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Mastering Python for Finance

You're reading from   Mastering Python for Finance Implement advanced state-of-the-art financial statistical applications using Python

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Product type Paperback
Published in Apr 2019
Publisher Packt
ISBN-13 9781789346466
Length 426 pages
Edition 2nd Edition
Languages
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Author (1):
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James Ma Weiming James Ma Weiming
Author Profile Icon James Ma Weiming
James Ma Weiming
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Toc

Table of Contents (16) Chapters Close

Preface 1. Section 1: Getting Started with Python FREE CHAPTER
2. Overview of Financial Analysis with Python 3. Section 2: Financial Concepts
4. The Importance of Linearity in Finance 5. Nonlinearity in Finance 6. Numerical Methods for Pricing Options 7. Modeling Interest Rates and Derivatives 8. Statistical Analysis of Time Series Data 9. Section 3: A Hands-On Approach
10. Interactive Financial Analytics with the VIX 11. Building an Algorithmic Trading Platform 12. Implementing a Backtesting System 13. Machine Learning for Finance 14. Deep Learning for Finance 15. Other Books You May Enjoy

Writing the StockOption base class

Before going any further and implementing the various pricing models that we are about to discuss, let's create a StockOption class to store and calculate the common attributes of the stock option that will be reused throughout this chapter:

In [ ]:
import math

"""
Stores common attributes of a stock option
"""
class StockOption(object):
def __init__(
self, S0, K, r=0.05, T=1, N=2, pu=0, pd=0,
div=0, sigma=0, is_put=False, is_am=False):
"""
Initialize the stock option base class.
Defaults to European call unless specified.

:param S0: initial stock price
:param K: strike price
:param r: risk-free interest rate
:param T: time to maturity
:param N:...
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