study – panel data analysis – which combines features of both cross-sectional and time series data within a single estimation framework. (2) To enrich students’ knowledge in terms of both theory and application on the study of panel data under alternative estimation environments and use inference to help decision-making.

Having successfully completed this module, the student should be able to:

• Demonstrate knowledge and understanding of econometric techniques used to analyse complex datasets, with a particular emphasis on panel and cross sectional data;
• Show competence in using an econometric software package;
• Undertake rich analysis of financial and economic data and interpret the statistical output;
• Evaluate model performance based on parametric, semi-parametric and non-parametric methods which would lend realistic approximations to complex financial and economic problems;
• Relate real life financial/economic data to strategic decision making.

Energy Finance and Trading (5 ECTS)

This module focuses on energy markets. It starts with an overview of the energy value chain and a presentation of the different players in the energy markets. It then moves on to discuss the valuation of companies involved in the energy sphere. The lecture on valuation discusses challenges, e.g. climate change, that energy firms are faced with and how it affects their valuation. Next, the module turns to energy derivatives. The discussion focuses on popular trading strategies, energy risk management (hedging), and recent innovations and challenges in the energy derivatives space.

Having successfully completed this module, the student should be able to:

• Explain the "energy value chain" and the role that different market participants play in the energy segment.
• Critically evaluate the methodologies used to price energy companies.
• Identify and propose solutions to the challenges faced by energy-related firms.
• Formulate trading strategies to express a view on energy markets.
• Develop risk management recommendations.

Fintech in Banking, Insurance & Asset Management (5 ECTS)

This module explores the intersection of financial technology (FinTech) with the traditional domains of banking, insurance, and asset management. Over six sessions, students will be guided through the development of a FinTech product, gaining hands-on experience in ideation, wireframing, model development, customer research, and final presentation. This practical approach ensures that students not only understand the core concepts of FinTech but can also apply them to create innovative solutions that address real-world challenges in the financial risk industry.

Having successfully completed this module, the student should be able to:

• Identify and evaluate key trends and innovations in the FinTech space, particularly within banking, insurance, and asset management.
• Design and wireframe a FinTech product, integrating user experience principles and applied finance principles.
• Develop financial models using ML and GenAI technologies to support FinTech applications.
• Conduct customer research to align FinTech products with market needs and regulatory requirements.
• Present and defend a FinTech product concept, demonstrating its viability and potential impact on the financial industry.
• Reflect critically on the challenges and opportunities presented by FinTech, considering ethical implications and future trends.

Financial Markets & Institutions (5 ECTS)

In this module we will discuss the role of a well-functioning financial system. We explore the functions of the main types of financial institutions and markets in the modern economy. We will then cover the role of national and supranational financial institutions, and their involvement in recent events in financial markets. We will look at a number of financial crises that have occurred in recent decades, their causes and impacts on the real economy. We will then examine financial regulation and the regulatory changes that have been implemented to attempt to prevent future crises.

Having successfully completed this module, the student should be able to:

• Critically appraise the role of the financial system and its importance to a well-functioning economy.
• Describe the main financial assets and the markets in which they are traded.
• Evaluate the role of the main financial institutions and the purpose they are designed to serve.
• Examine some of the financial crises that have occurred, their causes and effects.
• Describe and evaluate the regulation that has been put in place to try to prevent future crises.

Mathematics of Contingent Claims (10 ECTS)

This course aims to introduce the mathematical ideas and frameworks behind models of financial assets and apply mathematical tools used in basic derivative pricing. The module then develops the concept of stochastic processes in discrete and continuous time and describes the relevance of these systems for evaluating contingent claims. Topics covered will include arbitrage, random walks, Brownian motion, Ito calculus, and the Black-Scholes-Merton equation. The focus throughout the course is on calculations to ensure students are able to carry out computations from models they may study or develop in subsequent classes.

Having successfully completed this module, the student should be able to:

• Describe properties of probability models, stochastic variables, and processes in discrete and continuous time.
• Understand binomial, trinomial processes, and random walk processes and conduct random walk and Monte Carlo simulations.
• Define Brownian motion and Ito lemma and derive their main properties.
• Price basic instruments using the Black-Scholes-Merton model and the risk-neutral pricing theory.
• Understand the concept of Greeks and build corresponding hedging and arbitrage strategies.

Trading Psychology and Behavioural Analysis (5 ECTS)

This module will, through practical application, highlight the realities of taking decisions of risk in today’s financial markets.  Since the financial crisis and more recently the Covid-19 global pandemic, loose monetary policy has expanded asset price valuations beyond what a fundamental approach to analysis may dictate. However recent high inflationary readings have led to a tightening of global financial conditions and as such has led to increased volatility in part driven by behavioural finance and trading psychology. As candidates take and manage decisions of risk in live market prices, core behavioural theory will be explored in relation to the variability of their trading performance.

