In this study, we investigate empirically whether the control of the correlation matrix via the random matrix theory (RMT) method can create a more efficient portfolio than the traditional Markowitzs model. The reasons for this improvement are also investigated. From the viewpoints of both the degree of efficiency and diversification, we find that the portfolio from the correlation matrix without the properties of the largest eigenvalue via the RMT method is more efficient than the one created from the conventional Markowitz’s model. Furthermore, we empirically confirm that the properties of the largest eigenvalue cause an increase in the value of the correlation matrix and a decrease in the degree of diversification, thus ultimately increasing the degree of portfolio risk. These results suggest that the properties of a market factor are negatively related to the degree of efficiency obtainable through the Markowitzs portfolio model. In addition, on the basis of the ex-ante test (using the expected stock returns and risk of the past period as well as actual data in the future period) we find that the performance of the observed RMT-based efficient portfolio is superior to that of the portfolio from Markowitzs model. These results demonstrate that the improvement of Markowitzs portfolio model via the control of the correlation matrix can be a source of significant practical utility.