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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

Simulating a GARCH (p,q) process using modified garchSim()


The following code is based on the R function called garchSim(), which is included in the R package called fGarch. The authors for fGarch are Diethelm Wuertz and Yohan Chalabi. To find the related manual, we perform the following steps:

  1. Go to http://www.r-project.org.

  2. Click on CRAN under Download, Packages.

  3. Choose a close-by server.

  4. Click on Packages on the left-hand side of the screen.

  5. Choose a list and search for fGarch.

  6. Click on the link and download the PDF file related to fGarch.

The Python program based on the R program is given as follows:

import scipy as sp
import numpy as np
import matplotlib.pyplot as plt
#
sp.random.seed(12345) 
m=2
n=100              # n is the number of observations
nDrop=100          # we need to drop the first several observations 
delta=2
omega=1e-6 
alpha=(0.05,0.05)
#
beta=0.8 
mu,ma,ar=0.0,0.0,0.0
gamma=(0.0,0.0) 
order_ar=sp.size(ar) 
order_ma=sp.size(ma) 
order_beta=sp.size(beta)
#
order_alpha =sp.size...
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