MSc
1 year full time
Starts September 2017

Financial Mathematics

Understand the main aspects of quantitative finance – including general finance theory, finance models and programming for graduates with a science, engineering and mathematics background.

Our course has been developed drawing on expertise from industry professionals. You cover topics such as:

  • interest-rate theory
  • arbitrage theory
  • GARCH models
  • corporate finance
  • option pricing models and numerical analysis
  • programming in C and Java
  • the use of mathematical computing software.
Our students will learn the latest mathematical techniques and technical skills to start a successful career in the financial industry.”Dr Bertram Düring
Senior Lecturer in Mathematics

Key facts

  • This course builds on Sussex’s strong foundation of interdisciplinary study – you’ll be taught by faculty from both the Department of Mathematics and the Department of Business and Management.
  • Our courses are designed to meet employer demands – you’ll gain the knowledge and skills to compete effectively in the fast-paced world of work.
  • You have a choice between practice- and research-oriented study, working with experts in their fields.

How will I study?

You’ll study core modules and options in the autumn and spring terms. In the summer term, you undertake work on your MSc dissertation.

You’ll be assessed by a combination of unseen examinations and dissertation/projects.

What will I study?

  • Module list

    Core modules

    Core modules are taken by all students on the course. They give you a solid grounding in your chosen subject and prepare you to explore the topics that interest you most.

    • Dissertation (Financial Mathematics)

      45 credits
      All Year Teaching, Year 1

      You are expected to carry out independant study and research of a designated topic, and complete a report on the subject over the summer of the year of study

    • Corporate and International Finance

      15 credits
      Autumn Teaching, Year 1

      This module covers the most important topics in corporate finance such as: capital investment decision-taking; financing andcapital structure; risk management; and portfolio theory. You will then analyse issues in international finance including: models of exchange rates; efficiency in foreign exchange markets; monetary unions; and international financial crises.

    • Financial computing with MATLAB

      15 credits
      Autumn Teaching, Year 1

      From basic skills of MATLAB you will progress to be able to handle some financial data processing abilities.

    • Financial Mathematics

      15 credits
      Autumn Teaching, Year 1

      You will study generalized cash flows, time value of money, real and money interest rates, compound interest functions, quations of value, loan repayment schemes, investment project evaluation and comparison, bonds, term structure of interest rates, some simple stochastic interest rate models and project writing.

    • Financial and Time Series Econometrics

      15 credits
      Spring Teaching, Year 1

      The primary aim of this module is for you to become familiar with a variety of applied time-series econometric techniques, enabling the confident and independent use of these techniques.

      An important emphasis of the module is to provide you with 'hands-on' experience of econometric analysis through using a variety of economic data sets.

    • Financial Portfolio Analysis

      15 credits
      Spring Teaching, Year 1

      You will study valuation, options, asset pricing models, the Black-Scholes model, Hedging and related MatLab programming. These topics form the most essential knowledge for you if you intend to start working in the financial fields. They are complex application problems. Your understanding of mathematics should be good enough to understand the modelling and reasoning skills required. The programming element of this module makes complicated computations manageable and presentable.

    • Mathematical Models in Finance and Industry

      15 credits
      Spring Teaching, Year 1

      Topics include: partial differential equations (and methods for their solution) and how they arise in real-world problems in industry and finance. For example: advection/diffusion of pollutants, pricing of financial options.

    • Topics in Financial Risk Analysis

      15 credits
      Spring Teaching, Year 1

      This module introduces you to a variety of topics in financial risk analysis that are suitable for your masters dissertation in the summer. Sample topics include (but are not limited to):

      • option pricing (eg binomial trees and Black Scholes)
      • implied volatility and stochastic volatility models
      • American / exotic options, numerical methods, simulation
      • regression and data fitting / calibration techniques
      • risk management (eg value at risk, expected shortfall, back-testing of models, stress-testing).

      Formal lectures covering the topics are supported by practical workshops using Excel and Matlab. Also, some lecture and workshop time is devoted to research techniques and guidance on how to prepare a research proposal (‘concept outline’).

    Options

    Alongside your core modules, you can choose options to broaden your horizons and tailor your course to your interests.

