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Synopsis
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 reproducibility. All code and data is self-contained in a GitHub repo. The data includes...
About the Author
Chris Conlan is the founder and CEO of Conlan Scientific, a financial data science consultancy based out of Charlotte, North Carolina. He works with his team of data scientists to build machine learning solutions for banks, lenders, investors, traders, and fintech companies. Chris graduated University of Virginia's College of Arts & Sciences with a degree in statistics, where he later co-taught a data science capstone course.
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