The Geometric Portfolio Optimization with Semivariance in Financial Engineering

In this paper we consider a portfolio optimization problem on maximizing the geometric mean return subject to the lower semivariance as a risk measure in the financial engineering. Its optimal condition and the solving method via the Monte Carlo simulation are given, and a numerical experiment is presented in order to show that the method is efficient.