Course Outline
Introduction
Core Concepts of Algorithmic Trading
- Understanding algorithmic trading.
- Markets and trading mechanisms.
- Textual data and analysis.
Python, R, and Stata in Trading
- Stock trading.
- Bond trading.
- Investment analysis.
Setting Up the Development Environment
- Installing Quandl.
- Installing quantmod.
- Installing and configuring Stata.
Algorithmic Trading with Python
- Importing data.
- Using Quandl.
- Working with financial data.
- Creating databases for financial data.
Algorithmic Trading with R
- Importing data.
- Using quantmod.
- Working with regressions.
Algorithmic Trading with Stata
- Importing and cleaning data.
- Testing trading strategies.
- Working with regressions.
Summary and Conclusion
Requirements
- Experience with R
- Experience with Python
Audience
- Business Analysts
Testimonials (4)
Deepthi was super attuned to my needs, she could tell when to add layers of complexity and when to hold back and take a more structured approach. Deepthi truly worked at my pace and ensured I was able to use the new functions /tools myself by first showing then letting me recreate the items myself which really helped embed the training. I could not be happier with the results of this training and with the level of expertise of Deepthi!
Deepthi - Invest Northern Ireland
Course - IBM Cognos Analytics
Used good examples, good pace of the training and covered most things
David - McGraw Hill
Course - Data Preparation with Alteryx
Examples/exercices perfectly adapted to our domain
Luc - CS Group
Course - Scaling Data Analysis with Python and Dask
The trainer was very available to answer all te kind of question I did
