Python for Finance Cookbook: Over 80 powerful recipes for effective financial data analysis, 2nd Edition

Use modern Python libraries such as pandas, NumPy, and scikit-learn and popular machine learning and deep learning methods to solve financial modeling problems

Purchase of the print or Kindle book includes a free eBook in the PDF format
Key Features

Explore unique recipes for financial data processing and analysis with Python
Apply classical and machine learning approaches to financial time series analysis
Calculate various technical analysis indicators and backtesting backtest trading strategies

Book Description

Python is one of the most popular programming languages in the financial industry, with a huge collection of accompanying libraries. In this new edition of the Python for Finance Cookbook, you will explore classical quantitative finance approaches to data modeling, such as GARCH, CAPM, factor models, as well as modern machine learning and deep learning solutions.

You will use popular Python libraries that, in a few lines of code, provide the means to quickly process, analyze, and draw conclusions from financial data. In this new edition, more emphasis was put on exploratory data analysis to help you visualize and better understand financial data. While doing so, you will also learn how to use Streamlit to create elegant, interactive web applications to present the results of technical analyses.

Using the recipes in this book, you will become proficient in financial data analysis, be it for personal or professional projects. You will also understand which potential issues to expect with such analyses and, more importantly, how to overcome them.