Algorithmic Trading and Finance Models with Python, R, and Stata Essential Training

Business intelligence is one of the fastest growing areas of business, especially for financial investing. This project-based course focuses on using different types of software to build models (algorithms) that can trade stocks and other financial products. Michael McDonald shows how you can use Excel, Python, R, or Stata, to set up quantitative, testable investment rules so that you can make informed trading decisions. First, he explains what algo trading is and how it works. Next, he discusses how to develop an algo trading strategy and shares tips for how to identify opportunities in various markets. Then, he goes through an in-depth exploration of how to leverage existing software tools. Michael also covers stock trading, bond trading, data analysis, regressions, and more.

Topics include:

• What is algorithmic (algo) trading?
• Textual analysis
• Qualitative and text data
• Algorithmic trading careers
• Python and Quandl
• CSVs and Python
• Financial data
• R and quantmod
• Data analysis
• Regression analysis
• Stata
• Currency data
• Strategies

About the Author

Michael McDonald is a researcher and professor of finance at Fairfield University. He has extensive programming skills in SAS, Stata, Python, R, and SQL, among other programming languages. His past work experience includes using these programming languages to analyze big data sets in finance and economics and develop trading strategies based on data mining. He has done extensive work in investment banking, at tech startups, hedge funds, and on a wide variety of consulting projects. He has a track record of authoring creative and practical course materials for a variety of subject areas across business disciplines.

Product Details

• Full Video Tutorials
• Video File Format: MP4
• Skill Level: Intermediate
• Video Duration: 2h 08m
• Instructor: Michael McDonald