基于两种回归的指数追踪模型以及实证分析

Index Tracking Model Based on Two Regressions and Empirical Analysis

摘要: 指数追踪是一种用少量的成分股来追踪某一市场指数走势的方法，它是消极投资组合管理策略中的一种，近年来在我国发展迅速。本文通过三种选股方法选出三个样本股空间，并构建了基于线性回归的指数追踪模型，为了避免线性回归的系数受到极端值的影响，本文还建立了基于分位数回归的指数追踪模型。具体来说，本文选取了上证50指数为目标指数，通过给出建立指数追踪模型的约束条件，再构建两个指数追踪模型，最后分别通过最大权重选股法、最大市值选股法以及最大相关系数选股法对上证50指数的成分股进行选股，选取每种选股法的前15只股票作为样本股空间，最后通过对真实数据的拟合来对选定的成分股分配权重。

Abstract: Index tracking is a method of tracking the trend of a certain market index with a small number of constituent stocks. It is one of the negative portfolio management strategies and has developed rapidly in China in recent years. In this paper, three sample stocks are selected by three stock selection methods, and an exponential tracking model based on linear regression is constructed. In order to avoid the linear regression coefficient being affected by extreme values, this paper also establishes index tracking based on quantile regression model. Specifically, this paper selects the SSE 50 Index as the target index, and establishes two index tracking models by giving the constraints of establishing the index tracking model, and finally passes the maximum weight stock selection method, the maximum market value selection method and the maximum correlation. The coefficient stock selection method selects stocks of the SSE 50 index, selects the first 15 stocks of each stock picking method as the sample stock space, and finally assigns weights to the selected constituent stocks by fitting the real data.