Having successfully completed this module, the student should be able to:

• Understand the different objectives and pressures on buy-side and sell-side financial institution trading operations.
• Communicate with confidence how asset values have been impacted by behavioural factors in 2024/25.
• Appreciate your own strengths and weaknesses within different roles within the industry, helping to better align a career path to your skill sets.
• Understand through practice the impact of liquidity and volatility on market makers.
• Understand the importance of relationship management in order for an investment bank to facilitate client flow.
• Understand through practice the challenges facing portfolio managers when it comes to construction and managing a multi asset portfolio through major market volatility.
• Learn how to manage risk within an environment of uncertainty.
• Build and execute their own macro + technical trading strategies in live market prices.
• Appreciate the impact of technical levels on asset prices.

Sustainable Finance (5 ECTS) 

Sustainable Finance has become a critical area of the investment markets over the past decade. The module seeks to develop core understanding the main drivers of sustainable finance, investment in sustainable finance, the changing regulatory landscape in corporate reporting in emissions, and the growth of new industries and technology in the sustainable finance area.

The module covers best practise ESG investing, putting investing sustainably at the centre of developing investment strategy, in prioritising investments which mitigate climate change, and aid the transition to Net Zero by 2050.  The module examines the most efficient pathways to meeting legally binding carbon budgets and how both investors and corporations play a vital role in the execution of strategies to meet country specific climate commitments.  It will also examine the role of impact investing, green bonds, and responsible investing in investment strategy.

Having successfully completed this module, the student should be able to:

• Understand the key principles behind sustainable and ESG investing.
• Utilise the foundations of the portfolio management process to build multi-asset portfolios as part of the overall asset allocation decision making process.
• Understand the practical challenges which both institutional and individual investors face in managing sustainable investment portfolios to provide long term stable returns to meet long term liabilities.
• Design and evaluate strategies for managing institutional and individual wealth, while incorporating key ESG principles.
• Evaluate and recommend the most suited wealth management strategy for a range of potential economic scenarios. Understand how economic conditions can impact investment returns and investment strategies.
• Clearly understand the risks in implementation and execution of a wealth management strategy, how ESG investing impacts those risks, and how those risks can be minimised.         
• Recognise the critical importance of ESG factors when developing investment portfolios, with emphasis on assessing investments which mitigate climate change, and aid the transition to Net Zero by 2050.

Treasury Management & Derivatives (5 ECTS) 

This module will explore the principles and practices of treasury management, with a focus on cash and liquidity management, financial and operational risk management and capital structure financing. Students will explore the vital role of treasury management in the organisation, learning the different structures for managing treasury and its importance in managing liquidity, financial, credit, operational, legal and regulatory risks.

Having successfully completed this module, the student should be able to:

• Understand the role of Treasury management within the broader context of corporate finance and how it operates for different types of organisations.
• Understand the principles and best practices in the development of treasury polices.
• Understand cash management including planning and optimisation along with how to develop cashflow forecasting and the management of working capital.
• Understand various types of treasury risks such as financial market, operational, legal and regulatory, credit counterparty and liquidity risks.
• Understand the theoretical foundations and practical applications of derivative instruments in financial markets.
• Understand and value several types of forwards, futures, options, swaps and other derivatives and their place in the financial markets.
• Understand how derivatives can be used to achieve various hedging strategies.
• Understand optimal capital structures, how to raise capital and deal with investors.
• Understand the rationale for a credit rating, the different agencies and the credit rating process and its determinants.
• Understand and analyse the key elements of Liquidity Risk including methods to measure and manages the liquidity risks focusing on certain sectors.

Dissertation (30 ECTS) 

The objective of the project is to allow students to demonstrate and apply the techniques and knowledge acquired from the taught courses to a problem of real-world academic or managerial concern. To complete this module, which is worth 30 ECTS credits and is compulsory, students should:

• demonstrate that they have a good knowledge of the relevant literature on their chosen topic
• identify an interesting question associated with that topic and analyse this question using the techniques and tools learned, showing that they have a good grasp of the applicability of these techniques (statistical, numerical or theoretical);
• present the results of their analysis in a clear and convincing manner, within the word limit of no more than 12,000 words;

show their ability to communicate their work to a broad audience via the creation of an executive summary which should be 1500 words or less and which should be in the form of an academic article or managerial report.