Learn Algorithmic Trading with Python: Build Automated Electronic Trading Systems using Python by Jamal Sinclair O'Garro

Learn Algorithmic Trading with Python: Build Automated Electronic Trading Systems using Python
Jamal Sinclair O'Garro
Page: 276
Format: pdf, ePub, mobi, fb2
ISBN: 9781484249345
Publisher: Apress
Learn Algorithmic Trading with Python: Build Automated Electronic Trading Systems using Python

Amazon books download to android Learn Algorithmic Trading with Python: Build Automated Electronic Trading Systems using Python by Jamal Sinclair O'Garro

Overview

Develop and deploy an automated electronic trading system with Python and the SciPy ecosystem. This book introduces you to the tools required to gather and analyze financial data through the techniques of data munging and data visualization using Python and its popular libraries: NumPy, pandas, scikit-learn, and Matplotlib.

You will create a research environment using Jupyter Notebooks while leveraging open source back-testing software to analyze and experiment with several trading strategies. Next, you will measure the level of return and risk of a portfolio using measures such as Alpha, Beta, and the Sharpe Ratio. This will set the stage for the use of open source backtesting and scientific computing libraries such as zipline, NumPy, and scikit-learn to develop models that will help you identify, buy, and sell signals for securities in your portfolio and watch-list.

With Learn Algorithmic Trading with Python you will explore key techniques used to analyze the performance of a portfolio and trading strategies and write unit tests on Python code that will send live orders to the market. What You'll Learn 
 Analyze financial data with Pandas
 • Use Python libraries to perform statistical reviews Review algorithmic trading strategies
 • Assess risk management with NumPy and StatsModels Perform paper and Live Trading with IB Python API
 • Write unit tests and deploy your trading system to the Cloud

Who This Book Is For

Software developers, data scientists, or students interested in Python and the SciPy ecosystem

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