Financial Data Analytics with Python
Classroom based course! Tutor support! Certificate included! 12 CPD hours!
Royal Statistical Society
Summary
- Certificate of Attendance - Free
- Tutor is available to students
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Location & dates
End date: 16/10/2024
Additional info: Runs from 9:30am to 5:00pm on both days. Lunch included
Errol Street
City of London
London
EC1Y8LX
United Kingdom
Overview
This course will be held on 15 & 16 October 2024.
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.
Certificates
Certificate of Attendance
Hard copy certificate - Included
Course media
Description
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.
Topics Covered
Day 1
- 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.
Day 2
- ‘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
Who is this course for?
The course would be of interest to Data scientists and people working in finance such as Risk analysts and investment analysts.
Requirements
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.
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