Course Outline
Introduction
Core Concepts of Algorithmic Trading for Government
- Definition of algorithmic trading
- Overview of markets and trading practices
- Analysis of textual data in financial contexts
Utilizing Python, R, and Stata for Government Applications
- Stock trading methodologies
- Bond trading strategies
- Comprehensive investment analysis
Preparing the Development Environment for Government Use
- Installation of Quandl
- Installation of quantmod
- Installation and configuration of Stata
Algorithmic Trading with Python for Government
- Data import techniques
- Utilization of Quandl for financial data
- Manipulation and analysis of financial datasets
- Creation and management of financial databases
Algorithmic Trading with R for Government
- Data import methods
- Use of quantmod for financial analysis
- Conducting regression analyses
Algorithmic Trading with Stata for Government
- Importing and cleaning financial data
- Testing trading strategies
- Performing regression analyses
Summary and Conclusion for Government
Requirements
- Proficiency with R
- Experience in Python
Audience for Government
- Business Analysts
Testimonials (4)
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
Farris Chua
Course - Data Analysis in Python using Pandas and Numpy
The pace was just right and the relaxed atmosphere made candidates feel at ease to ask questions.