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Python for Finance. - Second Edition

You're reading from  Python for Finance. - Second Edition

Product type Book
Published in Jun 2017
Publisher
ISBN-13 9781787125698
Pages 586 pages
Edition 2nd Edition
Languages

Table of Contents (23) Chapters

Python for Finance Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Python Basics Introduction to Python Modules Time Value of Money Sources of Data Bond and Stock Valuation Capital Asset Pricing Model Multifactor Models and Performance Measures Time-Series Analysis Portfolio Theory Options and Futures Value at Risk Monte Carlo Simulation Credit Risk Analysis Exotic Options Volatility, Implied Volatility, ARCH, and GARCH Index

Selecting m stocks randomly from n given stocks


Based on the preceding program, we could easily choose 20 stocks from 500 available securities. This is an important step if we intend to investigate the impact of the number of randomly selected stocks on the portfolio volatility, as shown in the following code:

import scipy as sp 
n_stocks_available=500 
n_stocks=20 
sp.random.seed(123345) 
x=sp.random.uniform(low=1,high=n_stocks_available,size=n_stocks)
y=[] 
for i in range(n_stocks): 
    y.append(int(x[i])) 
#print y 
final=sp.unique(y) 
print(final) 
print(len(final))
[  8  31  61  99 124 148 155 172 185 205 226 275 301 334 356 360 374 379
 401 449]
20

In the preceding program, we select 20 numbers from 500 numbers. Since we have to choose integers, we might end up with less than 20 values, that is, some integers appear more than once after we convert real numbers into integers. One solution is to pick more than we need. Then choose the first 20 integers. An alternative is to use the randrange...

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