{"title":"检测印度股市的内幕交易:优化的深度学习方法","authors":"Prashant Priyadarshi, Prabhat Kumar","doi":"10.1007/s10614-024-10697-z","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":50647,"journal":{"name":"Computational Economics","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Detecting Insider Trading in the Indian Stock Market: An Optimized Deep Learning Approach\",\"authors\":\"Prashant Priyadarshi, Prabhat Kumar\",\"doi\":\"10.1007/s10614-024-10697-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":50647,\"journal\":{\"name\":\"Computational Economics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2024-08-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational Economics\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.1007/s10614-024-10697-z\",\"RegionNum\":4,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Economics","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1007/s10614-024-10697-z","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
期刊介绍:
Computational Economics, the official journal of the Society for Computational Economics, presents new research in a rapidly growing multidisciplinary field that uses advanced computing capabilities to understand and solve complex problems from all branches in economics. The topics of Computational Economics include computational methods in econometrics like filtering, bayesian and non-parametric approaches, markov processes and monte carlo simulation; agent based methods, machine learning, evolutionary algorithms, (neural) network modeling; computational aspects of dynamic systems, optimization, optimal control, games, equilibrium modeling; hardware and software developments, modeling languages, interfaces, symbolic processing, distributed and parallel processing