基于粗糙集和灰色理论的电子行业股票组合选择

IF 1 4区 工程技术 Q4 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
K. Huang, Chuen-Jiuan Jane
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引用次数: 11

摘要

本文说明了粗糙集理论(RS),结合使用灰色预测,GM(1,N), K-means和灰色关联,可以胜过经济学中使用的更标准的方法,如Probit模型。本研究以电子股为研究对象,运用新台湾经济资料库(TEJ)的财务报表资料,选取最优股票组合。首先,我们收集相对财务比率数据作为条件属性选择,然后使用GM(1,1)进行预测,GM(1,N)选择更重要的条件属性,并使用粗糙集计算出最佳投资组合。最后,运用灰色关联法进行基金权重分配,降低投资风险。本研究将证明粗糙集模型适用于股票投资组合。台湾地区的实证结果:2003-2007年5年间,平均年化收益率为20.41%,9个季度累计收益率为61.22%。该模型确定的投资组合是替代传统经济金融预测方法的一种很有前景的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Portfolio Selection of Electron Sector Stock Based on Rough Set and Grey Theory
This paper illustrates that rough set theory (RS), allied with the use of Grey Prediction, GM(1,N), K-means and Grey Relation, can out-perform the more standard approaches that are employed in economics, such as a Probit model. This study focuses on electron sector stock to select the optimal stock portfolio out applying the financial statement datum from the New Taiwan Economy database(TEJ). Firstly, we collect relative financial ratio datum as the conditional attributes selection and then use GM(1,1) for predicting, GM(1,N) for choosing the more important conditional attributes, and rough set for figuring the best portfolio out. Finally, conduct fund weight distribution using the grey relational method to reduce the investment risk. This study will demonstrate that rough sets model is applicable to stock portfolio. The empirical result in Taiwan: During five years (2003-2007), the average annual rate of return was 20.41%, the accumulated rate of return for nine-quarter was 61.22%. The portfolio determined by the model is a promising alternative to the conventional methods for economic and financial prediction.
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来源期刊
Journal of Grey System
Journal of Grey System 数学-数学跨学科应用
CiteScore
2.40
自引率
43.80%
发文量
0
审稿时长
1.5 months
期刊介绍: The journal is a forum of the highest professional quality for both scientists and practitioners to exchange ideas and publish new discoveries on a vast array of topics and issues in grey system. It aims to bring forth anything from either innovative to known theories or practical applications in grey system. It provides everyone opportunities to present, criticize, and discuss their findings and ideas with others. A number of areas of particular interest (but not limited) are listed as follows: Grey mathematics- Generator of Grey Sequences- Grey Incidence Analysis Models- Grey Clustering Evaluation Models- Grey Prediction Models- Grey Decision Making Models- Grey Programming Models- Grey Input and Output Models- Grey Control- Grey Game- Practical Applications.
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