稀疏超越指数追踪的分位数回归模型及其算法

Sparse Enhanced Indexation Tracking Model Based on Quantile Regression and Its Algorithm

针对超越指数追踪基金管理问题,建立稀疏超越指数追踪的分位数回归模型及其求解算法——HSS-Half阈值算法.利用OR-Library的四个市场指数历史数据进行实证分析.实证分析表明该模型比最小二乘模型具有更高的稳定性和超额收益能力,同时也降低了投资风险.

Aiming at the problem of enhanced indexation tracking fund management,we propose a sparse enhanced indexation tracking model based on quantile regression and its solution algorithm i.e.HSS-Half threshold algorithm.Empirical tests are conducted using four index historical data from OR-Library.The empirical analysis shows that the model has higher stability and excess return of out-of-sample capacity than the least square model,it also reduces investment risk.