{"title":"基于粗糙集和灰色理论的电子行业股票组合选择","authors":"K. Huang, Chuen-Jiuan Jane","doi":"10.30016/JGS.200712.0007","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":50187,"journal":{"name":"Journal of Grey System","volume":"10 1","pages":"183-192"},"PeriodicalIF":1.0000,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Portfolio Selection of Electron Sector Stock Based on Rough Set and Grey Theory\",\"authors\":\"K. Huang, Chuen-Jiuan Jane\",\"doi\":\"10.30016/JGS.200712.0007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":50187,\"journal\":{\"name\":\"Journal of Grey System\",\"volume\":\"10 1\",\"pages\":\"183-192\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2007-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Grey System\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.30016/JGS.200712.0007\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Grey System","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.30016/JGS.200712.0007","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
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.
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.