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Python for Finance

You're reading from  Python for Finance

Product type Book
Published in Apr 2014
Publisher
ISBN-13 9781783284375
Pages 408 pages
Edition 1st Edition
Languages
Author (1):
Yuxing Yan Yuxing Yan
Profile icon Yuxing Yan

Table of Contents (20) Chapters

Python for Finance
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
Introduction and Installation of Python Using Python as an Ordinary Calculator Using Python as a Financial Calculator 13 Lines of Python to Price a Call Option Introduction to Modules Introduction to NumPy and SciPy Visual Finance via Matplotlib Statistical Analysis of Time Series The Black-Scholes-Merton Option Model Python Loops and Implied Volatility Monte Carlo Simulation and Options Volatility Measures and GARCH Index

Adding texts to our graph


In the following example, we simply insert a text. Remember that the x and y scale is from 0 to 1:

>>>from pylab import *
>>>x = [0,1,2]
>>>y = [2,4,6]
>>>plot(x,y)
>>>figtext(0.2, 0.7, 'North & West')
>>>figtext(0.7, 0.2, 'East & South')
>>>show()

The corresponding output graph is given as follows:

Let's make it more complex. From the National Bureau of Economic Research web page at http://www.nber.org/cycles.html, we can find the following table showing the business cycle in the past two decades:

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Turning Point Date

Peak or Trough

Announcement Date

June 1, 2009

Trough

September 20, 2010

December 1, 2007

Peak

December 1, 2008

November 1, 2001

Trough

July 17, 2003

March 1, 2001

Peak

November 26, 2001

March 1, 1991

Trough

December 22, 1992

July 1, 1990

Peak

April 25, 1991

November 1, 1982

Trough

July 8, 1983

July 1, 1981

Peak

June 1, 1982

July 1, 1980

Trough

July 8,...