num_pages: 276
description: 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 LearnAnalyze financial data with PandasUse Python libraries to perform statistical reviewsReview algorithmic trading strategies Assess risk management with NumPy and StatsModelsPerform paper and Live Trading with IB Python APIWrite unit tests and deploy your trading system to the Cloud Who This Book Is ForSoftware developers data scientists or students interested in Python and the SciPy ecosystem
language: None
title: Learn Algorithmic Trading with Python: Build Automated Electronic Trading Systems Using Python
publisher: Apress