The form of the problem looks like you are trying to do a mean-variance portfolio optimization. If that is the case, you should not be dealing with variance as a restriction, but as part of the objective function:

max (r'*w - rho*w'*V*w)
s.t. sum(w) == 1

where rho is a risk aversion parameter.

You can solve this as a quadratic programming problem using either 1) solve.QP from the quadprog package; 2) portfolio.optim in package tseries

see http://tolstoy.newcastle.edu.au/R/help/05/01/10505.html for details on how to use the two.


On Sunday 01 May 2005 19:21, Gottfried Gruber wrote:
hi,

i want to execute the following opimization problem:
max r*w
s.t.:   w*z=1   # sum of w is 1
r, w are [nx1] vectors, z is a [nx1] vector consisting of 1
so far so good, works fine with lp

the problem arises with the additional restriction
w' * V * w
where V is a [nxn] matrix
how can i include this restriction since w arises twice?

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