Re: [Quantlib-dev] Simulating multiple correlated stochastic processes

[Max <ma...@gm...>]

Hi,

I studied the code further. And I realized that in StochasticProcessArray
class, the correlation matrix L is decomposed into a lower triangular using
SalvagingAlgorithm::Spectral. Then the new triangular matrix is applied to
the array of independent normal random variables.

I am not familiar with the "Spectral" analysis. However, I want to ask:
Given correlation matrix is symmetric and positive semidefinite, can I use
SalvagingAlgorithm::none method (which is essentially a Cholesky
decomposition) instead? And in this case, would the final results be
equivelant for SalvagingAlgorithm::Spectral and SalvagingAlgorithm::none
methods?


On Thu, Jun 26, 2008 at 12:08 AM, Max <ma...@gm...> wrote:

> Hi,
>
> I am trying to simulate the price dynamics of 4 different assets given the
> correlation among them (assuming all asset returns follow geometric Brownian
> motion).
>
> I have implemented the monte-carlo simulation using Quantlib classes, such
> as StochasticProcessArray, MultiPathGenerator, etc.
>
> However, I am not so sure how the StochasticProcessArray implementation
> ensures the correlation among the 4 assets is guaranteed, given the input
> 4x4 correlation matrix is positive defintie. Could someone help explain this
> from a theoretical perspective? or point me to the related reference?
>
> Thanks!
>
> Best regards,
> Max
>
>