{"title":"利用深度学习探索伊斯坦布尔证券交易所的情绪","authors":"Alev Atak","doi":"10.1016/j.bir.2023.12.010","DOIUrl":null,"url":null,"abstract":"<p>Sentiment analysis holds immense importance in finance and economics, addressing crucial issues such as principal–agent dynamics and information imbalances. The rise of natural language processing signifies a groundbreaking era in sentiment analysis, enabling the effective extraction of insights from textual data. Our research investigates the impact of qualitative financial data on firm valuation, utilizing sentiment extracted from annual financial disclosures, focusing on companies listed on the Borsa Istanbul Stock Exchange from 1998 to 2022. Employing a pre-trained transformer model, we develop sentiment indices and integrate textual data using a system-generalized method of moments. Our study aims to uncover how sentiment expressed in financial disclosures aids in mitigating challenges related to asymmetric information.</p>","PeriodicalId":46690,"journal":{"name":"Borsa Istanbul Review","volume":null,"pages":null},"PeriodicalIF":6.3000,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Exploring the sentiment in Borsa Istanbul with deep learning\",\"authors\":\"Alev Atak\",\"doi\":\"10.1016/j.bir.2023.12.010\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Sentiment analysis holds immense importance in finance and economics, addressing crucial issues such as principal–agent dynamics and information imbalances. The rise of natural language processing signifies a groundbreaking era in sentiment analysis, enabling the effective extraction of insights from textual data. Our research investigates the impact of qualitative financial data on firm valuation, utilizing sentiment extracted from annual financial disclosures, focusing on companies listed on the Borsa Istanbul Stock Exchange from 1998 to 2022. Employing a pre-trained transformer model, we develop sentiment indices and integrate textual data using a system-generalized method of moments. Our study aims to uncover how sentiment expressed in financial disclosures aids in mitigating challenges related to asymmetric information.</p>\",\"PeriodicalId\":46690,\"journal\":{\"name\":\"Borsa Istanbul Review\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.3000,\"publicationDate\":\"2024-01-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Borsa Istanbul Review\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.1016/j.bir.2023.12.010\",\"RegionNum\":2,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Borsa Istanbul Review","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1016/j.bir.2023.12.010","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
Exploring the sentiment in Borsa Istanbul with deep learning
Sentiment analysis holds immense importance in finance and economics, addressing crucial issues such as principal–agent dynamics and information imbalances. The rise of natural language processing signifies a groundbreaking era in sentiment analysis, enabling the effective extraction of insights from textual data. Our research investigates the impact of qualitative financial data on firm valuation, utilizing sentiment extracted from annual financial disclosures, focusing on companies listed on the Borsa Istanbul Stock Exchange from 1998 to 2022. Employing a pre-trained transformer model, we develop sentiment indices and integrate textual data using a system-generalized method of moments. Our study aims to uncover how sentiment expressed in financial disclosures aids in mitigating challenges related to asymmetric information.
期刊介绍：
Peer Review under the responsibility of Borsa İstanbul Anonim Sirketi. Borsa İstanbul Review provides a scholarly platform for empirical financial studies including but not limited to financial markets and institutions, financial economics, investor behavior, financial centers and market structures, corporate finance, recent economic and financial trends. Micro and macro data applications and comparative studies are welcome. Country coverage includes advanced, emerging and developing economies. In particular, we would like to publish empirical papers with significant policy implications and encourage submissions in the following areas: Research Topics: • Investments and Portfolio Management • Behavioral Finance • Financial Markets and Institutions • Market Microstructure • Islamic Finance • Financial Risk Management • Valuation • Capital Markets Governance • Financial Regulations
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