Finance and Financial Technology (FinTech)
Mathematical Sciences
Taught
MSc
Overview
Application Timeline
Tuition
- Whole course
| Student categories | Study | |
|---|---|---|
| Full-time | Part-time | |
| England | £15,500 | N/A |
| Northern Ireland | £15,500 | N/A |
| Scotland | £15,500 | N/A |
| Wales | £15,500 | N/A |
| Channel Islands | £15,500 | N/A |
| Republic of Ireland | £15,500 | N/A |
| EU | £28,500 | N/A |
| International | £28,500 | N/A |
Requirements
Language requirements information is currently unavailable.
Modules
Digital Banking, Payment Systems and Financial Markets
CoreEconometric Analysis for Finance
CoreProgramming for Finance
Core
About
Specialization Areas
The MSc Finance and FinTech programme focuses on several key areas:
- Digital banking and payment systems
- Python programming
- Finance applications of machine learning algorithms
Key Learning Outcomes
Students will gain a comprehensive understanding of:
- Big data in finance and insurance
- Emerging technologies such as blockchain and cryptocurrencies
- Trading simulations involving securities, futures, options, and algorithmic trading
- FinTech regulation, data protection, and cyber security challenges
Certification Opportunities
Participants will have the chance to complete the KNIME Level 1 Certification, enhancing their...
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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