Portfolio Construction Examples
Introduction
The efficient frontier computation functions require information about each asset
                in the portfolio. This data is entered into the function via two matrices: an
                expected return vector and a covariance matrix. The expected return vector contains
                the average expected return for each asset in the portfolio. The covariance matrix
                is a square matrix representing the interrelationships between pairs of assets. This
                information can be directly specified or can be estimated from an asset return time
                series with the function ewstats.
Note
An alternative to using these portfolio optimization functions is to use
                        the Portfolio object (Portfolio) 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.
Efficient Frontier Example
frontcon has been removed. To model the efficient frontier, use
                the Portfolio object instead. For
                example, using the Portfolio object, you can model an
                efficient frontier:
See Also
portalloc | frontier | portopt | Portfolio | portcons | portvrisk | pcalims | pcgcomp | pcglims | pcpval | abs2active | active2abs