In your first year, you’ll study the same modules as students on BSc (Hons) Mathematics. As well as mathematics, you will study probability and statistics, which underlie much of modern finance such as risk analysis. Modules include calculus, linear algebra, mathematical reasoning and numerical methods. Plymouth Business School lecturers introduce you to financial accounting.
Stage 1 Mathematics Placement Preparation
The route to graduate-level employment is found easier with experience. These sessions are designed to assist students in their search for a year-long placement and in their preparation for the placement itself. Such placements are optional but strongly recommended.
Data Analytics for Business Decision Making
The module introduces the area of data analytics and the role of data in business decision making. You will explore the use of accounting, economic and financial data and common decision making/analytical frameworks in informing business decisions. You will go on to examine major themes of management decision making (i.e. processes, models and analytical methods) and basic statistical analysis in the context of supporting and informing a number of key business decisions (e.g. pricing, investment).
This module introduces the basic reasoning skills needed to develop and apply mathematical ideas. Clear logical thinking is central to the understanding of mathematics. The module explores fundamental properties of prime numbers, their random generation and use in modern cryptography.
Calculus and Analysis
This module covers key topics in calculus and analysis and prepares students for the rest of their degree. It has an emphasis on proof and rigour and introduces some multi-dimensional calculus together with the reasoning skills needed for the development of modern mathematics. Analysis is the rigorous underpinning of calculus and these key ideas are developed and applied to limits of sequences, series and functions.
Linear Algebra and Complex Numbers
This module explores the concepts and applications of vectors, matrices and complex numbers. The deep connection between algebra and geometry is explored. The techniques that are presented in this module are at the foundation of many areas of mathematics, statistics, physics, and several other applications.
Probability with Applications
An understanding of uncertainty and random phenomena is becoming increasingly important nowadays in daily life and for a variety of fields. The aim of this module in probability is to develop the concept of chance in a mathematical framework. Random variables are also introduced, with examples involving most of the common distributions and the concepts of expectation and variance of a random variable.
In Year 2, you'll study a range of modules including vector calculus, differential equations and Monte Carlo methods where random sampling is used to solve numerical problems. You'll also examine financial markets, institutions, and instruments including interest rates, exchange rates, forward rates, options, swaps and hedging with derivative securities. The second year also provides you with skills in operational research, the mathematical techniques underlying management and decision making.
Financial Institutions and Markets
This module deals with financial markets, instruments, and institutions. You will examine the bond market, the stock market and the foreign exchange market and explore investment banking and mutual funds.
Stage 2 Mathematics Placement Preparation
These sessions are designed to help students obtain a year-long placement in the third year of their programme. Students are assisted both in their search for a placement and in their preparation for the placement itself.
In this module the geometrical and dynamical concepts needed to describe higher-dimensional objects are introduced. This includes vector calculus techniques and new forms of integration such as line integration. Students also explore the relations between integration and differentiation in higher dimensional hyperspaces. This knowledge is applied to various real world problems.
Statistical Inference and Regression
The module provides a mathematical treatment of statistical inference, including confidence intervals and hypothesis testing. Methods of estimation are explored, focusing on maximum likelihood estimation. The module also demonstrates the underlying mathematical theory of the general linear model, through a variety of applications, using professional software.
Ordinary Differential Equations
The module aims to provide an introduction to different types of ordinary differential equations and the analytical and numerical methods needed to obtain their solutions. Extensive use is made of computational mathematics packages. Applications to mechanical and chemical systems are considered as well as the chaotic behaviour seen in climate models.
Mathematical Methods and Applications
Vector calculus is extended to higher dimensions and applied to a range of important scientific problems primarily from classical mechanics and cosmology. Differential and integral calculus is applied to the solution of differential equations and the orthogonal functions bases are constructed. The crucial mathematical concepts of integral transforms (Fourier and Laplace) and Fourier series are introduced.
Operational Research and Monte Carlo Methods
This module gives students the opportunity to work on open-ended case studies in operational research (OR) and Monte Carlo methods, both of which are important methods in, for example, industry and finance. It allows students to work on their own and in teams to develop specific skills in OR and programming as well as refining their presentation and communication skills. The skills in computational simulation developed in this module have many applications.