    • Advanced Numerical Analysis

      15 credits
      Autumn Teaching, Year 1

      This module will cover topics including:

      • Iterative methods for linear systems: Jacobi and Gauss-Seidel, conjugate gradient, GMRES and Krylov methods
      • Iterative methods for nonlinear systems: fixed point iteration, Newton's method and Inexact Newton
      • Optimisation: simplex methods, descent methods, convex optimisation and non-convenx optimisation
      • Eigenvalue problems: power method, Von Mises method, Jacobi iteration and special matrices
      • Numerical methods for ordinary differential equations: existence of solutions for ODE's, Euler's method, Lindelöf-Picard method, continuous dependence and stability of ODE's
      • Basic methods: forward and backward Euler, stability, convergence, midpoint and trapezoidal methods (order of convergence, truncation error, stability convergence, absolute stability and A-stability)
      • Runge-Kutta methods: one step methods, predictor-corrector methods, explicit RK2 and RK4 as basic examples, and general theory of RK methods such as truncation, consitency, stability and convergence 
      • Linear multistep methods: multistep methods, truncation, consistency, stability, convergence, difference equaitons, Dahlquist's barriers, Adams family and backward difference formulas
      • Boundary value problems in 1d, shooting methods, finite difference methods, convergence analysis, Galerkin methods and convergence analysis
    • Cryptography

      15 credits
      Autumn Teaching, Year 1

      You will cover the following areas: 

      • symmetric-key cryptosystems
      • hash functions and message authentication codes
      • public-key cryptosystems
      • complexity theory and one-way functions
      • primality and randomised algorithms
      • random number generation
      • elliptic curve cryptography
      • attacks on cryptosystems
      • quantum cryptography
      • cryptographic standards.
    • Functional Analysis

      15 credits
      Autumn Teaching, Year 1

      In this module, you cover:

      • Banach spaces, Banach fixed-point theorem, Baire's theorem
      • bounded linear operators and on Banach spaces, continuous linear functionals, Banach-Steinhaus uniform boundedness principle
      • open mapping and closed graph theorems, Hahn-Banach theorem
      • Hilbert spaces, orthogonal expansions, Riesz representation theorem.
    • Introduction to Mathematical Biology

      15 credits
      Autumn Teaching, Year 1

      The module will introduce you to the concepts of mathematical modelling with applications to biological, ecological and medical phenomena. The main topics will include:

      • Continuous populations models for single species;
      • Discrete population models for single species;
      • Phase plane analysis;
      • Interacting populations (continuous models);
      • Enzyme kinetics;
      • Dynamics of infectious diseases and epidemics.
    • Linear Statistical Models

      15 credits
      Autumn Teaching, Year 1

      Topics include: full-rank model (multiple and polynomial regression), estimation of parameters, analysis of variance and covariance; model checking; comparing models, model selection; transformation of response and regressor variables; models of less than full rank (experimental design), analysis of variance, hypothesis testing, contrasts; simple examples of experimental designs, introduction to factorial experiments; and use of a computer statistical package to analyse real data sets.
    • Object Oriented Programming

      15 credits
      Autumn Teaching, Year 1

      You will be introduced to object-oriented programming, and in particular to understanding, writing, modifying, debugging and assessing the design quality of simple Java applications.

      You do not need any previous programming experience to take this module, as it is suitable for absolute beginners.

    • Partial Differential Equations

      15 credits
      Autumn Teaching, Year 1

      Topics include: Second-order Partial Differential Equations: wave equation, heat equation, Laplace equation. D'Alembert's solution, separation of variables, Duhamel's principle, energy method, Maximum principle, Green's identities.

    • Probability Models

      15 credits
      Autumn Teaching, Year 1

      You cover topics including:

      • short revision of probability theory
      • expectation and conditional expectation
      • convergence of random variables, in particular laws of large numbers, moment generating functions, and central limit theorem
      • stochastic processes in discrete time in particular Markov chains, including random walk, martingales in discrete time, Doob's optional stopping theorem, and martingale convergence theorem.
    • Programming in C++

      15 credits
      Autumn Teaching, Year 1

      After a review of the basic concepts of the C++ language, you are introduced to object oriented programming in C++ and its application to scientific computing. This includes writing and using classes and templates, operator overloading, inheritance, exceptions and error handling. In addition, Eigen, a powerful library for linear algebra is introduced. The results of programs are displayed using the graphics interface dislin.

