Programming for FinTech
| Code | School | Level | Credits | Semesters |
| BUSI4624 | Business | 4 | 20 | Autumn UK |
- Code
- BUSI4624
- School
- Business
- Level
- 4
- Credits
- 20
- Semesters
- Autumn UK
Summary
The module covers important concepts in Python. These include:
(1) data types
(2) operators and expressions
(3) conditional and unconditional loops
(4) data structure
(5) functions
(6) exception handling
(7) file handling
Students will learn how to use Python to analyse data, design trading algorithms, back-test trading strategies, and construct portfolios. The module also covers estimation of econometric models and pricing derivatives using Monte Carlo simulations using Python.
Target Students
Available to MSc Financial Technology students and MSc Exchange students.
Classes
- One 2-hour lecture each week for 11 weeks
- One 2-hour computing each week for 11 weeks
Assessment
- 50% Coursework 1: 2,500 words
- 50% Coursework 2: 2,500 words
Assessed by end of autumn semester
Educational Aims
The module aims to provide students with knowledge of how to use Python to analyse financial data, design trading algorithms, design machine learning algorithms, estimate econometric models, and price financial derivatives.Learning Outcomes
Knowledge and understanding: On successful completion of this module, students should be able to
* Describe the fundamental programming concepts.
* Identify and describe different data types and data structure.
* Discuss functions in Python.
* Explain the Python syntax and how it can be employed to handle different types of data and files, conditional and unconditional loops, and exceptions.
* Discuss the fundamentals of statistical and econometric techniques.
Intellectual Skills: This module develops:
* Design investment portfolios and automated trading algorithms using Python.
* Evaluate portfolio risk and returns and identify risk management strategies.
* Estimate econometric models using financial and economic data.
Professional Practical Skills: This module develops:
* Apply a range of programming skills to solve complex financial problems, price financial instruments, forecast asset returns, design optimal investment portfolios and automated trading strategies, stress test investment portfolios, backtest automated trading strategies, and implement risk management strategies.
* Execute appropriate risk management strategies.
Transferable (key) Skills: This module develops:
* Manage and interpret numerical and statistical data.
* Manage independent study and demonstrate effective planning and time-management skills.
* Critically evaluate research and information from various sources.