Optional placement year
An optional but highly recommended placement in Year 3 provides you with valuable paid professional experience and helps make your CV stand out. Recent placement providers include Vauxhall Motors (finance division) and reinsurance giant Swiss Re.
Mathematics and Statistics Placement
A 48-week period of professional training is spent as the third year of a sandwich programme while undertaking an approved placement with a suitable company. This provides an opportunity for the student to gain experience of how mathematics is used in a working environment, to consolidate their previous study and to prepare for the final year and employment after graduation. Recent placement providers include GSK, the Office for National Statistics, NATS (air traffic control) and VW Group.
In your final year you'll study financial institutions as well as stochastic calculus and time series both of which underlie the modelling of financial markets. You’ll choose from a range of modules including mathematical statistics and non-linear systems. Deepen your expertise with optional modules covering topics including partial differential equations, time series and optimisation techniques. You can also undertake a final year project on a topic of personal interest. Recent projects have included the Black-Scholes model and simulations of derivative pricing.
In this module, you will develop a broad understanding of equities and bonds as investments, considering their pricing and use in investment management along with that of derivatives. In addition, you will explore core concepts in finance including market efficiency, diversification, risk, portfolio building and evaluation.
Optimisation, Networks and Graphs
This module introduces the mathematics of continuous and discrete optimisation. It provides the theoretical background and practical algorithmic techniques required to model and solve a diverse range of problems.
This module introduces students to the concepts and methods of financial time series analysis and modelling and to a variety of financial applications. The module reviews the necessary univariate and multivariate time series models and inferential techniques. Model selection, forecasting and the ‘curse of dimensionality’ problem for high dimensional modelling are treated both analytically and computationally. The R programming language is widely used in this module.
Geometry and Algebra
A review of group theory leads into an exploration of plane affine, hyperbolic, and projective geometries, all from the Kleinian point of view. Then an introduction to rings and fields is given with applications in geometry emphasised. These topics are key ideas in the study of pure mathematics.
Partial Differential Equations
This module introduces partial differential equations using real-life problems. It provides a variety of analytic and numerical methods for their solution. It includes a wide range of applications including heat diffusion and the Tsunami wave.
This module provides an employment relevant tool box of statistical modelling techniques and a rigorous treatment of the underlying mathematics. The Bayesian framework for statistical inference is developed and compared with the classical approach. Important computational algorithms, including Markov Chain Monte Carlo, are described. Application-rich modelling problems are considered.
The content includes the design and analysis of clinical trials, including crossover and sequential designs and an introduction to meta-analysis. Epidemiology is studied, including case-control and cohort studies. Survival analysis is covered in detail. Computer packages are used throughout.
Professional Experience in Industry
This module provides an opportunity for students to gain experience in applying mathematics in a commercial setting by undertaking a summer placement. Students develop their skills in written and verbal communication, listening, problem solving, time management, teamwork and leadership. Recent summer placement providers include Babcock International, BMW Group, Chess Dynamics Ltd and South West Water.
Mathematical Finance in Context
This module is designed to be an alternative to the individual project. In the module students perform structured investigations on a variety of advanced topics in mathematics and statistics. Students give oral presentations and write up a journal style article on their work. Some of these articles have been published in the University of Plymouth’s Student Scientist journal.
Students who have identified a topic of particular interest have the opportunity to study it in a final year project. Students work individually and independently, with help and advice from a supervisor, on the chosen topic. The project is assessed through presentations and the preparation of a dissertation. This is a major piece of work and the project counts as two modules
Every undergraduate taught course has a detailed programme specification document describing the course aims, the course structure, the teaching and learning methods, the learning outcomes and the rules of assessment.
The following programme specification represents the latest course structure and may be subject to change:
The modules shown for this course are those currently being studied by our students, or are proposed new modules. Please note that programme structures and individual modules are subject to amendment from time to time as part of the University’s curriculum enrichment programme and in line with changes in the University’s policies and requirements.
In light of the Coronavirus (COVID-19) pandemic, the changeable nature of the situation and any updates to government guidance, we may need to make further, last minute adjustments to how we deliver our teaching and learning on some or all of our programmes, at any time during the academic year. We want to reassure you that even if we do have to adjust the way in which we teach our programmes, we will be working to maintain the quality of the student learning experience and learning outcomes at all times.