This function determines a risk-parity solution of a long-only
 portfolio with a budget-constraint.

optimize

Routines for solving convex optimization problems with cone constraints by means of interior-point methods. The implemented algorithms are partially ported from CVXOPT, a Python module for convex optimization (see <https://cvxopt.org> for more information).

Bernhard Pfaff

cccp

Cone Constrained Convex Problems

Lieven Vandenberghe

Martin Andersen

Joachim Dahl

rp function

<dl> <dt>x0</dt>
<dd><code>matrix</code> of dimension \(n \times 1\); starting values.</dd> <dt>P</dt>
<dd><code>matrix</code> of dimension \(n \times n\); dispersion matrix.</dd> <dt>mrc</dt>
<dd><code>matrix</code> of dimension \(n \times 1\); the marginal
 risk contributions.</dd> <dt>optctrl</dt>
<dd>An object of S4-class <code>Rcpp_CTRL</code>.</dd></dl>

Arguments

Risk-parity optimization — rp

<dl>

 <dt>x0</dt>
<dd><code>matrix</code> of dimension \(n \times 1\); starting values.</dd>

 <dt>P</dt>
<dd><code>matrix</code> of dimension \(n \times n\); dispersion matrix.</dd>

 <dt>mrc</dt>
<dd><code>matrix</code> of dimension \(n \times 1\); the marginal
 risk contributions.</dd>

 <dt>optctrl</dt>
<dd>An object of S4-class <code>Rcpp_CTRL</code>.</dd>

</dl>

rp: Risk-parity optimization

Description

Usage

Value

Arguments

References