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Python for Finance

Python for Finance

By : Yuxing Yan
3.9 (22)
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Python for Finance

Python for Finance

3.9 (22)
By: Yuxing Yan

Overview of this book

A hands-on guide with easy-to-follow examples to help you learn about option theory, quantitative finance, financial modeling, and time series using Python. Python for Finance is perfect for graduate students, practitioners, and application developers who wish to learn how to utilize Python to handle their financial needs. Basic knowledge of Python will be helpful but knowledge of programming is necessary.
Table of Contents (14 chapters)
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13
Index

Relationship between input values and option values

When the volatility of an underlying stock increases, both its call and put values increase. The logic is that when a stock becomes more volatile, we have a better chance to observe extreme values, that is, we have a better chance to exercise our option. The following Python program shows this relationship:

import numpy as np
import p4f as pf
s0=30;T0=0.5;sigma0=0.2;r0=0.05;x0=30
sigma=np.arange(0.05,0.8,0.05)
T=np.arange(0.5,2.0,0.5)
call_0=pf.bs_call(s0,x0,T0,r0,sigma0)
call_sigma=pf.bs_call(s0,x0,T0,r0,sigma)
call_T=pf.bs_call(s0,x0,T,r0,sigma0)
plot(sigma,call_sigma,'b')
plot(T,call_T)

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