Course Outline
Introduction
Core Concepts of Algorithmic Trading
- Defining algorithmic trading
- Markets and trading mechanisms
- Textual data and analysis
Python, R, and Stata
- 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
- Utilizing Quandl
- Working with financial data
- Creating databases for financial data
Algorithmic Trading with R
- Importing data
- Utilizing quantmod
- Working with regressions
Algorithmic Trading with Stata
- Importing and cleaning data
- Testing 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
The diversity of topics covered
Romaric - Vacher
Course - Business Intelligence and Data Analysis with Metabase
Machine Translated
he was well prepared - and he is very sympathetic
Oliver - Post CH AG
Course - Splunk Fundamentals
The trainer was very available to answer all te kind of question I did