Cholesky Decomposition and Its Applications in Python

In this video, we go over Cholesky decomposition of symmetric matrices. In terms of solving systems of linear equations, it is very similar to LU decomposition. I will show how to do the decomposition in and how to solve a system of linear equations using Numpy’s and Scipy’s built-in functions. Then we will explore how we can use this to generate correlated random variables. This has applications in finance where one might wish to do a Monte Carlo simulation on two or more correlated stocks.

Github: https://github.com/kpmooney/numerical_methods_youtube/blob/master/matrix_decomposition/Cholesky%20Decomposition.ipynb
Tip Jar: https://patpal.me/kpmooney