指数基金与跟踪误差优化模型

Index Fund and Tracking Error Optimzation Model

本文研究了跟踪误差最小化的两种模型:二次优化模型和线性优化模型。本文认为线性跟踪误差模型能够更加准确地体现投资者对待风险的态度,定位于特定目标。因此,在实践中应该采用绝对偏差最小化来取代偏差的平方最小化的方法。

This article investigates two models for minimizing tracking error:quadratic tracking error optimization and linear tracking error optimization.We argue that linear tracking error model give a more acurate description of the investor's risk attitude and target specific investment objective.Therefore we suggest that absolute deviations are minimized instead of squared deviations.