Book Image

Python for Finance

By : Yuxing Yan
Book Image

Python for Finance

By: Yuxing Yan

Overview of this book

Table of Contents (20 chapters)
Python for Finance
About the Author
About the Reviewers

Understanding optimization

In finance, many issues depend on optimization, such as choosing an optimal portfolio with an objective function and with a set of constraints. For those cases, we could use a SciPy optimization module called scipy.optimize. Assume that we want to estimate the x value that minimizes the value of y, where y =3 + x2. Obviously, the minimum value of y is achieved when x takes a value of 0.

>>>import scipy.optimize as optimize 
>>>def my_f(x):
       Return 3 + x**2
>>>optimize.fmin(my_f,5)   # 5 is initial value
     Optimization terminated successfully
     Current function values: 3:000000
     Iterations: 20
     Function evaluations: 40
Array([ 0. ])

To find a list of all input variables to this fmin() function and their meanings, issue help(optimize.fmin). To list all the functions included in scipy.optimize, issue dir(optimize).