Algorithmic Trading and Stocks Essential Training – Michael McDonald
Algorithmic Trading and Stocks Essential Training
By: Michael McDonald
Skill Level: Intermediate
Duration: 1h 29m
Released: March 14, 2018
Description:
Many stock market trades are now conducted with algorithms: computer programs that buy or sell stocks according to mathematical formulas. These trades are conducted at a speed and frequency that is hard for humans to replicate. Therefore, it’s important for finance professionals, and indeed everyone who invests in the stock market, to know how these algorithms work. This course shows how to develop a back-tested, rules-based trading strategy and program a simple trading algorithm of your own.
Professor Michael McDonald provides a brief primer on securities markets. He explains how data helps investors forecast performance and automate trading. Then he moves into the practical steps: coming up with algorithmic trading rules and developing and testing an algorithm. Finally, he shows how the algorithm can be applied and eventually expanded to other securities. Anyone working in financial services, or interested in investing in the stock market, will be able to use these tutorials to understand and develop simple trading algorithms of their own.
Topics include:
- Basics of trading stocks
- Algorithms and the financial industry
- How the Fed regulates algorithmic trading
- Case studies
- Quantitative rules and strategies
- Gathering data for algorithms
- Designing algorithms
- Testing algorithms
- Buying and selling with trading algorithms
Contents:
- Introduction
- 1. The Basics of Securities Markets
- 2. Investing and Securities
- 3. Building Algorithms
- 4. Using Trading Algorithms
- Conclusion
Author:
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.
Michael’s core knowledge is focused on financial markets and investment decision-making. He has helped advise firms on capital investments, valuation issues, and capital allocation to enhance business strategy. He is the author of multiple research studies addressing complex questions across the finance discipline. Michael’s work has been cited by the Wall Street Journal, Bloomberg, the CFA Institute, and many others.
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