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LinkedIn Learning

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

via LinkedIn Learning

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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 360 ratings

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