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Portfolio expected rate of return



R = portror(Return,Weight) returns a 1-by-M vector for the expected rate of return.


An alternative for portfolio optimization is to use the Portfolio object for mean-variance portfolio optimization. This object supports gross or net portfolio returns as the return proxy, the variance of portfolio returns as the risk proxy, and a portfolio set that is any combination of the specified constraints to form a portfolio set. For information on the workflow when using Portfolio objects, see Portfolio Object Workflow.


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This example shows a portfolio that is made up of two assets ABC and XYZ having expected rates of return of 10% and 14%, respectively. If 40% percent of the portfolio's funds are allocated to asset ABC and the remaining funds are allocated to asset XYZ, the portfolio's expected rate of return is:

r = portror([.1 .14],[.4 .6])
r = 0.1240

Input Arguments

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Rates of return, specified as a 1-by-N matrix. Each column of Return represents the rate of return for a single security.

Data Types: double

Weights, specified as a M-by-N matrix. Each row of Weight represents a different weighting combination of the assets in the portfolio.

Data Types: double

Output Arguments

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Expected rate of return, returned as a 1-by-M vector.


[1] Zvi Bodie, Alex Kane, Alan Marcus. Investments. McGraw-Hill Education; 10th edition (September 9, 2013).

Version History

Introduced before R2006a