The portfolio optimization functions assist portfolio managers in constructing portfolios that optimize risk and return.
Computes the optimal risky portfolio on the efficient frontier, based on the risk-free rate, the borrowing rate, and the investor's degree of risk aversion. Also generates the capital allocation line, which provides the optimal allocation of funds between the risky portfolio and the risk-free asset.
|Efficient Frontier Computation||Description|
Computes portfolios along the efficient frontier for a given group of assets. The computation is based on sets of constraints representing the maximum and minimum weights for each asset, and the maximum and minimum total weight for specified groups of assets.
Computes portfolios along the efficient frontier for a given group of assets. Generates a surface of efficient frontiers showing how asset allocation influences risk and return over time.
Computes portfolios along the efficient frontier for a given group of assets. The computation is based on a set of user-specified linear constraints. Typically, these constraints are generated using the constraint specification functions described below.
Generates the portfolio constraints matrix for a portfolio
of asset investments using linear inequalities. The inequalities are
of the type
Portfolio value at risk (VaR) returns the maximum potential
loss in the value of a portfolio over one period of time, given the
loss probability level
Asset minimum and maximum allocation. Generates a constraint set to fix the minimum and maximum weight for each individual asset.
Group-to-group ratio constraint. Generates a constraint set specifying the maximum and minimum ratios between pairs of groups.
Asset group minimum and maximum allocation. Generates a constraint set to fix the minimum and maximum total weight for each defined group of assets.
Total portfolio value. Generates a constraint set to fix the total value of the portfolio.
Transforms a constraint matrix expressed in absolute weight format to an equivalent matrix expressed in active weight format.
Transforms a constraint matrix expressed in active weight format to an equivalent matrix expressed in absolute weight format.
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.