基于Lasso变量选择下两种有偏估计的指数追踪  

A Study on Two Kinds of Index Tracking with Biased Estimation Based on the Lasso Variable Selection

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作  者:卜妤萱 BU Yuxuan(Chongqing Electric Power College,Chongqing 400053,P.R.China)

机构地区:[1]重庆电力高等专科学校,重庆400053

出  处:《重庆电力高等专科学校学报》2023年第4期13-18,47,共7页Journal of Chongqing Electric Power College

摘  要:指数追踪是备受投资者青睐的一种投资方式,怎样构建合理的、追踪误差较小的股票投资组合是研究指数追踪问题的焦点。以上证50指数及其50只成分股的5分钟线的收盘价为研究对象,采用基于Lasso变量选择下2种有偏估计的方法来建立指数追踪模型。研究发现:Lasso与岭估计相结合建立的模型指数追踪效果相对最好,其是最优模型。实证分析表明,该方法对指数型投资者和基金公司有一定的实际意义和参考价值。Index tracking is an method of investment favored by investors.How to construct a reasonable stock portfolio with less tracking error is the focus of research of index tracking.Taking the closing price of Shanghai Stock Exchange 50 Index and its 50 constituent stocks at the 5-minute line as the object of research,two biased estimation methods based on the Lasso variable are selected to establish the index tracking model.It is concluded that the index tracking effect of the model established by combining the Lasso and the Ridge estimation is relatively best,and it is the optimal model.The empirical analysis shows that this method has certain practical significance and reference value for index investors and fund companies.

关 键 词:指数追踪 Lasso 有偏估计 岭估计 主成分估计 

分 类 号:F224[经济管理—国民经济] F832.51

 

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