Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Mastering Pandas for Finance

You're reading from   Mastering Pandas for Finance Master pandas, an open source Python Data Analysis Library, for financial data analysis

Arrow left icon
Product type Paperback
Published in May 2015
Publisher Packt
ISBN-13 9781783985104
Length 298 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Michael Heydt Michael Heydt
Author Profile Icon Michael Heydt
Michael Heydt
Arrow right icon
View More author details
Toc

Table of Contents (11) Chapters Close

Preface 1. Getting Started with pandas Using Wakari.io FREE CHAPTER 2. Introducing the Series and DataFrame 3. Reshaping, Reorganizing, and Aggregating 4. Time-series 5. Time-series Stock Data 6. Trading Using Google Trends 7. Algorithmic Trading 8. Working with Options 9. Portfolios and Risk Index

Volatility calculation


The volatility of a stock is a measurement of the change in variance in the returns of a stock over a specific period of time. It is common to compare the volatility of a stock with another stock to get a feel for which may have less risk or to a market index to examine the stock's volatility in the overall market. Generally, the higher the volatility, the riskier the investment in that stock, which results in investing in one over another.

Volatility is calculated by taking a rolling window standard deviation on the percentage change in a stock. The size of the window affects the overall result. The wider the window, the less representative the measurement will become. As the window narrows, the result approaches the standard deviation. So, it is a bit of an art to pick the proper window size based upon the data sampling frequency. Fortunately, pandas makes this very easy to modify interactively.

As a demonstration, the following command calculates the volatility of...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime