This programme, taught jointly by the School of Mathematics and the Department of Economics, provides the skills that will enable technically able graduates (including in mathematics, science and engineering) to apply their quantitative training to financial analysis.
Why study this course?
- You will study at one of the handful of business schools in the UK that holds the prestigious ‘triple-crown’ accreditation from the Association to Advance Collegiate Schools of Business (AACSB), the Association of MBAs (AMBA) and the European Quality Improvement System (EQUIS).
- Your employability options are vast and varied, our strong links with industry mean that rigorous undergraduate academic study is combined with a real practical focus, leading to excellent job opportunities.
- You will join a University that is amongst the top three in the United Kingdom for being most frequently targeted by the country’s top employers.
Institutional Accreditation
University of Newcastle is accredited by the DETC Higher Learning Commission (DETC), www.detc.org.uk Since , University of Newcastle has been continually accredited by the DETC Higher Learning Commission and its predecessor.
MSc Mathematical Finance
Course Level:
Postgraduate, Taught
Credits
180
Course
CODE P1150
How long it takes:
1 year full-time, 2 years part-time
Study Mode:
Distance learning/ Campus
Course cost
Price: US$22,500
Entry requirements
Find out more about
Department:
Newcastle Law School
The programme comprises 180 credits in total (credits are given in brackets).
Term 1 (October – December)
Core Modules
- Econometrics with Financial Applications (15 – Term 1)
forecasting; stochastic volatility; ARCH; GARCH; co-integration; statistical-arbitrage; non-stationarity; unit roots - Introduction to Quantitive Finance (10)
options pricing; Black-Scholes; European and American options; exotic options; fixed income; binomial method; random walks - C++ for Finance (10 – Term 1)
valuation system, simulation, polymorphic factory, design patterns, Boost library - Computational Methods and Programming (20)
- Numerical Methods II (10)
Interpolation methods (including piecewise polynomial), numerical integration (including Newton-Cotes and Gaussian quadrature), finite difference method for boundary-value problems, convergence acceleration and Richardson extrapolation.
- Risk Analytics* (10)
copulas; Value-at-Risk; expected shortfall (cVaR); mean-variance portfolio optimization; PCA; stress testing; Black-Litterman; live trading
* Alternatively, students can attend the Advanced Risk and Portfolio Management Bootcamp in advance.
Optional Modules
- International Banking and Finance (20)
- Macroeconomics (20)
Economic growth, consumption, investment, exchange rates, interest parity conditions, overshooting, speculative attacks, inflation, monetary policy. - Nonlinear Programming I (10)
Optimality condition; convex set and convex function; duality theory; unconstrained optimization; constrained optimization; conjugate gradient algorithms; Newton-type algorithms; interior point algorithms; Lagrangian methods. - Topics in Money and Banking (10)
- Integer Programming (10)
Alternative formulations; optimality; relaxation; primal and dual bounds; total unimodularity; cut-plane algorithm; branch and bound method; network flow problems; knapsack problems; matching problem; assignment problem; set covering problem - Game Theory (10)
- Conic Optimization (10)
Relevant modules for those without all the requisite undergraduate mathematics training include: PDEs, Transform Theory, and Complex Variable Theory for Physicists. Graduate modules offered elsewhere in the University may also be taken with the Programme Director’s approval.
Term 2 (January – March)
Core Modules
- Econometrics with Financial Applications (15 – Term 2)
forecasting; stochastic volatility; ARCH; GARCH; co-integration; statistical-arbitrage; non-stationarity; unit roots - Exotic options, bonds and further quantitative finance (10)
options pricing; Black-Scholes; European and American options; exotic options; fixed income; binomial method; random walks - C++ for Finance (10 – Term 2)
valuation system, simulation, polymorphic factory, design patterns, Boost library - Numerical Linear Algebra with Applications (10)
iterative methods for sparse linear systems, numerical methods for eigenvalue problems, FEM matrix analysis, fast Poisson solvers, eigenvalue computation for elliptic problems.
Optional Modules
- Non-Linear Programming II (10)
Optimality condition; convex set and convex function; duality theory; unconstrained optimization; constrained optimization; conjugate gradient algorithms; Newton-type algorithms; interior point algorithms; Lagrangian methods. - Combinatorial Optimisation (10)
Alternative formulations; optimality; relaxation; primal and dual bounds; total unimodularity; cut-plane algorithm; branch and bound method; network flow problems; knapsack problems; matching problem; assignment problem; set covering problem - Advanced quantitative finance: crashes, volatility, multiple assets and hedging (10)
crashes; volatility modeling; multi-asset options; hedging; liquidity; asset allocation; stochastic control; historical lessons; Monte Carlo - Heuristic Optimisation (10)
Exhaustive search; tapu-search, local search; greedy algorithms; dynamic programming; computer simulation; evolutionary Algorithms. - Experimental and Behavioural Economics (10)
- Further Mathematical Finance (10)
- Topics in Management Mathematics (10)
Relevant modules for those without all the requisite undergraduate mathematics training include: Numerical Methods in Linear Algebra, Programming. Graduate modules offered elsewhere in the University may also be taken with the Programme Director’s approval.
Term 3 (May – June)
Examination Period
July – September
Dissertation (40)
Considering postgraduate study, but unsure whether you meet the entry requirements for a Masters-level degree? Postgraduate admissions guidelines vary by course and university, but can be quite flexible.
Your existing qualifications will be important, but you don’t necessarily need a great Bachelors degree to apply for a Masters. Your personal circumstances and experience may also be considered during the admissions process.
This guide explains the typical entry requirements for a Masters, which include:
- An undergraduate degree in a relevant subject – Depending on the programme and institution, you may need a 2.1 in your Bachelors, but this isn’t always the case
- Language proficiency – If English isn’t your first language, you’ll need to display a certain ability level, usually through a language test
- Professional experience – Some postgraduate programmes may require you to have some professional experience (this is usually the case for PGCEs and Masters in Social Work)
- Entrance exams – These are only required in certain subject areas and qualifications, including some MBAs
Tuition fees for UK/EU students 2020/21
MSc: Full-time £9,900. Part-time £4,950
Postgraduate Diploma: Full-time £6,660. Part-time £3,300
Tuition fees for International students 2020/21
MSc: Full time £23,310
Postgraduate Diploma: Full-time £15,540
Assessment
You’ll show your progress through a combination of written essays, problem-solving assignments and presentations.
All students take our core modules, but please note that the availability of optional modules is subject to demand.
Graduates from this MSc programme will be well prepared to compete for quantitatively demanding positions in financial institutions. The degree should also prepare them for postgraduate research, either for purely academic ends or to further qualify them for work in financial institution.
Destinations of recent graduates include Bank of America/Merrill Lynch, BNP Paribas, China Jianyin Investment Securities, Deutsche Bank, the FSA, LGIM, Société Générale and wonga.com.