Level: Intermediate (I)

This course will make use of powerful features of the Python language such as Pandas, NumPy and Matplotlib to introduce participants to financial statistics. Examples will be drawn from the equity, fixed income, commodities and FX markets. The focus will be on ‘stylised facts’ – the way in which real markets differ from the familiar Gaussian distribution and why this is important in many areas of finance. Delegates will access public source data using APIs and perform their own analysis.

Learning Outcomes

 
After attending this course delegates will have:

• The ability to use Python modules to clean, explore and manage data.

• The ability to build statistical models using Python.

• A deeper understanding of financial instruments and markets.

• The skills to use Python with financial data to increase their understanding of markets.

Topics Covered

• Introduction to Python Pandas as a tool for managing financial data.
• Using Python and APIs to access data.
• More advanced Pandas with time series data. Plotting using matplotlib.
• Financial instruments: stocks, futures, cash (FX), Fixed income and commodities.
• Data cleaning and preparation
• Data sources and exploratory analysis. Asset returns and the normal distribution.

• ‘Stylised’ facts of financial markets: volatility clustering, leverage effect and fat tails. Kurtosis and skew.
• Financial crises and crashes. Examples from the FX market. Alternative models.
• Government bond yield curves. Extracting data from central banks. Building a multivariate dataset with Pandas.
• Building statistical models with Python

Target Audience

Knowledge Assumed

Attendees are assumed to have a basic level of Python skills equivalent to having attended our Introduction to Python course.
 
Attendees need to come with a laptop with Python already installed. Anaconda is a good way to do this.

Steve Bell DPhil

Steve Bell is a theoretical physicist who has worked in a quantitative role in a London based hedge fund. He has also taught financial statistics at the London School of Economics and is the author of an introductory text on the subject.