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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

The put-call ratio


The put-call ratio represents the perception of investors jointly towards the future. If there is no obvious trend, that is, we expect a normal future, then the put-call ratio should be close to one. On the other hand, if we expect a much brighter future, the ratio should be lower than one. The following code shows a ratio of this type over the years. First, we have to download the data from CBOE. Perform the following steps:

  1. Go to http://www.cboe.com/.

  2. Click on Quotes & Data on the menu bar.

  3. Click on CBOE Volume & Put/Call Ratios.

  4. Click on CBOE Total Exchange Volume and Put/Call Ratios (11-01-2006 to present) under Current.

Assume that the file named totalpc.csv is saved under C:\temp\. The code is given as follows:

import pandas as pd
from matplotlib.pyplot import *
data=pd.read_csv('c:/temp/totalpc.csv',skiprows=2,index_col=0,parse_dates=True)
data.columns=('Calls','Puts','Total','Ratio')
x=data.index
y=data.Ratio
y2=ones(len(y))
title('Put-call ratio')
xlabel('Date...
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