Python for Finance Cookbook - Second Edition
Python for Finance Cookbook - Second Edition
Over 80 powerful recipes for effective financial data analysis
About the Book
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.
About the Author
Table of Contents
- Acquiring Financial Data
- Data Preprocessing
- Visualizing Financial Time Series
- Exploring Financial Time Series Data
- Technical Analysis and Building Interactive Dashboards
- Time Series Analysis and Forecasting
- Machine Learning-Based Approaches to Time Series Forecasting
- Multi-Factor Models
- Modelling Volatility with GARCH Class Models
- Monte Carlo Simulations in Finance
- Asset Allocation
- Backtesting Trading Strategies
- Applied Machine Learning: Identifying Credit Default
- Advanced Concepts for Machine Learning Projects
- Deep Learning in Finance
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