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Python for Algorithmic Trading Cookbook

You're reading from Python for Algorithmic Trading Cookbook Recipes for designing, building, and deploying algorithmic trading strategies with Python

Product type Paperback

Published in Aug 2024

Publisher Packt

ISBN-13 9781835084700

Length 404 pages

Edition 1st Edition

Languages

Python

Tools

Zipline

Concepts

Data Analysis

Author (1):

Jason Strimpel

View More author details

Table of Contents (16) Chapters

Preface

1. Chapter 1: Acquire Free Financial Market Data with Cutting-Edge Python Libraries FREE CHAPTER

2. Chapter 2: Analyze and Transform Financial Market Data with pandas

3. Chapter 3: Visualize Financial Market Data with Matplotlib, Seaborn, and Plotly Dash

4. Chapter 4: Store Financial Market Data on Your Computer

5. Chapter 5: Build Alpha Factors for Stock Portfolios

6. Chapter 6: Vector-Based Backtesting with VectorBT

7. Chapter 7: Event-Based Backtesting Factor Portfolios with Zipline Reloaded

8. Chapter 8: Evaluate Factor Risk and Performance with Alphalens Reloaded

9. Chapter 9: Assess Backtest Risk and Performance Metrics with Pyfolio

10. Chapter 10: Set Up the Interactive Brokers Python API

11. Chapter 11: Manage Orders, Positions, and Portfolios with the IB API

12. Chapter 12: Deploy Strategies to a Live Environment

13. Chapter 13: Advanced Recipes for Market Data and Strategy Management

14. Index

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15. Other Books You May Enjoy

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Authors (1)

Jason Strimpel

Jason Strimpel

Jason Strimpel is the founder of PyQuant News and co-founder of Trade Blotter, with a career spanning over 20 years in trading, risk management, and data science. He previously traded for a Chicago-based hedge fund, served as a risk manager at JPMorgan, and managed production risk technology for an energy derivatives trading firm in London. In Singapore, Jason served as the APAC CIO for an agricultural trading firm and built the data science team for a global metals trading firm. He holds degrees in finance and economics and a Master's in quantitative finance from the Illinois Institute of Technology. His career has taken him across America, Europe, and Asia. Jason shares his expertise through the PyQuant Newsletter, social media, and teaches the course "Getting Started With Python for Quant Finance."

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