estimatePortStd

Estimate standard deviation of portfolio returns

Syntax

pstd = estimatePortStd(obj,pwgt)

Description

pstd = estimatePortStd(obj,pwgt) estimate standard deviation of portfolio returns for PortfolioCVaR or PortfolioMAD objects. For details on the workflows, see PortfolioCVaR Object Workflow and PortfolioMAD Object Workflow.

Examples

Estimate Standard Deviations for Portfolio Returns for a PortfolioCVaR Object

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($$seed$$) resets the random number generator to produce the documented results. It is not necessary to reset the random number generator to simulate scenarios.

Estimate Standard Deviations for Portfolio Returns for a PortfolioMAD Object

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

pwgt = estimateFrontierLimits(p);

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

    0.0222
    0.1010

The function rng($$seed$$) 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

obj — Object for portfolio

object

Object for portfolio, specified using a PortfolioCVaR or PortfolioMADobject.

For more information on creating a PortfolioCVaR or PortfolioMAD object, see

• PortfolioCVaR

• PortfolioMAD

Data Types: object

pwgt — Collection of portfolios

matrix

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

pstd — Estimates for standard deviations of portfolio returns for each portfolio in pwgt

vector

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);