    • Topology and Advanced Analysis

      15 credits
      Autumn Teaching, Year 1

      Topics that will be covered in this module include:

      • Topological spaces
      • Base and sub-base
      • Separation axioms
      • Continuity
      • Metrisability
      • Completeness
      • Compactness and Coverings
      • Total Boundedness
      • Lebesgue numbers and Epsilon-nets
      • Sequential Compactness
      • Arzela-Ascoli Theorem
      • Montel's theorem
      • Infinite Products
      • Box and Product Topologies
      • Tychonov Theorem
      • Banach-Alaoglu theorem.
    • Advanced Partial Differential Equations

      15 credits
      Spring Teaching, Year 1

      You will be introduced to modern theory of linear and nonlinear Partial Differential Equations. Starting from the theory of Sobolev spaces and relevant concepts in linear operator theory, which provides the functional analytic framework, you will treat the linear second-order elliptic, parabolic, and hyperbolic equations (Lax-Milgram theorem, existence of weak solutions, regularity, maximum principles), e.g., the potential, diffusion, and wave equations that arise in inhomogeneous media.

      The emphasis will be on the solvability of equations with different initial/boundary conditions, as well as the general qualitative properties of their solutions. They then turn to the study of nonlinear PDE, focusing on calculus of variation.

    • Coding Theory

      15 credits
      Spring Teaching, Year 1

      Topics covered include: 

      • Introduction to error-correcting codes. The main coding theory problem. Finite fields.
      • Vector spaces over finite fields. Linear codes. Encoding and decoding with a linear code.
      • The dual code and the parity check matrix. Hamming codes. Constructions of codes.
      • Weight enumerators. Cyclic codes. MDS codes.
    • Continuum Mechanics

      15 credits
      Spring Teaching, Year 1

      Topics include: 

      • Kinematics: Eulerian and Lagrangian descriptions, velocity, acceleration, rate of change of physical quantities, material derivatives, streamlines.
      • Deformation: stress and strain tensors, Hooke's law, equilibrium equations.
      • Conservation laws for mass, momentum and energy.
      • Phase/group velocities of travelling wave solutions.
      • Models of fluid and solid mechanics.
    • Differential Geometry

      15 credits
      Spring Teaching, Year 1

      On this module, we will cover:

      • Manifolds and differentiable structures
      • Lie derivatives
      • Parallel transport
      • Riemannian metrics and affine connections
      • Curvature tensor
      • Sectional curvature
      • Scalar curvature
      • Ricci curvature
      • Bianchi identities
      • Schur's lemma
      • Complete manifolds
      • Hopf-Rinow theorem
      • Hadmard's theorem
      • Geodescis and Jacobi fields
      • Bonnet-Meyer and Synge theorems
      • Laplace-Beltrami operator
      • Heat kernels and index theorem.
    • Dynamical Systems

      15 credits
      Spring Teaching, Year 1

      • General dynamical systems: semiflow, stability and attraction, omega-limit set, global attractor
      • Ordinary Differential Equations: Linear systems, Lyapunov function, linearised systems around fixed points, two-dimensional
        systems, periodic orbit
      • Discrete systems (iterations): Linear systems, linearised systems around fixed points, chaos
    • Financial Invest & Corp Risk Analysis

      15 credits
      Spring Teaching, Year 1

      In this module, we introduce the three main risk concepts in the investment and corporate risk management field: market risk (times series), credit risk (financial rating) and operational risk (evaluation and reporting techniques), using Basel Regulations as guidelines.

      We then introduce the mathematical tools required to quantify, describe and analyse these risks quantitatively (including graphic representation, bootstrapping, calculation of transition matrices, ARCH/GARCH models, VaR, Monte-Carlo simulation)

      We also introduce some programming tools in Excel and MatLab on how to deal with these problems.

