Book Image

Python for Finance

By : Yuxing Yan
Book Image

Python for Finance

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)
13
Index

Debugging a program from a Python editor

The preceding two sections show the two ways to activate our program, that is, from a Python editor or using the import function. Usually, the choice should depend on a user's preference. However, while debugging, activating our program from our Python editor is much better than the second method. If we use the second method, our program is not updated as we normally expect.

The following example contains a typo since we use both r (lower case) and R (capital letter) in the program (assume that we save it under C:\Python33 with the name test02.py):

def pv_f(fv,r,n):
    return fv/(1+R)**n   # a typo of r

After issuing from test02 import * and calling the function, we will see an error message, as shown in the following code:

>>>from test02 import *
>>>pv_f(100,0.1,1)
Traceback (most recent call last):
  File "<pyshell#1>", line 1, in <module>
    pv_f(100,0.1,1)
  File ".\test02.py", line 3, in...