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estimatePortReturn

Estimate mean of portfolio returns for PortfolioMAD object

Syntax

pret = estimatePortReturn(obj,pwgt)

Description

pret = estimatePortReturn(obj,pwgt) estimates the mean of portfolio returns (as the proxy for portfolio returns).

 Note:   Depending on whether costs have been set, the portfolio return is either gross or net portfolio returns.

Tips

You can also use dot notation to estimate the mean of portfolio returns (as the proxy for portfolio return).

`pret = obj.estimatePortReturn(pwgt);`

Input Arguments

 obj MAD portfolio object [PortfolioMAD]. pwgt Collection of portfolios [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.

Output Arguments

 pret Estimates for means of portfolio returns for each portfolio in pwgt [NumPorts vector]. Portfolio weights are a [NumAssets-by-NumPorts matrix] and pret is a NumPorts-by-1 vector, where NumAssets is the number of assets in the universe and NumPorts is the number of portfolios in the collection of portfolios.

Attributes

 Access public Static false Hidden false

To learn about attributes of methods, see Method Attributes in the MATLAB® Object-Oriented Programming documentation.

Examples

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Estimate the Mean of Portfolio Returns

Given portfolio p, use the estimatePortReturn method to estimate the mean 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);
pret = estimatePortReturn(p, pwgt);
disp(pret)
```
```    0.0048
0.0154

```

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.