Book Image

Python for Finance

By : Yuxing Yan
Book Image

Python for Finance

By: Yuxing Yan

Overview of this book

A hands-on guide with easy-to-follow examples to help you learn about option theory, quantitative finance, financial modeling, and time series using Python. Python for Finance is perfect for graduate students, practitioners, and application developers who wish to learn how to utilize Python to handle their financial needs. Basic knowledge of Python will be helpful but knowledge of programming is necessary.
Table of Contents (14 chapters)
13
Index

Summary

In this chapter, many concepts and issues associated with statistics are discussed in detail. Topics include how to download historical prices from Yahoo! Finance; estimate returns, total risk, market risk, correlation among stocks, and correlation among different country's markets; form various types of portfolios; estimate a portfolio variance-covariance matrix; construct an efficient portfolio, and an efficient frontier; and estimate the Roll (1984) spread, Amihud's (2002) illiquidity, and Pastor and Stambaugh's (2003) liquidity.

Although in Chapter 4, 13 Lines of Python Code to Price a Call Option, we discuss how to use 13 lines to price a call option based on the Black-Scholes-Merton model even without understanding its underlying theory and logic. In the next chapter, we will explain the option theory and its related applications in more detail.