Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/237223 
Year of Publication: 
2020
Citation: 
[Journal:] Financial Innovation [ISSN:] 2199-4730 [Volume:] 6 [Issue:] 1 [Publisher:] Springer [Place:] Heidelberg [Year:] 2020 [Pages:] 1-25
Publisher: 
Springer, Heidelberg
Abstract: 
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.
Subjects: 
Text mining
Machine learning
Financial forecasting
Sentiment analysis
Text classification
Corporate finance
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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