Optimal portfolios with asymptotic criteria

This paper is concerned with a portfolio optimization model for a long planning horizon. The authors first argue that in this case the asymptotic growth rate and the asymptotic variance are better measures of performance than the usual mean and variance of return. They next propose an efficient algorithm for calculating the asymptotic frontier, i.e., the efficient frontier relative to the new criteria. Finally, the authors illustrate the present methods and compare the difference between the model and the classical mean-variance-model by using historical data based on the 1064 stocks of the Tokyo Stock Exchange.