Financial Technology (FinTech)
Mathematical Sciences
Taught
MSc
Financial Technology (FinTech)
Taught
MSc
Overview
Application Timeline
Tuition
- Year 1
| Student categories | Study | |
|---|---|---|
| Full-time | Part-time | |
| England | £12,800 | N/A |
| Northern Ireland | £12,800 | N/A |
| Scotland | £12,800 | N/A |
| Wales | £12,800 | N/A |
| EU | £21,650 | N/A |
| International | £21,650 | N/A |
Requirements
Language requirements information is currently unavailable.
Modules
Financial Technology Environment
CoreBlockchain, Cryptocurrencies and Smart contracts
CoreBig Data in Finance
Core
About
Introduction
Are you interested in a career in a rapidly expanding sector? The MSc Financial Technology (FinTech) programme is designed for graduates from non-computer science backgrounds who wish to enhance their skills in the innovative field of financial technology.
Programme Objectives
This programme aims to equip students with the necessary skills to navigate the evolving landscape of financial services influenced by disruptive technologies.
Target Audience
- Graduates with a first degree in business
- Graduates with a first degree in finance
- Graduates with a first degree in mathematics
- Graduates with a first degree in economics
Key...
Subject Area Information
Financial mathematics is a specialized field that combines mathematical theories and methods with financial practice to solve problems in finance. This discipline is essential for understanding and modeling financial markets, managing financial risks, and making informed investment decisions.
1. Introduction to Financial Mathematics
2. Probability and Statistics for Finance
3. Derivatives and Risk Management
4. Fixed Income Securities
5. Portfolio Theory and Asset Pricing
6. Numerical Methods in Finance
7. Financial Econometrics
8. Advanced Topics in Financial Mathematics
- Understanding fundamental financial concepts
- Calculating present and future values
- Analyzing financial data
- Modeling uncertainty
- Valuing derivative securities
- Designing hedging strategies
- Valuing fixed income securities
- Constructing optimal portfolios
- Implementing numerical algorithms
- Analyzing financial time series data
- Understanding complex financial instruments
- Proficiency in programming languages such as Python, R, or MATLAB
Career
Graduates of financial mathematics programs can pursue a variety of careers in the finance industry, leveraging their strong foundation in mathematics, finance, and computational techniques.
Quantitative Analyst (Quant)
Developing and implementing complex financial models to support trading and risk management.
Risk Manager
Identifying and mitigating financial risks for banks, investment firms, and corporations.
Financial Engineer
Designing new financial products and strategies using advanced mathematical techniques.
Investment Analyst
Analyzing financial data to make investment recommendations.
Actuary
Assessing financial risks in the insurance and pension industries.
Data Scientist
Applying statistical and computational methods to analyze financial data and inform business decisions.
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Enhance your academic journey with the help from our experts.