Course Outline
Introduction
Core Concepts of Algorithmic Trading
- Defining algorithmic trading
- Markets and trading
- 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
- 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 strategies
- Working with regressions
Summary and Conclusion
Requirements
- Experience with R
- Experience with Python
Audience
- Business Analysts
Testimonials (3)
Abhi has excellent knowledge of Alteryx and he explained things very clearly. He understood our goals and created bespoke demo datasets that were relevant to our organisation, which was very impressive. The training was well-structured and delivered at a good pace, with time for questions.
Samuel Taylor - Manchester Metropolitan University
Course - Alteryx for Data Analysis
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
Examples/exercices perfectly adapted to our domain
