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Python for Finance

Python for Finance

By : Yuxing Yan
3.9 (22)
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Python for Finance

Python for Finance

3.9 (22)
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)
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13
Index

Outputting data to external files

In this section, we discuss several ways to save our data, such as saving data or estimating results to a text file, a binary file, and so on.

Outputting data to a text file

The following code will download IBM's daily price historical data and save it to a text file:

>>>from matplotlib.finance import quotes_historical_yahoo
>>>import re
>>>ticker='dell'
>>>outfile=open("c:/temp/dell.txt","w")
>>>begdate=(2013,1,1)
>>>enddate=(2013,11,9)
>>>p = quotes_historical_yahoo(ticker, begdate, enddate,asobject=True, adjusted=True)
>>>x2= re.sub('[\(\)\{\}\.<>a-zA-Z]','', x)
>>>outfile.write(x2)
>>>outfile.close()

Saving our data to a binary file

The following program first generates a simple array that has just three values. We save them to a binary file named tmp.bin at C:\temp\:

>>>import array
>>>import...

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