{"title":"股票市场预测智能范式的集成模型","authors":"Qiang Wu, Yuehui Chen, Z. Liu","doi":"10.1109/WKDD.2008.54","DOIUrl":null,"url":null,"abstract":"The use of intelligent systems for stock market predictions has been widely established. This paper introduces a ensemble model of SVM and ANNs for the prediction of three stock indices. The performance of this model is then compared with support vector machine model and an artificial neural network respectively. Empirical results reveal that the ensemble result obtain the best results.","PeriodicalId":101656,"journal":{"name":"First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Ensemble Model of Intelligent Paradigms for Stock Market Forecasting\",\"authors\":\"Qiang Wu, Yuehui Chen, Z. Liu\",\"doi\":\"10.1109/WKDD.2008.54\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The use of intelligent systems for stock market predictions has been widely established. This paper introduces a ensemble model of SVM and ANNs for the prediction of three stock indices. The performance of this model is then compared with support vector machine model and an artificial neural network respectively. Empirical results reveal that the ensemble result obtain the best results.\",\"PeriodicalId\":101656,\"journal\":{\"name\":\"First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-01-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WKDD.2008.54\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WKDD.2008.54","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Ensemble Model of Intelligent Paradigms for Stock Market Forecasting
The use of intelligent systems for stock market predictions has been widely established. This paper introduces a ensemble model of SVM and ANNs for the prediction of three stock indices. The performance of this model is then compared with support vector machine model and an artificial neural network respectively. Empirical results reveal that the ensemble result obtain the best results.