I have a constraint quadratic (CQ) and linear objective portfolio optimization problem which I would like to reduce to a LP or QP standard form via some trick.
The original problem definition is to find the portfolio configuration x that maximizes the returns while keeping the cost to be at most C and the risk to be at most V where Sigma is the covariance matrix (SDP):
I first thought of doing a variable transformation so the QC could be linearized i.e. define a variable vector:
and then my problem would become:
and then my solution would be the squared root of the resulting but I am afraid that the "equivalent" cost constraint is not exactly equivalent ...
Can anyone please advice?
Many thanks in advance,