I would like to numerically compute an optimal portfolio, using multiple assets, which are correlated. So my question is: 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 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!

Multivariate quadrature (approximation of joint distribution for portfolio choice)

Sargondjani

2022 11 月 16

0 回答

6 ビュー (30 日間)

0 投票

I would like to numerically compute an optimal portfolio, using multiple assets, which are correlated.

So my question is:

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
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 件のコメント
なしを表示なしを非表示

Torsten 2022 年 11 月 16 日

編集済み: Torsten 2022 年 11 月 16 日

The standard approach is to use "int" for symbolic integration or "integral", "integral2", "integral3" for numerical integration.

Sargondjani 2022 年 11 月 17 日

@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.

サインインしてコメントする。

サインインしてこの質問に回答する。

Follow Question