    • Finite Element Analysis

      15 credits
      Spring Teaching, Year 1

      Topics include:

      • introduction to finite-element modelling methods and software
      • preparation of the graphical interface
      • setting up a model
      • mesh generation
      • stress analysis
      • nodal analysis and dynamic modelling
      • interfacing with other packages and the use of exchangeable formats
      • checking a solution
      • debugging and validation of the modelling process.
    • Measure and Integration

      15 credits
      Spring Teaching, Year 1

      In this module, you cover:

      • countably additive measures, sigma-algebras, Borel sets, measure spaces
      • outer measures and Caratheodory's construction of measures
      • construction and properties of Lebesgue measure in Euclidean spaces
      • measurable and integrable functions, Lebesgue integration theory on measure spaces, L^p spaces and their properties
      • convergence theorems: monotone convergence, dominated convergence, Fatou's lemma
      • application of limit theorems to continuity and differentiability of integrals depending on a parameter
      • properties of finite measure spaces and probability theory.
    • Medical Statistics

      15 credits
      Spring Teaching, Year 1

      Topics include: logistic regression, fitting and interpretation. Survival times; Kaplan-Meier estimate, log-rank test, Cox proportional hazard model. Designing medical research. Clinical trials; phases I-IV, randomised double-blind controlled trial, ethical issues, sample size, early stopping. Observational studies: prospective/retrospective, longitudinal/cross-sectional. Analysis of categorical data; relative risk, odds ratio; McNemar's test, meta-analysis (Mantel-Haenszel method). Diagnostic tests; sensitivity and specificity; receiver operating characteristic. Standardised mortality rates.
    • Monte Carlo Simulations

      15 credits
      Spring Teaching, Year 1

      The module will cover topics including:

      • Introduction to R 
      • Pseudo-random number generation 
      • Generation of random variates 
      • Variance reduction 
      • Markov-chain Monte Carlo and its foundations 
      • How to analyse Monte Carlo simulations 
      • Application to physics: the Ising model 
      • Application to statistics: goodness-of-fit tests
    • Numerical Solution of Partial Differential Equations

      15 credits
      Spring Teaching, Year 1

      Topics covered include: variational formulation of boundary value problems; function spaces; abstract variational problems; Lax-Milgram Theorem; Galerkin method; finite element method; examples of finite elements; and error analysis.
    • Optimal Control of Partial Differential Equations

      15 credits
      Spring Teaching, Year 1

      You will be introduced to optimal control problems for partial differential equations. Starting from basic concepts in finite dimensions (existence, optimality conditions, adjoint, Lagrange functional and KKT system) you will study the theory of linear-quadratic elliptic optimal control problems (weak solutions, existence of optimal controls, adjoint operators, necessary optimality conditions, Langrange functional and adjoint as Langrangian multiplier) as well as basic numerical methods for your solution (gradient method, projected gradient method and active set strategy). The extension to semi-linear elliptic control problems will also be considered.

    • Perturbation theory and calculus of variations

      15 credits
      Spring Teaching, Year 1

      The aim of this module is to introduce you to a variety of techniques primarily involving ordinary differential equations, that have applications in various branches of applied mathematics. No particular application is emphasised.

      Topics covered include

      • Dimensional analysis and scaling:
      • physical quantities and their measurement;
      • dimensions;
      • change of units;
      • physical laws;
      • Buckingham Pi Theorem;
      • scaling.
      • Regular perturbation methods:
      • direct method applied to algebraic equations and initial value problems (IVP);
      • Poincar method for periodic solutions;
      • validity of approximations.
      • Singular perturbation methods:
      • finding approximate solutions to algebraic solutions;
      • finding approximate solutions to boundary value problems (BVP) including boundary layers and matching.
      • Calculus of Variations:
      • necessary conditions for a function to be an extremal of a fixed or free end point problem involving a functional of integral form;
      • isoperimetric problems.
    • Random processes

      15 credits
      Spring Teaching, Year 1

      Topics covered include:

      Rationalisation:
      After the introduction of the Poisson process, birth and death processes as well as epidemics models can be presented in full generality as applications of the pooled Poisson process. At the same time, the students will be introduced to the Kolmogorov equations and to the techniques for solving them. Renewal theory is needed to better understand queues, and, for this reason, it is discussed before queues.
      Modernisation:
      A modern introductory course on stochastic processes must include at least a section on compound renewal processes (with a focus on the compound Poisson process) as well as a chapter on the Wiener process and on Ito stochastic calculus. This is necessary given the importance this process has in several applications from finance to physics. Modernisation is achieved by including a new introductory chapter divided into three parts.
      1. Poisson processes:
        1. Density and distribution of into-event time.
        2. Pooled Poisson process.
        3. Breaking down a Poisson process.
        4. Applications of the Poisson process, eg birth-and-death processes, the Kolmogorov equations.
      1. Renewal processes
        1. The ordinary renewal process.
        2. The equilibrium renewal process.
        3. The compound renewal process.
        4. Applications of renewal processes, queues.
      1. Wiener process
        1. Definition and properties
        2. Introduction to stochastic integrals
        3. Introduction to stochastic differential equations.

