Book Image

Python for Finance - Second Edition

By : Yuxing Yan
5 (1)
Book Image

Python for Finance - Second Edition

5 (1)
By: Yuxing Yan

Overview of this book

This book uses Python as its computational tool. Since Python is free, any school or organization can download and use it. This book is organized according to various finance subjects. In other words, the first edition focuses more on Python, while the second edition is truly trying to apply Python to finance. The book starts by explaining topics exclusively related to Python. Then we deal with critical parts of Python, explaining concepts such as time value of money stock and bond evaluations, capital asset pricing model, multi-factor models, time series analysis, portfolio theory, options and futures. This book will help us to learn or review the basics of quantitative finance and apply Python to solve various problems, such as estimating IBM’s market risk, running a Fama-French 3-factor, 5-factor, or Fama-French-Carhart 4 factor model, estimating the VaR of a 5-stock portfolio, estimating the optimal portfolio, and constructing the efficient frontier for a 20-stock portfolio with real-world stock, and with Monte Carlo Simulation. Later, we will also learn how to replicate the famous Black-Scholes-Merton option model and how to price exotic options such as the average price call option.
Table of Contents (23 chapters)
Python for Finance Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Index

Chapter 4. Sources of Data

Since our society entered a so-called information era, we have been engulfed by a huge amount of information or data. For this very reason, there is an increasing demand for persons armed with data handling skills, such as data scientists or graduates from business analytics programs. Kane (2006) proposed an open source finance concept which consists of three components:

  • The use of open source software in testing hypotheses and implementing investment strategies

  • Cheap access to financial data

  • Replication to confirm published research results

In this book, these three components are simply called: open software, open data, and open codes. Python is one of the best-known pieces of open source software. At the moment, usage of public data is quite inconsistent with the current environment. In this book, we use a huge amount of data, especially public data. In this chapter, the following topics will be covered:

  • Open source finance

  • Source of macro-economic data

  • Source of accounting...