Multivariate quadrature (approximation of joint distribution for portfolio choice)

1 次查看(过去 30 天)
I would like to numerically compute an optimal portfolio, using multiple assets, which are correlated.
So my question is:
  1. Is there a standard approach for multi-dimensional quadrature? (standard deviation and covariance are sufficient statistics). I only saw this on the file exchange: https://nl.mathworks.com/matlabcentral/fileexchange/13508-multi-dimensional-gauss-points-and-weights
  2. Or is the standard approach to use Monte Carlo simulation, using random draws from a multi-variate distribution (random number generator)
I specifically do not want to use theoretical solutions, but numerical ones.
Many thanks in advance!
  2 个评论
Torsten
Torsten 2022-11-16
编辑:Torsten 2022-11-16
The standard approach is to use "int" for symbolic integration or "integral", "integral2", "integral3" for numerical integration.
Sargondjani
Sargondjani 2022-11-17
@Torsten thank you!! That works very nice, at least upto 3 dimensions... I guess for higher dimensions I'll have to stick with Monte Carlo simulation.

请先登录,再进行评论。

回答(0 个)

类别

Help CenterFile Exchange 中查找有关 Portfolio Optimization and Asset Allocation 的更多信息

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by