Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/237223 
Erscheinungsjahr: 
2020
Quellenangabe: 
[Journal:] Financial Innovation [ISSN:] 2199-4730 [Volume:] 6 [Issue:] 1 [Publisher:] Springer [Place:] Heidelberg [Year:] 2020 [Pages:] 1-25
Verlag: 
Springer, Heidelberg
Zusammenfassung: 
Text-mining technologies have substantially affected financial industries. As the data in every sector of finance have grown immensely, text mining has emerged as an important field of research in the domain of finance. Therefore, reviewing the recent literature on text-mining applications in finance can be useful for identifying areas for further research. This paper focuses on the text-mining literature related to financial forecasting, banking, and corporate finance. It also analyses the existing literature on text mining in financial applications and provides a summary of some recent studies. Finally, the paper briefly discusses various text-mining methods being applied in the financial domain, the challenges faced in these applications, and the future scope of text mining in finance.
Schlagwörter: 
Text mining
Machine learning
Financial forecasting
Sentiment analysis
Text classification
Corporate finance
Persistent Identifier der Erstveröffentlichung: 
Creative-Commons-Lizenz: 
cc-by Logo
Dokumentart: 
Article

Datei(en):
Datei
Größe
1.08 MB





Publikationen in EconStor sind urheberrechtlich geschützt.