{"title":"预测收益和回报:回顾最近的进展","authors":"Jeremiah Green , Wanjia Zhao","doi":"10.1016/j.jfds.2022.04.004","DOIUrl":null,"url":null,"abstract":"<div><p>We selectively review recent advancements in research on predictive models of earnings and returns. We discuss why applying statistical, econometric, and machine learning advancements to forecasting earnings and returns presents difficult challenges. In the context of these challenges, we discuss recent papers that confront the challenges and present promising advancements and paths for future research.</p></div>","PeriodicalId":36340,"journal":{"name":"Journal of Finance and Data Science","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405918822000046/pdfft?md5=dcf5751ffa50be857ae9e9abd388099e&pid=1-s2.0-S2405918822000046-main.pdf","citationCount":"5","resultStr":"{\"title\":\"Forecasting earnings and returns: A review of recent advancements\",\"authors\":\"Jeremiah Green , Wanjia Zhao\",\"doi\":\"10.1016/j.jfds.2022.04.004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>We selectively review recent advancements in research on predictive models of earnings and returns. We discuss why applying statistical, econometric, and machine learning advancements to forecasting earnings and returns presents difficult challenges. In the context of these challenges, we discuss recent papers that confront the challenges and present promising advancements and paths for future research.</p></div>\",\"PeriodicalId\":36340,\"journal\":{\"name\":\"Journal of Finance and Data Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2405918822000046/pdfft?md5=dcf5751ffa50be857ae9e9abd388099e&pid=1-s2.0-S2405918822000046-main.pdf\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Finance and Data Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2405918822000046\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Finance and Data Science","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2405918822000046","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Mathematics","Score":null,"Total":0}
Forecasting earnings and returns: A review of recent advancements
We selectively review recent advancements in research on predictive models of earnings and returns. We discuss why applying statistical, econometric, and machine learning advancements to forecasting earnings and returns presents difficult challenges. In the context of these challenges, we discuss recent papers that confront the challenges and present promising advancements and paths for future research.