#### Overview of this book

Python for Finance
Credits
Acknowledgments
www.PacktPub.com
Preface
Free Chapter
Introduction and Installation of Python
13 Lines of Python to Price a Call Option
Introduction to Modules
Statistical Analysis of Time Series
Index

## Cumulative standard normal distribution

In Chapter 4, 13 Lines of Python to Price a Call Option, we used 13 lines of Python codes to price a call option since we have to write our own cumulative standard normal distribution. Fortunately, the cumulative standard normal distribution is included in the submodule of `SciPy`. The following example shows the value of the cumulative standard normal distribution at zero:

```>>>from scipy.stats import norm
>>>norm.cdf(0)
0.5
```

Thus, we could simplify our call option model considerably using just five lines. The following code is a typical example of the benefits we can enjoy using various modules:

```from scipy import log,exp,sqrt,stats
defbs_call(S,X,T,r,sigma):
d1=(log(S/X)+(r+sigma*sigma/2.)*T)/(sigma*sqrt(T))
d2 = d1-sigma*sqrt(T)
return S*stats.norm.cdf(d1)-X*exp(-r*T)*stats.norm.cdf(d2)
```

Now, we could use the following function by inputting a set of values:

```>>>price=bs_call(40,40,1,0.03,0.2)
>>>round(price...```