{"title":"基于深度神经网络的股票市场趋势预测与投资策略","authors":"Mingze Shi, Qiangfu Zhao","doi":"10.1109/iCAST51195.2020.9319488","DOIUrl":null,"url":null,"abstract":"This research is mainly about the prediction of the price change in the stock market. Instead of daily change, this paper analyzes the trend of price change for weeks by judging turning points. Deep neural networks will be used as the classifier of true and fake golden crosses to judge the growth trend of price change. Most stocks on the sample list have positive profits after simulated trading of 10 years. Based on the results we may conclude that deep neural networks are helpful to assist users positively for stock investment.","PeriodicalId":212570,"journal":{"name":"2020 11th International Conference on Awareness Science and Technology (iCAST)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Stock Market Trend Prediction and Investment Strategy by Deep Neural Networks\",\"authors\":\"Mingze Shi, Qiangfu Zhao\",\"doi\":\"10.1109/iCAST51195.2020.9319488\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research is mainly about the prediction of the price change in the stock market. Instead of daily change, this paper analyzes the trend of price change for weeks by judging turning points. Deep neural networks will be used as the classifier of true and fake golden crosses to judge the growth trend of price change. Most stocks on the sample list have positive profits after simulated trading of 10 years. Based on the results we may conclude that deep neural networks are helpful to assist users positively for stock investment.\",\"PeriodicalId\":212570,\"journal\":{\"name\":\"2020 11th International Conference on Awareness Science and Technology (iCAST)\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 11th International Conference on Awareness Science and Technology (iCAST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/iCAST51195.2020.9319488\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 11th International Conference on Awareness Science and Technology (iCAST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iCAST51195.2020.9319488","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Stock Market Trend Prediction and Investment Strategy by Deep Neural Networks
This research is mainly about the prediction of the price change in the stock market. Instead of daily change, this paper analyzes the trend of price change for weeks by judging turning points. Deep neural networks will be used as the classifier of true and fake golden crosses to judge the growth trend of price change. Most stocks on the sample list have positive profits after simulated trading of 10 years. Based on the results we may conclude that deep neural networks are helpful to assist users positively for stock investment.