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

Business intelligence is one of the fastest growing industries, particularly in financial investing. This project-based course focuses on developing models (algorithms) that can trade stocks and other financial products using various types of software. Michael McDonald demonstrates how to use Excel, Python, R, or Stata to create quantitative, testable investment rules that will allow you to make informed trading decisions. First, he defines algo trading and explains how it works. Following that, he discusses how to create an algo trading strategy and shares tips for identifying opportunities in various markets. Then he delves into how to make the best use of existing software tools. Michael also talks about stock trading, bond trading, data analysis, regressions, and other topics.

KEY FEATURE

To execute trades at precise times, algorithmic trading combines computer programming and financial markets.

Trend-following strategies, arbitrage opportunities, and index fund rebalancing are all common trading strategies.

Algorithmic trading can also be based on trading volume (volume-weighted average price) or time (time-weighted average price).

To get started with algorithmic trading, you’ll need a computer, a network connection, financial market knowledge, and coding skills.

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Key Topics

    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

    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

    R and Bond Trading

    • One software option: R
    • Importing data with R
    • quantmod and R
    • Data analysis in R
    • Regressions in R

    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

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