B.Sc. Financial Mathematics (Hons)

University of Kent
Em Canterbury (Reino Unido)

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  • Bachelor's degree
  • Canterbury (Reino Unido)

The Financial Mathematics (Hons) programme from the University of Kent provides a thorough grounding in the mathematical concepts, tools and skills needed to understand financial decision making. It offers the opportunity to study financial theory and applications built on rigorous foundations within a friendly and highly successful department.

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Instalações e datas

Início Localização
01 setembro 2016
CT2 7PE, Kent, Reino Unido
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O que se aprende nesse curso?

Financial Mathematics
Financial Training
GCSE Mathematics


Course Content

The course structure below gives a flavour of the modules that will be available to you and provides details of the content of this programme. This listing is based on the current curriculum and may change year to year in response to new curriculum developments and innovation. Most programmes will require you to study a combination of compulsory and optional modules, you may also have the option to take ‘wild’ modules from other programmes offered by the University in order that you may customise your programme and explore other subject areas of interest to you or that may further enhance your employability.

Stage 1

Possible modules may include:

  • Statistics
  • Business Economics
  • Finance 1
  • Introduction to Financial Concepts
  • Calculus and Mathematical Modelling
  • Proofs and Numbers
  • Matrices and Computing
Stage 2

Possible modules may include:

  • Analysis
  • Linear Algebra
  • Probability and Inference
  • Regression
  • Corporate Finance for Financial Mathematics
  • Probability and Measure Theory
  • Economics 2
  • Portfolio Theory and Asset Pricing Models
Year in industryAll single honours Mathematics degrees (except Mathematics with Secondary Education) offer the option of spending a year working in industry between Stages 2 and 3. We can offer help and advice in finding a placement.
Stage 3

Possible modules may include:

  • Mathematics of Financial Derivatives
  • Stochastic Processes
  • Time Series Modelling and Simulation
  • Applied Stochastic Modelling and Data Analysis
  • Analysis of Variance
  • Practical Multivariate Analysis
  • Discrete Mathematics
  • Complex Analysis
  • Polynomials in Several Variables
  • Groups and Representations
  • Elements of Abstract Analysis
  • Numerical Solution of Differential Equations
  • Nonlinear Systems and Mathematical Biology
  • Games and Networks