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.
In most cases, we expect that graduates from the Masters will take positions in quantitative analysis (or similar) in major financial institutions, such as in the City. The programme also prepares you to pursue further studies in academia.
The programme comprises 180 credits in total (credits are given in brackets).
Term 1 (October – December)
Compulsory Modules
Econometrics with Financial Applications| (15+)
forecasting; stochastic volatility; ARCH; GARCH; co-integration; statistical-arbitrage; non-stationarity; unit roots
Introduction to quantitative finance| (10+)
options pricing; Black-Scholes; European and American options; exotic options; fixed income; binomial method; random walks
Computational Methods and Frontiers| (10+)
finite differences; finite elements; numerical solutions; partial differential equations
Risk Analytics| (10)
copulas; Value-at-Risk; expected shortfall (cVaR); mean-variance portfolio optimization; PCA; stress testing; Black-Litterman; live trading
Optional Modules
International Banking and Finance| (20)
Macroeconomics| (30)
Economic growth, consumption, investment, exchange rates, interest parity conditions, overshooting, speculative attacks, inflation, monetary policy.
Multicriteria Decision Making| (10)
Vector optimization; Pareto efficiency; efficient set; goal programming; partial and total order; invariant order; cone and dual cone.
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.
Conic optimization |(10)
Interior point algorithms; semi-definite programming; conic optimization; quadratic optimization; Semi-definite relaxation; finance and engineering applications.
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
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)
Compulsory Modules
Econometrics with Financial Applications| (+15)
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
Computational Methods and Frontiers| (+10)
finite differences; finite elements; numerical solutions; partial differential equations
Economics of Financial Markets |(20)
consumption-based CAPM; equity premium; factor models; time-varying risk; behavioural finance
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.
Research Frontiers in Management Mathematics| (10)
Semi-infinite programming; economic equilibrium problems; projection algorithms; fixed-point methods; merit functions.
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)
Students are encouraged to pursue internships while writing their dissertations
Related links
School of Mathematics website www.mat.bham.ac.uk|
Department of Economics website www.economics.bham.ac.uk|