Sample vs. Population Mean-Variance Efficient Portfolios
研究用历史数据计算风险资产收益率时，抽样误差对投资组合排序的影响，发现要将误差控制在5%需50-100个观测值，远超常见做法。
It is common to use historical data in calculating the rates of return of risky options, and these data are used to calculate the mean and the variance, which are employed in the (MV) preference ranking. In this paper we study the effect of possible sampling error on the portfolio ranking. It is shown that in order to keep the error at a reasonable level (5 percent), one needs 50–100 observations, a number that is rarely used in the (MV) comparison of portfolios. The results are almost independent of the correlation between the portfolios.