Course Outline
Introduction
Core Concepts of Algorithmic Trading
- Defining algorithmic trading
- Understanding markets and trading mechanisms
- Analyzing textual data
Utilizing Python, R, and Stata
- Stock trading applications
- Bond trading applications
- Investment analysis techniques
Setting Up the Development Environment
- Installing Quandl
- Installing quantmod
- Installing and configuring Stata
Algorithmic Trading with Python
- Importing data
- Leveraging Quandl
- Working with financial data
- Creating databases for financial data
Algorithmic Trading with R
- Importing data
- Leveraging quantmod
- Conducting regression analysis
Algorithmic Trading with Stata
- Importing and cleaning data
- Testing trading strategies
- Conducting regression analysis
Summary and Conclusion
Requirements
- Prior experience with R
- Proficiency in 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
