{"title":"人工智能方法应用于低(日内)和极低(高频)时间框架交易环境中的金融资产价格预测","authors":"Donata Petrelli, Fabrizio Cesarini","doi":"10.1002/JSC.2407","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":46986,"journal":{"name":"Strategic Change-Briefings in Entrepreneurial Finance","volume":null,"pages":null},"PeriodicalIF":3.6000,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/JSC.2407","citationCount":"4","resultStr":"{\"title\":\"Artificial intelligence methods applied to financial assets price forecasting in trading contexts with low (intraday) and very low (high‐frequency) time frames\",\"authors\":\"Donata Petrelli, Fabrizio Cesarini\",\"doi\":\"10.1002/JSC.2407\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":46986,\"journal\":{\"name\":\"Strategic Change-Briefings in Entrepreneurial Finance\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2021-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1002/JSC.2407\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Strategic Change-Briefings in Entrepreneurial Finance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/JSC.2407\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Strategic Change-Briefings in Entrepreneurial Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/JSC.2407","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
Artificial intelligence methods applied to financial assets price forecasting in trading contexts with low (intraday) and very low (high‐frequency) time frames