Entry requirements

A lower second-class (2.2) undergraduate honours degree or above demonstrating a high mathematics content.

Applicants with a degree in mathematics, finance, economics, business, science, engineering or computing are ideally suited to this course but other subjects, combined with suitable experience, can also be considered.

English language requirements

Lower level (IELTS 6.0, with not less than 6.0 in each section)

Find out about other English language qualifications we accept.

English language support

Don’t have the English language level for your course? Find out more about our pre-sessional courses.

Additional information for international students

We welcome applications from all over the world. Find out about international qualifications suitable for our Masters courses.

Visas and immigration

Find out how to apply for a student visa


Fees and scholarships

How much does it cost?

Fees

Home: £7,700 per year

EU: £7,700 per year

Channel Islands and Isle of Man: £7,700 per year

Overseas: £17,450 per year

Note that your fees may be subject to an increase on an annual basis.

How can I fund my course?

Postgraduate Masters loans

Borrow up to £10,280 to contribute to your postgraduate study.

Find out more about Postgraduate Masters Loans

Scholarships

Our aim is to ensure that every student who wants to study with us is able to despite financial barriers, so that we continue to attract talented and unique individuals.

Chancellor's Masters Scholarship (2017)

Open to students with a 1st class from a UK university or excellent grades from an EU university and offered a F/T place on a Sussex Masters in 2017

Application deadline:

1 August 2017

Find out more about the Chancellor's Masters Scholarship

Sussex Graduate Scholarship (2017)

Open to Sussex students who graduate with a first or upper second-class degree and offered a full-time place on a Sussex Masters course in 2017

Application deadline:

1 August 2017

Find out more about the Sussex Graduate Scholarship

Sussex India Scholarships (2017)

Sussex India Scholarships are worth £3,500 and are for overseas fee paying students from India commencing Masters study in September 2017.

Application deadline:

1 August 2017

Find out more about the Sussex India Scholarships

Sussex Malaysia Scholarships (2017)

Sussex Malaysia Scholarships are worth £3,500 and are for overseas fee paying students from Malaysia commencing Masters study in September 2017.

Application deadline:

1 August 2017

Find out more about the Sussex Malaysia Scholarships

Sussex Nigeria Scholarships (2017)

Sussex Nigeria Scholarships are worth £3,500 or £5,000 and are for overseas fee paying students from Nigeria commencing a Masters in September 2017.

Application deadline:

1 August 2017

Find out more about the Sussex Nigeria Scholarships

Sussex Pakistan Scholarships (2017)

Sussex Pakistan Scholarships are worth £3,500 and are for overseas fee paying students from Pakistan commencing Masters study in September 2017.

Application deadline:

1 August 2017

Find out more about the Sussex Pakistan Scholarships

How Masters scholarships make studying more affordable

Living costs

Find out typical living costs for studying at Sussex.


Faculty

You’ll be taught by faculty from both the Department of Mathematics and the Department of Business and Management.

  • Faculty profiles

    Prof Carol Alexander
    Professor of Finance
    C.Alexander@sussex.ac.uk

    Research interests: Algebra, Applied Statistics, Decision Analysis, Evolutionary Game Theory, Exchange Trading, Finance, Financial Markets, Financial Mathematics, Financial Modelling, Game Theory, Hedge Funds, Mathematical Statistics, Mathematics, Real Options, Risk Analysis, Statistical Methodology, Statistical Modelling, Stochastic Analysis, Stochastic Processes, Volatility Analysis

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    Prof Katie Bailey
    Professor Of Management
    K.Bailey@sussex.ac.uk

    Research interests: Change Management, employee engagement, gender and employment, HRM in the public sector, Human resource management, knowledge-intensive firms, meaningful work, strategic human resource management

    View profile

    Prof Constantin Blome
    Professor Of Operations Management
    C.Blome@sussex.ac.uk

    Research interests: Manufacturing Procurement, Operations Management, Operations Strategy, Outsourcing, Procurement, Public Procurement, Risk management, Supply Chain Innovation, Supply Chain Management, Sustainability: Environmental

