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{ "item_title" : "Algorithmic Trading with Python", "item_author" : [" Chris Conlan "], "item_description" : "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 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.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/9/79/863/278/9798632784986_b.jpg", "price_data" : { "retail_price" : "22.99", "online_price" : "22.99", "our_price" : "22.99", "club_price" : "22.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Algorithmic Trading with Python|Chris Conlan

Algorithmic Trading with Python : Quantitative Methods and Strategy Development

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Overview

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 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.

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Details

  • ISBN-13: 9798632784986
  • ISBN-10: 9798632784986
  • Publisher: Independently Published
  • Publish Date: April 2020
  • Dimensions: 11 x 8.5 x 0.27 inches
  • Shipping Weight: 0.69 pounds
  • Page Count: 128

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