Module description
What is the module about?
This module aims to introduce the students to various aspects of computer science applied to accounting and finance. It will cover the main aspects of Python programming and algorithms used in finance.
Students will learn to write, critically assess, and correct computer programs and algorithms commonly used in accounting and finance.
It will discuss topics such as financial data extraction techniques with popular libraries, financial data analytics, financial algorithms, time series analysis, financial data processing & data visualization, input / output (IO) operations for “big data” analytics, algorithmic trading, statistical analysis including linear regression and factor models, and algorithmic portfolio management.
Who should do this module?
Students who are interested in technical Python programming / coding and “hands on” practical financial data analytics and learning important financial algorithms specifically applied to accounting and finance.
Lecture Outline
Lecture 1: Numerical Computing with NumPy
Lecture 2: Introduction to Data Analysis with Pandas
Lecture 3: Financial Data Analysis with Pandas
Lecture 4: Data Visualisation
Lecture 5: Financial Data and Pre-processingReading Week
Lecture 6: Financial Data Extraction and Time Series Analysis
Lecture 7: Input / Output Operations (Big Data Analytics and File Saving Techniques)
Lecture 8: Algorithmic Trading: Backtesting Trading Strategies
Lecture 9: Statistical Analysis: OLS regression: CAPM and Factor Models
Lecture 10: Algorithmic Portfolio Managemen
Assessment details
75% Individual Project
25% Group Project
Teaching pattern
Weekly Lecture
Weekly Tutorials
Suggested reading list
Key text or background reading
Yves Hilpisch - Python for Finance 2nd Edition (2019 O Reilly)
Eryk Lewinson - Python for Finance Cookbook (2020 Packt Publishing)
Wes Mckinney - Python for Data Analysis 2nd Edition (2017 O Reilly)