    View profile

    Dr Ingo Borchert
    Senior Lecturer in Economics
    I.Borchert@sussex.ac.uk

    Research interests: Brexit, Foreign direct investment, International Trade, Service sector integration, Trade in services, Trade liberalization, Trade policy

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    Dr Achilleas Boukis
    Lecturer In Marketing
    A.Boukis@sussex.ac.uk

    Research interests: Consumer branding, Innovation Management, internal branding, Service Encounter, Services Marketing

    View profile

    Dr Odul Bozkurt
    Senior Lecturer in International Human Resource Management
    O.Bozkurt@sussex.ac.uk

    Research interests: employment studies, globalization and work, Green Economy, international human resource management, Japan, repair work, retail employment, skills and employment, social class and employment, Sociology of work and organizations, UK retailing, vintage sector

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    Dr Michael Coulon
    Senior Lecturer in Finance
    M.Coulon@sussex.ac.uk

    Research interests: Commodities, Energy, Environmental policy, Finance, Financial Mathematics, Financial Modelling

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    Dr Des Doran
    Senior Lecturer in Operations & Supply Chain Management
    D.Doran@sussex.ac.uk

    Research interests: Logistics, Operations Management, Production Management, Supply Chain Management

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    Dr Bertram Duering
    Reader in Mathematics
    B.During@sussex.ac.uk

    Research interests: Applied Mathematics, Financial Mathematics, Modelling, Numerical Analysis, Optimal Control, Partial Differential Equations

    View profile

    Mr Robert Eastwood
    Tutorial Fellow
    R.K.Eastwood@sussex.ac.uk

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    Dr Benjamin Everly
    Lecturer In Organisational Behaviour
    B.Everly@sussex.ac.uk

    Research interests: Diversity management, gender and management, Intergroup relations, Race and gender equality

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    Dr Sonja Fagernas
    Senior Lecturer in Economics
    S.A.E.Fagernas@sussex.ac.uk

    Research interests: Development Economics, Economics of Education, Law and economics, public policy

    View profile

    Dr Dimitrios Gounopoulos
    Visiting Senior Research Fellow
    D.Gounopoulos@sussex.ac.uk

    Research interests: Bond Issues, Capital Structure, Commodities, Dividend Policy, Earnings Management, Educations of CEOs, Executive Compensation, Finance, Gold - Precious Metals - Industrial Metals, Initial Public Offering, International Accounting Issues, Pension Funds, Political Connections

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    Dr Bruce Hearn
    Senior Lecturer in Accounting & Finance
    B.A.Hearn@sussex.ac.uk

    Research interests: Corporate finance, corporate governance, Finance, Financial Management

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    Dr Michael Hopkins
    Senior Lecturer
    M.M.Hopkins@sussex.ac.uk

    Research interests: biotechnology, diagnostics, Financing Innovation, Healthcare, Hidden Innovation, Innovation Systems, Intellectual Property, Managing Change, pharmaceuticals, Regulation of Technology, Science and technology policy, Science And Technology Studies, Scientometrics, Technology Strategy

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    Prof Ranko Jelic
    Professor of Finance
    R.Jelic@sussex.ac.uk

    Research interests: Corporate finance, European corporate bonds, Management Buyouts, Private equity, Privatisation

    View profile

    Dr Max Jensen
    Senior Lecturer In Mathematics
    M.Jensen@sussex.ac.uk

    Research interests: Financial Mathematics, Numerical Analysis, Optimal Control, Partial Differential Equations

    View profile

    Dr Andreas Kaeck
    Reader In Finance
    A.Kaeck@sussex.ac.uk

    Research interests: Asset Pricing, Derivatives, Finance, Financial Econometrics, Risk management, Volatility Analysis

    View profile

    Dr Norifumi Kawai
    Senior Lecturer in International Business
    N.Kawai@sussex.ac.uk

    Research interests: corporate social responsibility, expatriate management, global strategy, managerial economics, strategic human resource management

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    Dr Marv Khammash
    Lecturer in Marketing
    M.Khammash@sussex.ac.uk

    Research interests: consumer activism, Consumer behaviour, Consumer health, Consumer studies, digital identities, Digital Marketing, digital media, ethical consumption, Forecast Models, ICT and Digital Technologies, Internet of things, Marketing, Marketing Research, Mobile Apps, online identity, Peer to Peer Computing, Pharmaceutical marketing, Piracy, Psychosocial methods, Social networking, technology foresight

