You’ll study the basic concepts and standard methods of:

• mathematical notation and proof
• functions
• complex numbers and variables
• solution of equations
• resolution of inequalities
• sequences and series

This module will introduce you to the fundamental concepts of calculus, and you’ll develop some of their applications including basic ordinary differential equations.

You’ll be given an introductory treatment of vectors, matrices, geometry, and discrete maths, and you’ll be introduced to their application to real-world problems.

This module provides an introduction to finance and accounting, covering:

• the basic concepts and practicalities of corporate finance
• the principles of valuation
• financial management and business investment
• the role and purpose of company accounts and their usefulness
• security analysis
• risk and returns from investments
• personal finance.

At all times the module content will be linked with financial behaviour in the real world.

This module will present some basic ideas and techniques of statistics while introducing some essential study skills (for example basic IT, note-taking, study skills for mathematics and statistics).

This module will present some basic ideas and techniques of statistics while introducing some essential study skills, allowing you to develop and practice personal and technical skills (for example, self study, teamwork, analysing data, writing reports and making presentations).

This module will introduce you to the basic ideas of linear algebra, such as matrices and determinants, vector spaces, bases, eigenvalues and eigenvectors. You’ll study various standard methods for solving ordinary differential equations and understand their relevance and the connections with linear algebra.

This module will present the basic ideas, techniques and results for calculus of two or more variables, including partial differentiation and integration over curves, surfaces and volumes.

This module will present the basic concepts of probability theory and statistical inference, and provide you with the tools to appropriately analyse a given data set and effectively communicate the results of such analysis.

This module will introduce you to R as both a data-science environment and as a general programming language. You’ll use R to import data and perform exploratory data analysis, including data visualisation. You’ll be introduced to basic concepts in scientific modelling, including parameter exploration, and you’ll be equipped for implementing and debugging simple models in R.

This module will provide an understanding of the principles and theories relevant to the process of building investment portfolios. It covers practical applications as well as theoretical material and considers the capital asset pricing model (CAPM), market efficiency, and the estimation and evaluation of fund performance measures. It also considers issues in bond portfolio management and equity trading strategies. 

This module will demonstrate the central role linear algebra plays in applied mathematics. You’ll be provided with the tools to solve equations involving matrices. You’ll see how theoretical considerations lead to efficient computational techniques, and gain practical experience of solving linear algebra problems computationally.

This module will introduce and provide understanding of the least squares multiple regression model, general linear model, transformations and variable selection procedures, helping you to understand their importance in contemporary technology.

By the end of the module, you’ll be familiar with, and able to perform in R, multiple linear regression, generalised linear models (Poisson and Negative Binomial), generalised additive models, and penalised regression models.

This module looks at the role of the treasurer in a multinational corporation and the main task of managing risk with respect to funding requirements, foreign exchange, liquidity and banking relationships. Also included is the management of country-specific risks for multi-national firms.

This module will cover financial markets, institutions, and instruments, process of financing of a corporate entity and some specialist topics (such as convertibles, real options, mergers and acquisitions international project appraisal) that are relevant for corporate decision making.

This module will motivate the need for numerical algorithms to approximate the solution of problems that cannot be solved with pen and paper. You’ll develop skills in performing detailed analysis of the performance of numerical methods, and continue to develop your skills in the implementation of numerical algorithms using Matlab.

This module will introduce you to the concepts of univariate and multivariate probability distributions and their properties. You’ll learn about generating functions and their applications. The module will present approaches to parameter estimation, focussing on maximum likelihood estimation and properties of estimators.

This module will provide you with the fundamental principles of statistical modelling through experimental design. You’ll derive the statistical models used in the analysis of balanced experimental designs and use them in the analysis of data sets. The fundamental principles of balance, replication, blocking, interactions, nesting and repeated measures are all covered.

This module will provide an overview of the fundamental tools used in survey design and analysis. You’ll learn how to apply the principles of survey design to create and carry out surveys, and you’ll develop skills in the analysis of survey data, as well as in the interpretation and presentation of results.

This module will expose you to a number of diverse topics in stochastic processes that can be used to model real systems. In addition to theoretical analysis, appropriate computational algorithms using R are introduced.

This module will provide a broad introduction to analytical methods for solving partial differential equations. You’ll develop your understanding and technical skills in this area.

This module will provide you with experience of the skills required to undertake project work, and to communicate the findings in written and oral form using a variety of sources, such as books, journals and the internet.

The finance dissertation is a long piece of academic writing that investigates in detail a particular finance topic in which you have an interest. You will research your chosen subject by critiquing other researcher’s work, discussing relevant theories and/or methodologies, reviewing literature, collecting data and carrying out your own research on this data, usually involving statistical analysis. Once you have produced your results on your data, you will have to interpret what it all means and write it up in an acceptable academic format.

This module will provide you with a range of applied statistical techniques that can be used in professional life. You’ll learn the fundamental principles of statistical modelling through experimental design and multivariate analysis.

This module will introduce you to a range of modern statistical methods and practices used in industry, commerce and research, and you'll develop skills in their application and presentation.

You’ll learn new statistical methodology and apply it to real data from medical research studies, with an emphasis on the interpretation of the statistical results in the context of the medical problem being investigated. This skill is necessary for the application of statistics to medical data and differs from the traditional, standard interpretation of statistical textbook problems.

You’ll be introduced to ideas in mathematics and statistics that can be used to model real systems, with an emphasis on the valuation of financial derivatives.

The module places equal emphasis on deterministic analysis (calculus, differential equations) and stochastic analysis (Brownian motion, birth and death processes). In both cases, in addition to theoretical analysis, appropriate computational algorithms are introduced.

