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Python for Finance

You're reading from   Python for Finance Apply powerful finance models and quantitative analysis with Python

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Product type Paperback
Published in Jun 2017
Publisher
ISBN-13 9781787125698
Length 586 pages
Edition 2nd Edition
Languages
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Author (1):
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Yuxing Yan Yuxing Yan
Author Profile Icon Yuxing Yan
Yuxing Yan
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Table of Contents (17) Chapters Close

Preface 1. Python Basics FREE CHAPTER 2. Introduction to Python Modules 3. Time Value of Money 4. Sources of Data 5. Bond and Stock Valuation 6. Capital Asset Pricing Model 7. Multifactor Models and Performance Measures 8. Time-Series Analysis 9. Portfolio Theory 10. Options and Futures 11. Value at Risk 12. Monte Carlo Simulation 13. Credit Risk Analysis 14. Exotic Options 15. Volatility, Implied Volatility, ARCH, and GARCH Index

Introduction to the pandas_reader module

Via this module, users can download various economics and financial via Yahoo! Finance, Google Finance, Federal Reserve Economics Data (FRED), and Fama-French factors.

Assume that the pandas_reader module is installed. For detail on how to install this module, see the How to install a Python module section. First, let's look at the simplest example, just two lines to get IBM's trading data; see the following:

import pandas_datareader.data as web
df=web.get_data_google("ibm")

We could use a dot head and dot tail to show part of the results; see the following code:

>>> df.head()
>>> 
                  Open        High         Low       Close   Volume  
Date                                                                  
2010-01-04  131.179993  132.970001  130.850006  132.449997  6155300   
2010-01-05  131.679993  131.850006  130.100006  130.850006  6841400   
2010-01-06  130.679993  131.490005  129.809998  130.000000...
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