Based on the mean-variance model,the multi-prior approach is applied to study the optimum problem of multi-prior portfolio under the uncertainty about the expected return of risky asset.By introducing a set of constraint constants to measure the uncertainty degree of the expected return,and obtaining the confidence interval of the true expected return,this paper builds the max-min model of multi-prior portfolio, utilizes the Lagrange method to obtain the closed-form solution of the model,and conducts an empirical study based on the eight stock's monthly return data from July 2011 to June 2016 in Shanghai Exchange 50 Index.Results show:the weight of multi-prior portfolio is a weighted average of the weight of mean-variance portfolio and that of minimum-variance portfolio;the performance of multi-prior portfolio is greater than that of minimum-variance portfolio for an appropriate constraint constant;the stability of multi-prior portfolio is strengthened compared with the mean-variance portfolio.The study demonstrates that the multi-prior portfolio can improve the performance of mean-variance portfolio as well as its stability.%基于均值-方差模型,运用多先验方法研究风险资产期望收益具有不确定性下的多先验资产组合优化问题.通过引入一组约束常数测度期望收益的不确定性程度,给出真实期望收益的置信区间,构建多先验资产组合最大-最小化模型,运用拉格朗日法获得模型的最优封闭解,并以上证50指数中8只股票2011年7月到2016年6月的月度收益数据为样本予以实证.结果表明,多先验资产组合权重是均值-方差资产组合权重与最小方差资产组合权重的加权平均;某一适当约束常数下的多先验资产组合的业绩高于均值-方差资产组合;多先验资产组合的稳定性强于均值-方差资产组合.研究指出多先验资产组合不但能提高均值-方差资产组合的业绩,而且也能提升均值-方差资产组合的稳定性.
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