    View profile

    Dr Andreas Kornelakis
    Visiting Senior Research Fellow
    A.Kornelakis@sussex.ac.uk

    Research interests: Banking Sector, Collective Bargaining, Comparative Studies, Employee Voice, Europe, Flexibility, Human resource management, Labour relations, Pay Determination, Pay Systems, Political economy, Telecommunications, Work

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    Dr Julie Litchfield
    Senior Lecturer in Economics
    J.A.Litchfield@sussex.ac.uk

    Research interests: Applied Economics, Conflict and violence, Development Economics, Migration, Poverty

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    Dr Michelle Luke
    Reader in Organisational Behaviour
    M.A.Luke@sussex.ac.uk

    Research interests: Organisational behaviour, Organisational psychology, Psychology, Social psychology

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    Prof Emmanuel Mamatzakis
    Professor of Finance
    E.Mamatzakis@sussex.ac.uk

    Research interests: Corporate finance, corporate governance, Finance, Financial accounting, Financial Crisis in Greece, Financial Econometrics, Financial Management, Financial Markets, Financial stability, Public finances

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    Dr Monica Masucci
    Lecturer In Strategy and Entrepreneurship
    M.Masucci@sussex.ac.uk

    Research interests: Strategy and entrepreneurship

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    Prof Andy Mckay
    Professor of Development Economics
    A.Mckay@sussex.ac.uk

    Research interests: Africa, Inequality, labour, Poverty, Structural change and economic growth, vietnam

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    Dr Piera Morlacchi
    Senior Lecturer in Entrepreneurship and Organisation Studies
    P.Morlacchi@sussex.ac.uk

    Research interests: Artificial Intelligence, Complex adaptive systems and networks, Design Creativity and Innovation, Entrepreneurship, ethnography, Health Entrepreneurship, health technologies, nonprofit organization (NPO), organization studies, public policy, Science And Technology Studies, Social Innovation and Sustainability, Sociology of Work and Organization

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    Prof Susan Newell
    Professor of Information Systems
    Sue.Newell@sussex.ac.uk

    View profile

    Dr Mike Osborne
    Senior Lecturer in Accounting & Finance
    M.J.Osborne@sussex.ac.uk

    Research interests: Capital budgeting, Corporate finance, Finance, Fixed income mathematics, Interest rates, Investment appraisal, Project analysis, Retail finance, Time value of money

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    Dr Nikolaos Papanikolaou
    Lecturer in Banking and Finance
    N.Papanikolaou@sussex.ac.uk

    Research interests: Applied Econometrics, Applied Economics, Applied microeconomics, Bank accounting, bank regulation, Corporate culture, Economic Growth, european political economy, Financial accounting, Financial Econometrics, Financial Markets, Financial stability, International Accounting Issues, Monetary Economics, Systemic risk

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    Dr Dimitra Petrakaki
    Reader in Information Systems
    D.Petrakaki@sussex.ac.uk

    Research interests: Information Systems, Information technology and organisational change, Organisational theory, Science And Technology Studies, Sociology, sociology of health, sociology of technology

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    Dr Matias Ramirez
    Senior Lecturer in Management
    Matias.Ramirez@sussex.ac.uk

    Research interests: Land Use

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    Prof Barry Reilly
    Professor of Econometrics
    B.M.Reilly@sussex.ac.uk

    Research interests: Applied Econometrics, Development Economics, Economics of Sport, Labour economics

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    Dr Maria Restuccia
    Lecturer In Marketing
    M.Restuccia@sussex.ac.uk

    Research interests: Marketing, Marketing Research, New Product Development, Policy, Arts Management & Creative Industries

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    Dr Carlos Sato
    Lecturer in Management
    C.E.Y.Sato@sussex.ac.uk

    Research interests: Major Projects Studies, Project Management, Technological Change, Technology and Innovation Management

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    Prof Enrico Scalas
    Professor Of Statistics & Probability
    E.Scalas@sussex.ac.uk

    Research interests: Econophysics, Financial Mathematics, Mathematical Statistics, Monte Carlo simulations, Probability Theory, Statistical Mechanics, Stochastic Processes

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    Dr Vikrant Shirodkar
    Senior Lecturer in International Business
    V.Shirodkar@sussex.ac.uk

    Research interests: Corporate Political Activity, corporate social responsibility, Emerging Markets, International business, lobbying