The first half of the module introduces general modelling and simulation tools, and the second half focuses on the specific application of valuing financial derivatives, including the celebrated Black-Scholes theory.

You’ll be introduced to ideas in mathematics and statistics that can be used to model real systems, with an emphasis on the valuation of financial derivatives.

The module places equal emphasis on deterministic analysis (calculus, differential equations) and stochastic analysis (Brownian motion, birth and death processes). In both cases, in addition to theoretical analysis, appropriate computational algorithms are introduced.

The first half of the module introduces general modelling and simulation tools, and the second half focuses on the specific application of valuing financial derivatives, including the celebrated Black-Scholes theory.

This module will present you with the basic theory and practice of finite element methods and polynomial and piecewise polynomial approximation theory.

This module will teach the application of mathematical models to a variety of general problems in biology, medicine, and ecology, with many applications drawn from marine population modelling.

You’ll see the application of ordinary differential equations to simple biological and medical problems, the use of mathematical modelling in biochemical reactions, and the application of partial differential equations in describing spatial processes such as cancer growth and pattern formation in embryonic development.

The marine population modelling applications will also introduce you to the use of difference models to represent population processes through applications to fisheries, and the use of coupled ODE system to describe ecosystems.

This module will demonstrate the central role network theory plays in mathematical modelling. You’ll see the intimate connection between linear algebra and graph theory, and use this connection to develop a sound theoretical understanding of network theory. You’ll apply the theory as a tool for revealing structure in networks, and apply the algorithms on a network using computer codes.

During this modules you will look at:

• financial versus non-financial reporting
• theoretical basis for sustainability disclosure
• determinants of sustainability reporting
• capital market effects of sustainability reporting
• real effects of sustainability reporting

This module explores the stochastic discount factor approach to asset pricing. The stochastic discount factor approach provides a general framework for evaluating issues in asset pricing. The aim of the module is to examine a number of theoretical and empirical issues in asset pricing.

This module will cover theories of capital structure, sources of capital (debt and equity), and corporate payout policy at an advanced level. The starting point for this module will be Modigliani-Miller assumptions introduced in Business Finance, and course material will highlight how the relaxation of these assumptions leads to formal models on corporate financing behaviour under imperfect capital markets. The emphasis will be upon the ideas necessary to analyse the firm’s financing decisions. It discusses financial structure and the alternative mechanisms for distributing corporate wealth to shareholders.

This module covers the main topics in the corporate investment and restructuring literature. It's primarily connected with corporate investment, otherwise referred to as real investment. It examines in more detail the theoretical foundations of the principles of optimal investment behaviour, restructuring and the strategic investment positions adopted by firms in practice. It builds significantly on the mergers and acquisitions theories and evidence and also examines the interface between investment and the financing decisions.

This module aims to develop a deep understanding of the main issues in the theory and practice of corporate investment and restructuring policies, and to develop students' initiative and ability to research the relevant literature. It'll emphasise the role of key concepts in finance in explaining and understanding observed corporate investment and restructuring policies, whilst also highlighting their limitations in this respect. This module is based mainly on academic articles that have influenced and directed the current level of understanding of Corporate Investment Policy. 

This module examines the problems associated with specifying financial models in forms which are amenable to estimation and testing with the available data. Consideration is given to the nature of financial data, the methods by which it's compiled and the problems it may present for applied financial analyst. You will be taught techniques of estimation, together with the methods for solving financial model problems. One coursework includes practical experience of applying the techniques to financial data using the econometric software PcGive.

The first aim of this module is to train you in the financial quantitative techniques used for the estimation and testing of financial models. The second aim is to build on and extend aspects of the models covered in other finance modules in order to provide you with skills required to evaluate advanced applied financial research. Therefore, it is assumed that students taking this module are familiar with basic statistics and simple least-squares methods of estimation.

This module builds on your knowledge of finance and your understanding of finance theory developed through the core modules in years 1 to 3. It will introduce you to behavioural finance and provide you with an understanding of the main flaws of traditional finance theory from a behavioural finance viewpoint. This module will allow you to develop the ability to discuss issues arising from violations of the rationality assumption and to enable you to evaluate new theoretical models based on research in psychology.

This module will allow you to appreciate the role of new developments in finance and their possible implications for established views of financial markets. It will provide you with an understanding of the main ideas of behavioural finance. A particular emphasis is placed on understanding the roles of non-rational actions and the development of new financial models that incorporate these. You will engage with up-to-date research and develop a critical view of existing and new finance theories and models.

This module considers financial issues associated with the operation of a firm in the international environment. It will focus on complications that make corporate financial decision harder for internationally oriented firms than domestic firms, like exchange rates and political risk.

Specifically, it will focus on the following issues:

• exchange rate theories and implications for the multinational company
• management of corporate exchange rates exposure
• the evaluation and incorporation of political risk into project evaluation
• the array of corporate financing possibilities in a global market
• the basic issues in international investment analysis, like capital budgeting and cost of capital determination for foreign projects
• methods for evaluating the performance of foreign operations

While this module presents theoretical points of view on the various issues, it uses both empirical academic evidence and discussion of firms' real-world activities to prepare you for careers dealing with financial issues of international corporate operations both at the banking and corporate level. It studies corporate financial decisions in an international setting.

This module covers advanced material in derivatives pricing. We will cover stochastic calculus and its implication in finance. In addition, numerical methods, such as Monte Carlo simulation, the Binomial tree model, and finite difference methods, will be introduced to price basic options. Finally, this course explores portfolio risk management and real option pricing framework. By the end of this course, you will have a good understanding of how derivative contracts work, how they are used and how they are priced. Students will learn how traditional option pricing framework could be used to analyse real investment projects.