摘要
已有的业绩评价指标多依据一个或多个历史统计数据,往往忽视直觉与数据分析相结合。而将贝叶斯统计推断理论引入证券投资基金业绩评价过程,却能很好地将二者结合起来。该方法首先建立关于管理技能的灵活的先验信念集合,并将这些先验信念与一般多因素模型相结合,进而推导出模型中的截距项--α的后验期望代数解。这为证券投资基金业绩评价提供了一个崭新的视角。
The existing performance evaluation indexes are mostly based on one or more historical statistical data, and the combination of intuition with data analysis is often ignored. To tackle this problem, this thesis introduces the theory of Bayesian Statistical Inference into the performance evaluation procedure for securities investment funds. We begin with a flexible set of prior beliefs about managerial skill that can be elicited without any reference to probability distribution or their parameters. We then combine these prior beliefs with a general multi-factor model and derive an analytical solution for the posterior expectation of alpha, the intercept term from the model. Finally, we apply our methodology to a sample of domestic securities investment funds and conduct a practical analysis.
出处
《西南交通大学学报（社会科学版）》
2004年第6期85-88,共4页
Journal of Southwest Jiaotong University(Social Sciences)
关键词
贝叶斯
业绩评价指标
证券投资基金
投资理论
<Keyword>Bayesian
securities investment funds
performance evaluation
