{"title":"人工智能革命:从线性回归到ChatGPT及其他,以及它如何与金融联系","authors":"Irene E. Aldridge","doi":"10.3905/jpm.2023.1.519","DOIUrl":null,"url":null,"abstract":"This article surveys the evolution of machine learning from linear regression through ChatGPT to fully unsupervised learning. We illustrate the advantages of artificial intelligence (AI) over traditional methods with simple intuitive examples for the US equities markets. We also show that the AI inferences are consistent with classical finance models, such as the capital asset pricing model. We also describe how, unlike machine learning, true AI unsupervised models satisfy the optimal modeling characteristics. Most importantly, we show step by step how AI identifies and extracts signals from data.","PeriodicalId":53670,"journal":{"name":"Journal of Portfolio Management","volume":"49 1","pages":"64 - 77"},"PeriodicalIF":1.1000,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The AI Revolution: From Linear Regression to ChatGPT and beyond and How It All Connects to Finance\",\"authors\":\"Irene E. Aldridge\",\"doi\":\"10.3905/jpm.2023.1.519\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article surveys the evolution of machine learning from linear regression through ChatGPT to fully unsupervised learning. We illustrate the advantages of artificial intelligence (AI) over traditional methods with simple intuitive examples for the US equities markets. We also show that the AI inferences are consistent with classical finance models, such as the capital asset pricing model. We also describe how, unlike machine learning, true AI unsupervised models satisfy the optimal modeling characteristics. Most importantly, we show step by step how AI identifies and extracts signals from data.\",\"PeriodicalId\":53670,\"journal\":{\"name\":\"Journal of Portfolio Management\",\"volume\":\"49 1\",\"pages\":\"64 - 77\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2023-07-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Portfolio Management\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.3905/jpm.2023.1.519\",\"RegionNum\":4,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Portfolio Management","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.3905/jpm.2023.1.519","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
The AI Revolution: From Linear Regression to ChatGPT and beyond and How It All Connects to Finance
This article surveys the evolution of machine learning from linear regression through ChatGPT to fully unsupervised learning. We illustrate the advantages of artificial intelligence (AI) over traditional methods with simple intuitive examples for the US equities markets. We also show that the AI inferences are consistent with classical finance models, such as the capital asset pricing model. We also describe how, unlike machine learning, true AI unsupervised models satisfy the optimal modeling characteristics. Most importantly, we show step by step how AI identifies and extracts signals from data.
期刊介绍:
Founded by Peter Bernstein in 1974, The Journal of Portfolio Management (JPM) is the definitive source of thought-provoking analysis and practical techniques in institutional investing. It offers cutting-edge research on asset allocation, performance measurement, market trends, risk management, portfolio optimization, and more. Each quarterly issue of JPM features articles by the most renowned researchers and practitioners—including Nobel laureates—whose works define modern portfolio theory.