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    Dr Josh Siepel
    Senior Lecturer in Management
    J.Siepel@sussex.ac.uk

    Research interests: Design Innovation, Economics, Entrepreneurship, entrepreneurship policy, Financing Innovation, Firm growth, Innovation Creativity and Design, Innovation policy issues, skills and employment, Small Business Policy, SMEs; SME finance; SME public policy

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    Prof Chris Storey
    Professor of Marketing
    C.D.Storey@sussex.ac.uk

    Research interests: Buyer-Seller Relationships, innovation, Marketing, New Product Development, Services Marketing

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    Prof David Storey
    Professor of Enterprise
    D.J.Storey@sussex.ac.uk

    Research interests: Gamblers Ruin, SMEs; SME finance; SME public policy

    View profile

    Prof Roger Strange
    Professor of International Business
    R.N.Strange@sussex.ac.uk

    Research interests: corporate governance, Foreign direct investment, International business, MNE location, Outsourcing

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    Dr Puay Tang
    Senior Lecturer
    P.Tang@sussex.ac.uk

    Research interests: academic entrepreneurship, evaluation of publicly funded investments, research impact assessment, University-industry links

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    Dr Qi Tang
    Reader in Mathematics
    Q.Tang@sussex.ac.uk

    Research interests: Stochastic integral-differential equations

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    Dr Shqiponja Telhaj
    Senior Lecturer in Economics
    S.Telhaj@sussex.ac.uk

    Research interests: Applied microeconomics, Economics of Education, Labour economics

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    Dr Shova Thapa Karki
    Lecturer in Entrepreneurship and Sustainability
    S.Thapa-Karki@sussex.ac.uk

    Research interests: Biodiversity and Conservation, Conflict and resources, Green Management, Peri-urban sustainability, Social-ecological resilience, Sustainability: Environmental, Sustainable Entrepreneurship

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    Prof Joseph Tidd
    Professor of Science & Technology Policy Research
    J.Tidd@sussex.ac.uk

    Research interests: Industrial Innovation, Innovation Management, New Product Development

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    Prof Hans Van Der Heijden
    Professor Of Accounting
    H.Vanderheijden@sussex.ac.uk

    Research interests: Accounting, Accounting Education, Accounting Information Systems, Enterprise Systems, Information Systems, SAP, Software Development

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    Dr Jie Wen
    Lecturer in Finance
    J.Wen@sussex.ac.uk

    Research interests: Corporate finance, financial market microstructure, Financial regulation

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    Dr Mirela Xheneti
    Senior Lecturer in Entrepreneurship & Small Business
    M.Xheneti@sussex.ac.uk

    Research interests: Entrepreneurship, Entrepreneurship in the Informal Economy, Institutional Entrepreneurship, Small Business Growth, Small Business Policy, Transition Economies

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    Dr Biao Yang
    Senior Lecturer in Operations Management
    Biao.Yang@sussex.ac.uk

    Research interests: Inventory models, Operations Management, Production Management, Supply Chain Management

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    Dr Yong Yang
    Senior Lecturer in Strategy
    Yong.Yang@sussex.ac.uk

    Research interests: Foreign direct investment, global strategy, International business, MNE location, Strategic management

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    Dr Xiaoxiang Zhang
    Lecturer in Finance
    Xiaoxiang.Zhang@sussex.ac.uk

    Research interests: Asset Pricing, Corporate finance, corporate governance, Finance, Financial Management, financial market microstructure, information disclosure and efficiency, Microstructure analysis, Stock market liquidity

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Careers

Graduate destinations

100% of students from the Department of Mathematics were in work or further study six months after graduating. Recent graduates have gone on to jobs including:

  • accountant, Ernst & Young
  • graduate analyst, Invesco
  • performance analyst, Legal and General Investment Management.

(HESA EPI, Destinations of Post Graduate Leavers from Higher Education Survey 2015)

Your future career

Our graduates have found jobs in banking (investment funds and hedge funds) and financial software companies.

Working while you study

Our Careers and Employability Centre can help you find part-time work while you study. Find out more about career development and part-time work

The mix of theoretical and practical study, from monetary theory and econometrics to MATLAB and C++ programming, helped me to succeed in finding a job in the financial market.”Ryan Horne
Trading Analyst Services Department
Orc Software

Contact us