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

Introduction to matplotlib


Graphs and other visual representations have become more important in explaining many complex financial concepts, trading strategies, and formulas.

In this section, we discuss the matplotlib module, which is used to create various types of graphs. In addition, the module will be used intensively in Chapter 10, Options and Futures, when we discuss the famous Black-Scholes-Merton option model and various trading strategies. The matplotlib module is designed to produce publication-quality figures and graphs. The matplotlib module depends on NumPy and SciPy, which were discussed in the previous sections. To save generated graphs, there are several output formats available, such as PDF, Postscript, SVG, and PNG.

How to install matplotlib

If Python was installed by using the Anaconda super package, then matplotlib is preinstalled already. After launching Spyder, type the following line to test. If there is no error, it means that we have imported/uploaded the module successfully...