• C++ Programming for Financial Engineering
    Highly recommended by thousands of MFE students. Covers essential C++ topics with applications to financial engineering. Learn more Join!
    Python for Finance with Intro to Data Science
    Gain practical understanding of Python to read, understand, and write professional Python code for your first day on the job. Learn more Join!
    An Intuition-Based Options Primer for FE
    Ideal for entry level positions interviews and graduate studies, specializing in options trading arbitrage and options valuation models. Learn more Join!

Sampling Correlated Asset Paths

DanM

Math Student
Joined
8/1/09
Messages
179
Points
28
I've seen some do this by performing Cholesky factorization on the correlation matrix and some by performing it in the covariance matrix. Which way is correct?
 
You could do it either way. Starting with a vector of uncorrelated standard normals, using the covariance matrix is more direct since you have to factor in the individual volatilities anyway.
 
Back
Top