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Hands-On Financial Trading with Python

You're reading from Hands-On Financial Trading with Python

Product type Book

Published in Apr 2021

Publisher Packt

ISBN-13 9781838982881

Pages 360 pages

Edition 1st Edition

Languages

Concepts

Authors (2):

Jiri Pik

Sourav Ghosh

View More author details

Table of Contents (15) Chapters

Preface

1. Section 1: Introduction to Algorithmic Trading

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

Summary

In this chapter, we have learned how to create matrices of any dimension in Python, how to access the matrices' elements, how to calculate basic linear algebra operations on matrices, and how to save and load matrices.

Working with NumPy matrices is a principal operation for any data analysis since vector operations are machine-optimized and thus are much faster than operations on Python lists—usually between 5 and 100 times faster. Backtesting any algorithmic strategy typically consists of processing enormous matrices, and then the speed difference can translate to hours or days of saved time.

In the next chapter, we introduce the second most important library for data analysis: Pandas, built upon NumPy. NumPy provides support for data manipulations based upon DataFrames (a DataFrame is the Python version of an Excel worksheet—that is, a two-dimensional data structure where each column has its own type).

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Authors (2)

Jiri 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 Jiri Pik

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.

See other products by Sourav Ghosh

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