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LinkedIn Learning

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

via LinkedIn Learning

Overview

Learn how to make informed trading decisions by using software tools—like Excel, Python, R, and Stata—to build models or algorithms that use quantitative, testable investment rules.

Syllabus

Introduction
  • Getting started with algorithmic trading and finance
  • What you should know
1. The Basics of Algo Trading
  • Basics of algo trading
  • Market making with algos
  • An algorithm example
  • Prop trading with algos
  • Algos in practice
  • Textual analysis and algo trading
  • Algorithmic trading with qualitative and text data
  • Careers in algorithmic trading
2. Stock Trading with Python
  • One software option: Python
  • Importing data in Python
  • Quandl and Python
  • CSVs and Python
  • Financial data and Python
  • Python and building financial databases
3. R and Bond Trading
  • One software option: R
  • Importing data with R
  • quantmod and R
  • Data analysis in R
  • Regressions in R
4. Investment Analysis and Stata
  • One software option: Stata
  • Getting currency data
  • Cleaning up data for algorithms
  • Strategies in currencies
  • Testing strategies in Stata
  • Regressions in Stata
Conclusion
  • Next steps

Taught by

Michael McDonald

Reviews

4.7 rating at LinkedIn Learning based on 627 ratings

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