Best Data Science Books for Finance

Financial analysis is one of the important tasks for every business. The use of data science in finance helps solve many business problems involving stock markets, risk analysis, hypothesis testing, fraud detection, risk management, credit allocation and algorithmic trading. If you are a data scientist or learning data science and want to become a data scientist in finance, you must know about finance and how to use data science in finance. If you want to know about some of the best books that will help you learn the application of data science in finance, this article is for you. In this article, I will take you through some of the best data science books for finance.

Best Data Science Books for Finance

Machine Learning for Finance

Machine Learning for Finance is one of the best books for learning and implementing financial analysis principles using Python. It is written by Jannes Klaas who is a quantitative researcher with a background in economics and finance. Some of the topics covered in this book are:

  1. applying machine learning to structured data, natural language, text, and digital images
  2. using machine learning for fraud detection, financial trends analysis, customer segmentation and more
  3. implementation of heuristic baselines, time series, generative models and reinforcement learning
  4. debugging machine learning applications
  5. addressing bias and privacy concerns in machine learning

You should know Python and college-level math and statistics before starting with this book. You can find this book here.

Machine Learning for Algorithmic Trading

Algorithmic trading is one of the popular concepts among financial insiders. If you want to learn data science in finance specifically for trading, this book is for you. This book will guide you on using machine learning to build and back test automated trading strategies using Python. Some of the topics covered in this book are:

  1. applying machine learning to structured data, natural language, text, and digital images
  2. research and evaluation of alpha factors using statistics, Alphalens, and SHAP values
  3. implementation of machine learning to solve investment and trading problems
  4. optimize portfolio risk and performance analysis
  5. creating pairs trading strategies

You should know about machine learning and Python before getting started with this book, so I will not recommend it to beginners in data science. You can find this book here.

Summary

The use of data science in finance helps solve many business problems involving stock markets, risk analysis, hypothesis testing, fraud detection, risk management, credit allocation and algorithmic trading. I hope you liked this article on the best books to learn the application of data science in finance. Feel free to ask your valuable questions in the comments section below.

Aman Kharwal
Aman Kharwal

Coder with the ♥️ of a Writer || Data Scientist | Solopreneur | Founder

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