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Hands-On Financial Trading with Python

You're reading from Hands-On Financial Trading with Python A practical guide to using Zipline and other Python libraries for backtesting trading strategies

Product type Paperback

Published in Apr 2021

Publisher Packt

ISBN-13 9781838982881

Length 360 pages

Edition 1st Edition

Languages

Python

Tools

NumPy

Concepts

Data Analysis

Authors (2):

Sourav Ghosh

Jiri Pik

View More author details

Table of Contents (15) Chapters

Preface

1. Section 1: Introduction to Algorithmic Trading FREE CHAPTER

2. Chapter 1: Introduction to Algorithmic Trading

3. Section 2: In-Depth Look at Python Libraries for the Analysis of Financial Datasets

4. Chapter 2: Exploratory Data Analysis in Python

5. Chapter 3: High-Speed Scientific Computing Using NumPy

6. Chapter 4: Data Manipulation and Analysis with pandas

7. Chapter 5: Data Visualization Using Matplotlib

8. Chapter 6: Statistical Estimation, Inference, and Prediction

9. Section 3: Algorithmic Trading in Python

10. Chapter 7: Financial Market Data Access in Python

11. Chapter 8: Introduction to Zipline and PyFolio

12. Chapter 9: Fundamental Algorithmic Trading Strategies

13. Other Books You May Enjoy

Appendix A: How to Setup a Python Environment

Technical requirements

The Python code used in this chapter is available in the Chapter09/signals_and_strategies.ipynb notebook in the book's code repository.

The rest of the chapter is locked

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Authors (2)

Pik

Pik

Jiri Pik is an artificial intelligence architect & strategist who works with major investment banks, hedge funds, and other players. He has architected and delivered breakthrough trading, portfolio, and risk management systems, as well as decision support systems, across numerous industries. Jiri's consulting firm, Jiri Pik—RocketEdge, provides its clients with certified expertise, judgment, and execution at the speed of light.

See other products by Pik

Sourav Ghosh

Sourav Ghosh

Sourav Ghosh has worked in several proprietary, high-frequency algorithmic trading firms over the last decade. He has built and deployed extremely low latency, high-throughput automated trading systems for trading exchanges around the world, across multiple asset classes. He specializes in statistical arbitrage market-making and pairs trading strategies with the most liquid global futures contracts. He is currently the vice president at an investment bank based in São Paulo, Brazil. He holds a master's in computer science from the University of Southern California. His areas of interest include computer architecture, FinTech, probability theory and stochastic processes, statistical learning and inference methods, and natural language processing.

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