ON THE MAXIMIZATION OF THE GEOMETRIC MEAN WITH LOGNORMAL RETURN DISTRIBUTION.

In this paper we discuss the relevancy of the geometric mean as a portfolio selection criteria. A procedure for finding that portfolio with the highest geometric mean when returns on portfolios are lognormally distributed is presented. The development of this algorithm involves a proof that the portfolio with maximum geometric mean lies on the efficient frontier in arithmetic mean variance space. This finding has major implications for the relevancy of much of portfolio and general equilibrium theory. These implications are explored. [ABSTRACT FROM AUTHOR]