# Documentation

### This is machine translation

Translated by
Mouseover text to see original. Click the button below to return to the English version of the page.

# estimatePortStd

Estimate standard deviation of portfolio returns

Use the estimatePortStd function with a PortfolioCVaR or PortfolioMAD objects to estimate standard deviation of portfolio returns.

For details on the workflows, see PortfolioCVaR Object Workflow and PortfolioMAD Object Workflow.

## Syntax

pstd = estimatePortStd(obj,pwgt)

## Description

example

pstd = estimatePortStd(obj,pwgt) estimate standard deviation of portfolio returns for PortfolioCVaR or PortfolioMAD objects.

## Examples

collapse all

Given a portfolio pwgt, use the estimatePortStd function to show the standard deviation of portfolio returns.

m = [ 0.05; 0.1; 0.12; 0.18 ];
C = [ 0.0064 0.00408 0.00192 0;
0.00408 0.0289 0.0204 0.0119;
0.00192 0.0204 0.0576 0.0336;
0 0.0119 0.0336 0.1225 ];
m = m/12;
C = C/12;

rng(11);

AssetScenarios = mvnrnd(m, C, 20000);

p = PortfolioCVaR;
p = setScenarios(p, AssetScenarios);
p = setDefaultConstraints(p);
p = setProbabilityLevel(p, 0.95);

pwgt = estimateFrontierLimits(p);

pstd = estimatePortStd(p, pwgt);
disp(pstd)
0.0223
0.1010

The function rng() resets the random number generator to produce the documented results. It is not necessary to reset the random number generator to simulate scenarios.

Given a portfolio pwgt, use the estimatePortStd function to show the standard deviation of portfolio returns.

m = [ 0.05; 0.1; 0.12; 0.18 ];
C = [ 0.0064 0.00408 0.00192 0;
0.00408 0.0289 0.0204 0.0119;
0.00192 0.0204 0.0576 0.0336;
0 0.0119 0.0336 0.1225 ];
m = m/12;
C = C/12;

rng(11);

AssetScenarios = mvnrnd(m, C, 20000);

p = setScenarios(p, AssetScenarios);
p = setDefaultConstraints(p);

pwgt = estimateFrontierLimits(p);

pstd = estimatePortStd(p, pwgt);
disp(pstd)
0.0222
0.1010

The function rng() resets the random number generator to produce the documented results. It is not necessary to reset the random number generator to simulate scenarios.

## Input Arguments

collapse all

Object for portfolio, specified using a PortfolioCVaR or PortfolioMADobject.

Collection of portfolios, specified as a NumAssets-by-NumPorts matrix, where NumAssets is the number of assets in the universe and NumPorts is the number of portfolios in the collection of portfolios.

Data Types: double

## Output Arguments

collapse all

Estimates for standard deviations of portfolio returns for each portfolio in pwgt, returned as a NumPorts vector.

## Tips

You can also use dot notation to estimate the standard deviation of portfolio returns.

pstd = obj.estimatePortStd(pwgt);