指数跟踪组合复制方法和实证研究

发布时间：2018-04-02 09:44

本文选题：指数跟踪　切入点：FastICA　出处：《华东师范大学》2014年硕士论文

【摘要】：随着证券市场的发展和演变,市场指数体系的建立渐渐趋于完善。指数化投资理念已成为世界范围内的主要投资策略和投资方法之一,作为指数化投资的重要技术,指数跟踪组合复制方法得到了国内外众多学者的关注和研究。但是大部分研究都是以证券收益率为出发点来构造指数跟踪模型,很少会对股票价格的时间序列做研究。在指数跟踪投资组合的成分股的选择方法上,大多数学者采用的是市值排名法、按行业抽样或者简单的随机抽样,这些选股方法都缺乏对股票以及目标指数的历史信息进行充分的挖掘和利用。另外,已有研究基本上都只对一种复制方法进行研究,缺乏对不同跟踪组合复制方法的跟踪效果作系统的比较分析。本文针对以上问题提出了一个新的跟踪组合复制的方法,以价格的时间序列为研究对象,用FastICA方法对股票价格时间序列进行特征提取,根据不同的趋势特征对股票进行聚类分层,充分挖掘股票和目标指数的历史信息。然后提出了基于聚类的Non-negative LARS算法进行选股；最后,对选入的股票按照目标函数优化求解,以此赋予股票不同的权重,从而得到复制跟踪的最优组合。在实证分析部分,本文还对各种指数跟踪组合复制方法进行了多角度的对比,结果显示本文提出的指数跟踪复制方法在样本内的跟踪效果是相对最优的,而且基于ICA的聚类和基于聚类的Non-negative LARS算法也取得了不错的效果；在样本外的短期和中期,该方法也有很好的跟踪效果。另外,在实证分析时还尝试从更大的样本空间挑选股票构造跟踪组合,结果表明从沪深300指数的成分股挑选股票构造的跟踪组合其效果要优于从所有股票中选股构造的跟踪组合,这对指数跟踪技术的一项探索,也是一项有益的尝试,有一定的实际参考价值。
[Abstract]:With the development and evolution of securities market, the establishment of market index system tends to perfect gradually.The concept of indexed investment has become one of the main investment strategies and investment methods in the world. As an important technology of indexed investment, the method of index tracking portfolio replication has been paid attention to and studied by many scholars at home and abroad.In the selection method of index tracking portfolio composition, most scholars use market value ranking method, sampling by industry or simple random sampling.These stock selection methods are short of the historical information of stock and target index.In addition, most of the previous studies focus on only one replication method, which lacks a systematic comparative analysis of the tracking effects of different tracking combinations.In order to solve the above problems, a new method of tracking portfolio replication is proposed in this paper. Taking the time series of price as the research object, the FastICA method is used to extract the features of the time series of stock prices.Then we propose a clustering based Non-negative LARS algorithm for stock selection. Finally, we optimize the stock selection according to the objective function to give different weights to the stock and obtain the optimal combination of replication tracking.In the part of empirical analysis, this paper also makes a multi-angle comparison of various index tracking combination replication methods. The results show that the index tracking replication method proposed in this paper is relatively optimal in the sample tracking effect.Moreover, the clustering algorithm based on ICA and Non-negative LARS algorithm based on clustering have also achieved good results, and the method also has good tracking effect in the short and medium term outside the sample.In addition, in the empirical analysis, we also try to select the stock structure tracking portfolio from a larger sample space.The results show that the tracking combination selected from the constituent stocks of CSI 300 index is more effective than the one from all stocks, which is also a useful attempt to explore the technology of index tracking.It has certain practical reference value.
【学位授予单位】：华东师范大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F832.51;F224

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