Mastering pandas for Finance Kindle Edition

by Michael Heydt (Author) Format: Kindle Edition

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ISBN-13: 978-1783985104

ISBN-10: 1783985100

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Master pandas, an open source Python Data Analysis Library, for financial data analysis

About This Book

A single source for learning how to use the features of pandas for financial and quantitative analysis.
Explains many of the financial concepts including market risk, options valuation, futures calculation, and algorithmic trading strategies.
Step-by-step demonstration with interactive and incremental examples to apply pandas to finance

Who This Book Is For

If you are interested in quantitative finance, financial modeling, and trading, or simply want to learn how Python and pandas can be applied to finance, then this book is ideal for you. Some knowledge of Python and pandas is assumed. Interest in financial concepts is helpful, but no prior knowledge is expected.

What You Will Learn

Modeling and manipulating financial data using the pandas DataFrame
Indexing, grouping, and calculating statistical results on financial information
Time-series modeling, frequency conversion, and deriving results on fixed and moving windows
Calculating cumulative returns and performing correlations with index and social data
Algorithmic trading and backtesting using momentum and mean reversion strategies
Option pricing and calculation of Value at Risk
Modeling and optimization of financial portfolios

In Detail

This book will teach you to use Python and the Python Data Analysis Library (pandas) to solve real-world financial problems.

Starting with a focus on pandas data structures, you will learn to load and manipulate time-series financial data and then calculate common financial measures, leading into more advanced derivations using fixed- and moving-windows. This leads into correlating time-series data to both index and social data to build simple trading algorithms. From there, you will learn about more complex trading algorithms and implement them using open source back-testing tools. Then, you will examine the calculation of the value of options and Value at Risk. This then leads into the modeling of portfolios and calculation of optimal portfolios based upon risk. All concepts will be demonstrated continuously through progressive examples using interactive Python and IPython Notebook.

By the end of the book, you will be familiar with applying pandas to many financial problems, giving you the knowledge needed to leverage pandas in the real world of finance.

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Product details

ASIN ‏ : ‎ B00Y9W1838
Publisher ‏ : ‎ Packt Publishing (May 25, 2015)
Publication date ‏ : ‎ May 25, 2015
Language ‏ : ‎ English
File size ‏ : ‎ 20464 KB
Text-to-Speech ‏ : ‎ Enabled
Screen Reader ‏ : ‎ Supported
Enhanced typesetting ‏ : ‎ Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Not Enabled
Print length ‏ : ‎ 300 pages
Lending ‏ : ‎ Not Enabled

Best Sellers Rank: #1,852,381 in Kindle Store (See Top 100 in Kindle Store)
- #191 in Personal Finance Software (Kindle Store)
- #341 in Business Accounting Software Computer
- #351 in Personal Finance Software (Books)

Customer Reviews:
8 ratings

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Jbabek

Great book, dodgy seller

Reviewed in the United States on August 21, 2020

Verified Purchase

There is a note on the back of the book that says 'For Sale in India Only', and it was blacked out in sharpie. Great book otherwise. Will not buy from this seller again, as there are examples in the online version of the book that do not match the ones here.

Helpful

Al Krinker

The content is great and it def will get you going

Reviewed in the United States on October 7, 2016

I wish I could give it 5 stars, but since this book was poorly edited by tech reviewer that missed many errors, I can't go above 3... The content is great and it def will get you going, but some formulas for example Value at Risk at the very end is incorrect and even in example it is wrong (they forgot the mean!)

4 people found this helpful

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yatgonewest

Excellent intro to Pandas

Reviewed in the United States on August 30, 2015

I would recommend this book as a good basic intro to the fundamentals of Pandas even if you're not particularly interested in applying it to finance. I have read portions of a few others and this authors style is very concise and to the point on Series and DataFrames, and in particular on indexing of both.

7 people found this helpful

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Amazon Customer

Another great book on Pandas!

Reviewed in the United States on July 1, 2015

This book brings together several important concepts in finance and explains how to implement them using a core of Python and pandas. Some of the key topics included in the books are:

Wakari.io - a collaborative data analytics platform that allows to explore data and create analytic scripts in collaboration with IPython Notebooks.
Introduction to the Series and DataFrame objects
A chapter on Reshaping, Reorganizing, and Aggregating Data
Correlations of Google trends with stock movements, creating algorithmic trading systems
Calculating options payoffs, prices, and behaviors
Constructing an efficient portfolio
An overview of modern portfolio theory and Computing Value at Risk (VaR)

I liked that the provided code is in the form of ipython notebook.

Disclaimer: I received this eBook as a complementary copy.

One person found this helpful

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ajk251

Nice overview

Reviewed in the United States on July 11, 2015

I found this book to be a useful one - it nicely covers all the pandas/finance basics. If your're a bit of a novice in either one, this book provides a nice introduction. It doesn't waste time with a Python introduction or other book-filling topics. It shows how to do all of the most useful operations in pandas as they relate to finance. Then it goes into options, portfolio theory, and applying pandas to a Google Trends project. I particularly liked the section on Zipline, a back-testing library. It was a little clearer than the documentation. The part where Quandl is used is also nice.

That said, if you dug around the internet, you could probably cobble these examples together. Also, it doesn't really go into either pandas or finance too deeply. I don't hold those against the book - it can't be all things to all people. The book makes for a nice overview of the relevant topics - but expect an overview.

Note: I was asked to give a review of the book by the publisher in exchange for a free ebook (I purchased the book from the publisher).

2 people found this helpful

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