Course Outline
Introduction
Algorithmic Trading Core Concepts
- What is algorithmic trading?
- Markets and trading
- Textual data and analysis
Python, R, and Stata
- Stock trading
- Bond trading
- Investment analysis
Preparing the Development Environment
- Installing Quandl
- Installing quantmod
- Installing and configuring Stata
Algorithmic Trading and Python
- Importing data
- Using Quandl
- Working with financial data
- Creating databases for financial data
Algorithmic Trading and R
- Importing data
- Using quantmod
- Working with regressions
Algorithmic Trading and Stata
- Importing and cleaning data
- Testing strategies
- Working with regressions
Summary and Conclusion
Requirements
- Experience with R
- Python experience
Audience
- Business Analysts
Testimonials (5)
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
The fact of having more practical exercises using more similar data to what we use in our projects (satellite images in raster format)
Matthieu - CS Group
Course - Scaling Data Analysis with Python and Dask
Very good preparation and expertise of a trainer, perfect communication in English. The course was practical (exercises + sharing examples of use cases)
Monika - Procter & Gamble Polska Sp. z o.o.
Course - Developing APIs with Python and FastAPI
Trainer develops training based on participant's pace