Python for Financial Traders
Use Python and its statistical computing libraries to analyse and visualise your financial data and to gather some actionable insights.
Our three-day course is an introduction to data science and the Python programming language, exploring many of the key libraries and tools commonly used in the financial services industry.
Aimed at finance professionals, the course builds real solutions for data analysis using Pandas, visualisation using Matplotlib and Plot.ly, and n-dimensional matrix manipulation and linear algebra using Numpy.
The course is run by instructors with experience in financial and trading systems, therefore adding value with highly relevant Labs and models.
What you will learn:
- Explore the basics of the Python programming language
- Earn the confidence to consume market data and extract features
- Conduct real-world financial analysis in Python
- Explore many of the key libraries and tools commonly used in the financial services industry
- Acquire knowledge on how to perform transformations on data
- Understand how to work with financial time series data
- Apply Python to build pricing and simple predictive models
- Visualise your data with professional looking charts and graphs
- Perform technical analysis and back-testing of models
- Use Python to consume financial data from spreadsheets
- Perform technical analysis to choose symbols between data ranges
- Use Python to build a trading strategy and to execute back-testing
Audience:
This course is of benefit to Financial Traders, business analysts, quantitative analysts, sales and marketing, financial software developers and any professional seeking to perform data analysis.
Prior knowledge of Python is not required.
Course outline:
- The basics of the Python programming language
- How to consume market data and extract relevant features
- How to perform transformations on data
- How to work with financial time series data
- How to build pricing and simple predictive models
- How to visualize your data with professional looking charts and graphs
- How to perform technical analysis and back-testing of models
Labs
This course is hands-on. There are multiple labs that will explore different aspects of financial analysis, including:
- How to consume financial data from spreadsheets
- Internet, construct a collection of portfolios and export them to a spreadsheet.
- How to produce a chart of Bollinger bands from market data.
- How to use Pandas to consume financial data and perform analysis
- Slicing into date ranges, down sampling and up sampling, interpolation
- Moving time windows and aggregation.
- How to construct professional price/volume charts.
- How to consume poorly formatted market data, perform re-indexing and transformations to provide a clean data set, apply analysis to the data and re-export to a spreadsheet.
- How to calculate the alpha and beta values from a given portfolio to show the return on investment as compared to a traditional market index and measure its volatility.
- How to use Python to create programs to consume, transform, analyse and export data.
- How to perform technical analysis to choose a set of symbols between data ranges, build a trading strategy, execute back-testing to validate the strategy and produce a report to show the best to worse cases for the symbol and the strategy.
