Learn Algorithmic Trading with Python: Build Automated Electronic Trading Systems Using Python

O'Garro, Jamal Sinclair



Develop and deploy an automated electronic trading system with Python and the SciPy ecosystem. This book introduces you to the tools required to gather and analyze financial data through the techniques of data munging and data visualization using Python and its popular libraries: NumPy, pandas, scikit-learn, and Matplotlib.
You will create a research environment using Jupyter Notebooks while leveraging open source back-testing software to analyze and experiment with several trading strategies. Next, you will measure the level of return and risk of a portfolio using measures such as Alpha, Beta, and the Sharpe Ratio. This will set the stage for the use of open source backtesting and scientific computing libraries such as zipline, NumPy, and scikit-learn to develop models that will help you identify, buy, and sell signals for securities in your portfolio and watch-list.

With Learn Algorithmic Trading with Python you will explore key techniques used to analyze the performance of a portfolio and trading strategies and write unit tests on Python code that will send live orders to the market.

What You'll Learn

    Analyze financial data with Pandas
  • Use Python libraries to perform statistical reviews
  • Review algorithmic trading strategies
  • Assess risk management with NumPy and StatsModels
  • Perform paper and Live Trading with IB Python API
  • Write unit tests and deploy your trading system to the Cloud

Who This Book Is For

Software developers, data scientists, or students interested in Python and the SciPy ecosystem


Jamal Sinclair O'Garro is a full-stack Python and Node.js developer with over 10 years of experience working at several top-tier bulge-bracket investment banks and asset managers including Goldman Sachs, Morgan Stanley, JPMorgan, BlackRock Financial Management, a multi-billion dollar hedge fund, and a major securities market maker. His primary focus is designing and building electronic trading software systems. He has experience developing semi-systematic trading, algorithmic trading, backtesting and data visualization programs on Wall Street.

Jamal is also heavily involved in the NYC tech scene and runs two of New York City's largest tech meetups. He has been invited to and has spoken at President Barack Obama's White House, the United Nations, and New York University. Jamal has been featured or quoted in major media outlets such as Fortune, Forbes, CNN/Money and TechCrunch. He has also taught software engineering and web development courses at the New Jersey Institute of Technology and Columbia University. In his spare time he likes to shoot photography, learn new functional programming languages, give tech talks, and teach others how to code.