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Algorithmic Trading and Stocks Essential Training

Algorithmic Trading and Stocks Essential Training

2h 23mIntermediate2022-09-15

Authors

Michael McDonald

Michael McDonald

Researcher and Professor of Finance at Fairfield University

Course details

Many stock market trades are conducted with algorithms, computer programs that buy or sell stocks according to mathematical formulas. These equity trades happen at a speed and frequency that humans cannot replicate. It's important for finance professionals and everyone who invests in the stock market to know how these algorithms work. In this course, Professor Michael McDonald shows how to develop a back-tested, rules-based trading strategy and program a simple trading algorithm of your own. Professor McDonald goes over the basics of securities markets, from stocks, bonds, and derivatives to predicting values with regressions. He explains investing and securities, including case studies and a chance to visually examine trading relationships. He shares the steps to build your own algorithms, then goes over buying and selling with an algorithm, expanding the algorithm to other securities, and analyzing scenarios in investing. Plus, Professor McDonald covers practical examples of trading with algorithms.

Skills covered

Content Management Systems (CMS)Essential TrainingWeb Development

Concepts

0. Introduction

  • 01 - Algorithmic trading

1. The Basics of Securities Markets

  • 02 - Basics of stocks
  • 03 - Basics of stock markets
  • 04 - Basics of trading stocks
  • 05 - Algorithms and the financial industry
  • 06 - Algorithms in Excel
  • 07 - Data analytics and algorithms
  • 08 - Stocks and the Fed
  • 09 - Big data in finance
  • 10 - Predicting values with regressions
  • 11 - Stocks and trading in practice

2. Investing and Securities

  • 12 - Stationarity and the VIX
  • 13 - Case study - ETF pairs trading with algorithms (OIH and XOP)
  • 14 - Case study - Dual share class pairs trading (VIA and VIA.B)
  • 15 - Common quantitative rules and strategies
  • 16 - Visually examining trading relationships

3. Building Algorithms

  • 17 - Gathering data for an algorithm
  • 18 - Designing an algorithm
  • 19 - Testing algorithm accuracy
  • 20 - Algorithm profitability and trading decisions
  • 21 - Economic data and stock correlations
  • 22 - Predicting economic variables
  • 23 - Advanced algorithms
  • 24 - Evaluating models

4. Using Trading Algorithms

  • 25 - Buying and selling with an algorithm
  • 26 - Expanding the algorithm to other securities
  • 27 - Scenario analysis in investing

5. The Evolution of Trading

  • 28 - Find trading strategies in research literature
  • 29 - Short-term vs. long-term quantitative strategies
  • 30 - Social media and drawing data from online platforms
  • 31 - Does algo trading work
  • 32 - Algo trading in practice - Who uses it
  • 33 - Algo trading services for individual investors

Conclusion

  • 34 - Next steps

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