BSc Mathematics with Finance
Entry requirements
A level: AAA or AABB including Mathematics (grade A) IB: Pass, with 36 points overall with 18 at Higher Level, including 6 points from Higher Level Mathematics (Preferred Mathematics module is Analysis and Approaches, but Applications and Interpretation is also considered)
About this course
Bachelor of Science in Mathematics with Finance, a mathematics degree centred on mathematical and financial applications within the broader subject area of Mathematics and Accounting and Finance. Core topics include Programming, Signal Processing, Data Analysis, Statistics, Mathematical Modelling, Financial Analysis, Accounting, Environmental Analysis, and Artificial Intelligence & Machine Learning. The curriculum culminates in a compulsory research project. The first year covers foundational principles through Calculus I, Computational Mathematics, Introduction to Statistics, and Principles of Macroeconomics. The second year introduces core concepts in economic analysis and probability via modules such as Analysis, Intermediate Microeconomics, Statistical Inference, and Stochastic Processes. The final year focuses on specialized financial applications through Futures and Options, International Banking, and Mathematical Finance. Optional modules in the final year allow students to explore topics such as Actuarial Mathematics I, Machine Learning, and Mathematical Biology.
Modules
- Calculus I
- Calculus II
- Computational Mathematics
- Core Skills for Mathematicians I
- First Year Mathematics Workshop
- Introduction to Statistics
- Linear Algebra I
- Linear Algebra II
- Principles of Macroeconomics
- Principles of Microeconomics
- Accounting and Finance for Non-Specialists
- Analysis
- Core Skills for Mathematicians II
- Intermediate Microeconomics
- Partial Differential Equations
- Statistical Inference
- Statistical Modelling I
- Stochastic Processes
- Futures and Options
- International Banking
- Mathematical Finance
- Mathematics Project
- Actuarial Mathematics I
- Actuarial Mathematics II
- Advanced Fluid Dynamics
- Advanced Partial Differential Equations
- Algebraic Topology
- Complex Analysis
- Complex and Integral Transform Methods
- Computational Statistical Inference
- Design and Analysis of Experiments
- Further Number Theory and Cryptography
- Galois Theory
- Geometry and Data
- Hilbert Spaces
- Learning and Teaching Mathematics
- Machine Learning
- Mathematical Biology
- Mathematical Programming
- Numerical Partial Differential Equations
- Optimization
- Relativity, Black Holes and Cosmology
- Statistical Methods in Insurance
- Statistical Modelling II
- Structure and Dynamics of Networks
- Survival Models