Algorithmic Trading and Finance Models with Python, R, and Stata Essential Training (2019)

2h 8mIntermediate2019-07-19

Authors

Michael McDonald

Researcher and Professor of Finance at Fairfield University

Course details

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.

Note: Prior to watching this course, it is recommended that you watch the course Algorithmic Trading and Stocks Essential Training.

Learning objectives
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

Skills covered

StataRStatisticsContent Management Systems (CMS)Corporate FinanceData VisualizationFinance and AccountingPythonEssential TrainingWeb DevelopmentProgramming LanguagesData ScienceBusiness Analysis and StrategyBusiness Software and ToolsOpen SourceSoftware Development

Concepts

0. Introduction

01 - Getting started with algorithmic trading and finance
02 - What you should know

1. The Basics of Algo Trading

03 - Basics of algo trading
04 - Market making with algos
05 - An algorithm example
06 - Prop trading with algos
07 - Algos in practice
08 - Textual analysis and algo trading
09 - Algorithmic trading with qualitative and text data
10 - Careers in algorithmic trading

2. Stock Trading with Python

11 - One software option - Python
12 - Importing data in Python
13 - Quandl and Python
14 - CSVs and Python
15 - Financial data and Python
16 - Python and building financial databases

3. R and Bond Trading

17 - One software option - R
18 - Importing data with R
19 - quantmod and R
20 - Data analysis in R
21 - Regressions in R

4. Investment Analysis and Stata

22 - One software option - Stata
23 - Getting currency data
24 - Cleaning up data for algorithms
25 - Strategies in currencies
26 - Testing strategies in Stata
27 - Regressions in Stata

Conclusion

28 - Next steps