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

Pricing average options


In Chapter 12, Monte Carlo Simulation, we discussed two exotic options. For convenience, we will include them in this chapter as well. Because of this, readers will find some duplicates. European and American options are path-independent options. This means that an option's payoff depends only on the terminal stock price and strike price. One related issue for path-dependent options is market manipulation at the maturity date. Another issue is that some investors or hedgers might care more about the average price instead of a terminal price.

For example, a refinery is worried about oil, its major raw material, and price movement in the next three months. They plan to hedge the potential price jumps in crude oil. The company could buy a call option. However, since the firm consumes a huge amount of crude oil every day, naturally it cares more about the average price instead of just the terminal price on which a vanilla call option depends. For such cases, average options...