Borrar filtros
Borrar filtros

Multivariate quadrature (approximation of joint distribution for portfolio choice)

4 visualizaciones (últimos 30 días)
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 comentarios
Torsten
Torsten el 16 de Nov. de 2022
Editada: Torsten el 16 de Nov. de 2022
The standard approach is to use "int" for symbolic integration or "integral", "integral2", "integral3" for numerical integration.
Sargondjani
Sargondjani el 17 de Nov. de 2022
@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.

Iniciar sesión para comentar.

Respuestas (0)

Categorías

Más información sobre Portfolio Optimization and Asset Allocation en Help Center y File Exchange.

Community Treasure Hunt

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

Start Hunting!

Translated by