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Python for Finance

You're reading from   Python for Finance If your interest is finance and trading, then using Python to build a financial calculator makes absolute sense. As does this book which is a hands-on guide covering everything from option theory to time series.

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Product type Paperback
Published in Apr 2014
Publisher
ISBN-13 9781783284375
Length 408 pages
Edition 1st Edition
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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 (14) Chapters Close

Preface 1. Introduction and Installation of Python FREE CHAPTER 2. Using Python as an Ordinary Calculator 3. Using Python as a Financial Calculator 4. 13 Lines of Python to Price a Call Option 5. Introduction to Modules 6. Introduction to NumPy and SciPy 7. Visual Finance via Matplotlib 8. Statistical Analysis of Time Series 9. The Black-Scholes-Merton Option Model 10. Python Loops and Implied Volatility 11. Monte Carlo Simulation and Options 12. Volatility Measures and GARCH Index

Retrieving historical price data from Yahoo! Finance

The function called quotes_historical_yahoo() in the matplotlib module could be used to download historical price data from Yahoo! Finance. For example, we want to download daily price data for IBM over the period from January 1, 2012 to December 31, 2012, we have the following four-line Python code:

>>>from matplotlib.finance import quotes_historical_yahoo
>>>date1=(2012, 1, 1)
>>>date2=(2012, 12,31)
>>>price=quotes_historical_yahoo('IBM', date1, date2)

To download IBM's historical price data up to today, we could use the datetime.date.today() function as follows:

>>>import datetime
>>>import matplotlib.finance as finance
>>>import matplotlib.mlab as mlab
>>>ticker = 'IBM'
>>>begdate = datetime.date(2013,1,1)
>>>enddate = datetime.date.today()
>>>price = finance.fetch_historical_yahoo(ticker, begdate, enddate)
&gt...
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