CAJ | 학술논문

本文研究了指数型基金管理中最核心的指数追踪问题.依据结构风险最小化思想,首先构造了以追踪误差为基础的损失函数,接着考虑了时间因素对历史追踪误差的影响,采用指数加权的方法将时间因素纳入追踪误差的分析中,利用SVM理论给出了指数复制问题的结构风险的形式,在此基础上构建了各种市场实际约束下最小化结构风险的时间加权SVM的指数优化复制模型,最后利用OR-Library中的5个市场指数历史数据进行了实证检验.结果表明本文提出的时间加权SVM模型能够显著提高样本外的追踪效果.同时使得追踪组合的鲁棒性有明显的改善,从而表明本文提出的时间加权SVM指数复制模型具有较高的理论和应用价值.
본문연구료지수형기금관리중최핵심적지수추종문제.의거결구풍험최소화사상,수선구조료이추종오차위기출적손실함수,접착고필료시간인소대역사추종오차적영향,채용지수가권적방법장시간인소납입추종오차적분석중,이용SVM이론급출료지수복제문제적결구풍험적형식,재차기출상구건료각충시장실제약속하최소화결구풍험적시간가권SVM적지수우화복제모형,최후이용OR-Library중적5개시장지수역사수거진행료실증검험.결과표명본문제출적시간가권SVM모형능구현저제고양본외적추종효과.동시사득추종조합적로봉성유명현적개선,종이표명본문제출적시간가권SVM지수복제모형구유교고적이론화응용개치.
In this paper,we study the index tracking problem which plays core role in index fund management.According to minimizing structure risk,a loss function based on tracking error is constructed firstly,then time is considered in history tracking error,and exponential weighted method is used to handle it,so the structure risk is proposed on the basis of SVM,a model is generated to deal with index tracking problem by minimizing structure risk constrained some real market conditions,lastly,some empirical tests are conducted using five index historical data from OR-Library.The numerical results show that our model can improve the out-of-sample performance,at the same time,the robust of the tracking portfolio is improved evidently,thus it has good theoretical and applied value.