Chris Conlan

Financial Data Scientist

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  • Blog
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    • Programming with Python
    • Programming with R
    • Automated Trading
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  • Books
    • The Financial Data Playbook
    • Fast Python
    • Algorithmic Trading with Python
    • The Blender Python API
    • Automated Trading with R
  • Snippets

Algorithmic Trading with Python

Algorithmic Trading with Python

Algorithmic Trading with Python discusses modern quant trading methods in Python with a heavy focus on pandas, numpy, and scikit-learn.

After establishing an understanding of technical indicators and performance metrics, readers will walk through the process of developing a trading simulator, strategy optimizer, and financial machine learning pipeline.

This book maintains a high standard of reprocibility. All code and data is self-contained in a GitHub repo. The data includes hyper-realistic simulated price data and alternative data based on real securities.

Algorithmic Trading with Python (2020) is the spiritual successor to Automated Trading with R (2016). This book covers more content in less time than its predecessor due to advances in open-source technologies for quantitative analysis.

Where to Buy

Available at Amazon.

Latest Release: The Financial Data Playbook

The Financial Data Playbook

Available for purchase at Amazon.com.

Algorithmic Trading

Pulling All Sorts of Financial Data in Python [Updated for 2021]

Calculating Triple Barrier Labels from Advances in Financial Machine Learning

Calculating Financial Performance Metrics in Pandas

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