Book Image

Python for Finance - Second Edition

By : Yuxing Yan
5 (1)
Book Image

Python for Finance - Second Edition

5 (1)
By: Yuxing Yan

Overview of this book

This book uses Python as its computational tool. Since Python is free, any school or organization can download and use it. This book is organized according to various finance subjects. In other words, the first edition focuses more on Python, while the second edition is truly trying to apply Python to finance. The book starts by explaining topics exclusively related to Python. Then we deal with critical parts of Python, explaining concepts such as time value of money stock and bond evaluations, capital asset pricing model, multi-factor models, time series analysis, portfolio theory, options and futures. This book will help us to learn or review the basics of quantitative finance and apply Python to solve various problems, such as estimating IBM’s market risk, running a Fama-French 3-factor, 5-factor, or Fama-French-Carhart 4 factor model, estimating the VaR of a 5-stock portfolio, estimating the optimal portfolio, and constructing the efficient frontier for a 20-stock portfolio with real-world stock, and with Monte Carlo Simulation. Later, we will also learn how to replicate the famous Black-Scholes-Merton option model and how to price exotic options such as the average price call option.
Table of Contents (23 chapters)
Python for Finance Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
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...