This module offers you a standard introduction of the field of corporate finance at postgraduate level. You consider the classical areas of Modigliani-Miller irrelevance, Taxes and capital structure, Trade-off theory and Pecking order theory of capital structure, before exploring the more modern areas, which are essentially based on contract theory.

Master the pricing of financial derivatives and their use for hedging financial risks. You study the basics of futures and options, analyse the Black-Scholes and binomial option pricing models, and consider various numerical techniques for pricing financial derivatives. Futures and options are then utilised in the context of hedging financial risks, and you are introduced to the concept of volatility trading and the treatment of volatility as an asset class.

Understand the process of portfolio management. You cover the main concepts such as efficient diversification, managing risk exposures, and the valuation of financial assets that are at the core of managing investment portfolios, and pay special attention to the practicalities of the implementation of these concepts.

Behavioural finance rejects crucial tenets of mainstream finance such as the Efficient Market Hypothesis (EMH) on the basis that agents are less than fully rational, and that arbitrage fails to eliminate mispricing. Instead it identifies market anomalies or regularities such as holiday effects that are at odds with the EMH. You learn to use ideas from cognitive psychology, such as overconfidence, and aspects of imperfect arbitrage to explain these.

The recent financial crisis and credit crunch have demonstrated that risk management was too narrowly defined. In this course you examine the Value at Risk (VAR) measure of financial risk developed in the 1990s, before discussing the new post-crisis Regulatory environment.

Discover the concepts and tools that are useful to asset managers who want to use fixed income securities for investing, market-making or speculating. You first study fixed income markets and instruments, before going on to explore basic concepts of bond portfolio management and investigating the quantitative tools used to value bonds and manage bonds' portfolios.

Explore the basics of the structure and environment of banking, and selected aspects of the applied economics of the modern banking firm. You study structure-conduct-performance, competition, bank efficiency, regulation, international banking and bank failures and crises.

Taught exclusively by leading industry experts, this module offers you a unique opportunity to appreciate the latest developments and issues faced by leading practitioners in the areas of quantitative finance and risk management.

Wish to conduct your own research using econometric methods? Understand econometric methods and learn to apply them to a wide variety of situations. Examine methods of linear regression and hypothesis testing. Study time series concepts of unit roots and co-integration. Explore ideas around model selection and panel data models.

What mathematical concepts are vital to understanding modern economic theory? Gain the essential mathematics skills needed to study economics at Masters-level, such as optimisation theory and the role of equilibrium. Understand how economic arguments work and improve your problem solving skills by using real-world economic problems.

How do you optimise sticky price models? What implication does this have on monetary policy? How do you apply the New Keynesian model to monetary aspects of the business cycle? Study theoretical models and empirical evidence for monetary aspects of the business cycle, and learn how to critically assess work.

What are the distinctive features of less developed economies? How do theories around child labour or inequality explain poverty? What economic policies could alleviate such problems? Understand the issues facing developing countries, examining policies theoretically and empirically. Act as a policy advisor, undertaking research on issues of development economics.

What are the concepts and methods of modern microeconomics? And how can you apply economic reasoning to this? Understand the main principles and theories of modern microeconomics, looking at topics like contract theory, equilibrium concepts in game theory, and market signalling. Learn to apply economic reasoning to these arguments.

What are the main issues facing the modern macroeconomist? How do you critically assess macroeconomic policies? Acquire the necessary tools for macroeconomic analysis, focusing on the important questions faced by macroeconomists today.

Study the concepts of risk and return in equity markets, both in the context of asset pricing, and in the management of equity portfolios. You will start by focusing on the analysis of the stylised facts of asset returns, and will then review the theoretical foundations of modern finance, covering expected utility theory and risk aversion.

How do individuals make decisions? When does classic economic theory not predict empirically observed behaviour? And how do you then use behavioural economics to reconcile your empirical findings with theoretical models? Learn about empirical and theoretical research in behavioural economics that can be used to explain individual decision making.

What happens when classic economic theory doesn’t predict empirically observed behaviour? Can behaviour economics help? Study strategic interactions and markets using behavioural economics to reconcile empirical findings with theoretical models. Gain an understanding of experimental methods used in behavioural economics.

This postgraduate module equips you with the key tools in modern data science, with a focus on machine learning (ML) and its application to Economics and Finance. The main goal of this module is to enable you to understand how machine learning tools can complement the tools of traditional econometrics and how to apply these techniques to real-world economics and finance problems. By the end of this module you will have: 1. Developed a comprehensive understanding of key concepts in modern machine learning (ML): classification, prediction, supervised and unsupervised learning 2. Demonstrated a critical understanding of the advantages and disadvantages of ML as compared to traditional econometric approaches 3. Applied ML to real-world economics and finance problems, with examples based on: i. Prediction ii. Causal Inference and Policy Evaluation

How do firms interact? What impact does this have on products that are available to you? Or the price that you pay? Understand current thinking on industrial organisation, with a focus on competition policy, regulation and business strategy. Apply analytical models of firm behaviour and strategic interaction to real-life situations.

Despite all the talk about the “death of distance”, geography matters more than ever. This course is a journey through the current economic landscape. We will try to understand the economic forces driving trends in wages, productivity and innovation across cities and regions. These are the forces that will define the geography of future jobs and will shape the economic destiny of local communities around the world.

What are the main uncertainties for international financial markets? What causes a currency crisis? How do you deal with global imbalances? Understand the analytical tools used in the field of international macroeconomics and finance. Demonstrate how such tools can be applied by examining key policy issues of interest today.

What compensation should CEOs get? How can you motivate team performance? What impact does an altruistic manager make? Study real-world issues like policymaking, finance and management using economic models from contract theory, incentive theory, and the theory of the firm.

This module equips you with the tools commonly used in economics to critically assess the efficacy of current policies and the effects of policy changes. You will put theoretical knowledge into practice, closely reviewing canonical applications of these tools in the economics literature as well as performing evaluations yourself.

Get to grips with modern microeconometrics. Examine the nature of causal and noncausal models, discuss the nature of microeconomic data structures, and review core econometric methods in the first part of this module. Then, analyse limited dependent variable models, including discrete choice and selection models, and examine program evaluation methods.

What are the main issues with panel data? And the main econometric techniques to analyse panel data? What methods can you use to evaluate spell duration data? Answer such questions with examples from labour economics, while gaining the skills to analyse a variety of research and policy problems.

What are the issues regarding different types of panel datasets? Or problems with survey methodology? Understand longitudinal data analysis by using micro-econometric techniques and critically examine survey methodology issues, like response rate and sampling frames. Apply panel data methods to study labour markets, focusing on marriage, unemployment and wages.