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.

Consider the use of modern econometric techniques in the analysis of financial time series. You cover multivariate models for stationary and non-stationary processes, such as Vector Autoregressive models, consider appropriate models for volatility, and study Markov processes and simulation methods used for financial modelling.

This course will provide you with a thorough grounding in both the theory and practice of time series econometrics with applications to topics relevant to finance. This knowledge, along with training in industry standard computing software, will be highly beneficial to students undertaking further study or wishing to work in the financial sector.

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.

Investment banks are major engines of most economies today. This module will describe the operations of primary global financial and advisory markets and the key players in the investment and corporate banking fields. The module will also provide an overview of the corporate and investment banking industry, with a focus on the main activities of full-service investment banks, including M&A advisories and the raising and underwriting of financing deals.

The module introduces students to financial markets as well as providing a detailed introduction to the quantitative methods that are a pre-requisite to other CCFEA modules. 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.

The modules introduces students to computational thinking in economics and finance by looking at different relevant models and theories, such as agent-based modelling and game theory. Students will also be introduced to various applications, such as financial forecasting, automated bargaining and mechanism design.

This module is a mix of theory and practice with big data cases in finance. Algorithmic and data science theories will be introduced and followed by a thorough introduction of data-driven algorithms for structures and unstructured data. Modern machine learning and data mining algorithms will be introduced with particular case studies on financial industry.

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 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.