Natural language based financial forecasting: a survey
Natural language processing (NLP), or the pragmatic research perspective of computational linguistics, has become increasingly powerful due to data availability and various techniques developed in the past decade. This increasing capability makes it possible to capture sentiments more accurately and...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
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Springer Netherlands
2018
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| Online Access: | http://hdl.handle.net/1721.1/116314 https://orcid.org/0000-0002-9038-1622 |
| _version_ | 1826205472758169600 |
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| author | Cambria, Erik Xing, Frank Z. Welsch, Roy E |
| author2 | Sloan School of Management |
| author_facet | Sloan School of Management Cambria, Erik Xing, Frank Z. Welsch, Roy E |
| author_sort | Cambria, Erik |
| collection | MIT |
| description | Natural language processing (NLP), or the pragmatic research perspective of computational linguistics, has become increasingly powerful due to data availability and various techniques developed in the past decade. This increasing capability makes it possible to capture sentiments more accurately and semantics in a more nuanced way. Naturally, many applications are starting to seek improvements by adopting cutting-edge NLP techniques. Financial forecasting is no exception. As a result, articles that leverage NLP techniques to predict financial markets are fast accumulating, gradually establishing the research field of natural language based financial forecasting (NLFF), or from the application perspective, stock market prediction. This review article clarifies the scope of NLFF research by ordering and structuring techniques and applications from related work. The survey also aims to increase the understanding of progress and hotspots in NLFF, and bring about discussions across many different disciplines. Keywords: Financial forecasting, Natural language processing, Text mining Predictive analytics, Knowledge engineering , Computational finance |
| first_indexed | 2024-09-23T13:13:58Z |
| format | Article |
| id | mit-1721.1/116314 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T13:13:58Z |
| publishDate | 2018 |
| publisher | Springer Netherlands |
| record_format | dspace |
| spelling | mit-1721.1/1163142022-10-01T13:53:53Z Natural language based financial forecasting: a survey Cambria, Erik Xing, Frank Z. Welsch, Roy E Sloan School of Management Welsch, Roy E Natural language processing (NLP), or the pragmatic research perspective of computational linguistics, has become increasingly powerful due to data availability and various techniques developed in the past decade. This increasing capability makes it possible to capture sentiments more accurately and semantics in a more nuanced way. Naturally, many applications are starting to seek improvements by adopting cutting-edge NLP techniques. Financial forecasting is no exception. As a result, articles that leverage NLP techniques to predict financial markets are fast accumulating, gradually establishing the research field of natural language based financial forecasting (NLFF), or from the application perspective, stock market prediction. This review article clarifies the scope of NLFF research by ordering and structuring techniques and applications from related work. The survey also aims to increase the understanding of progress and hotspots in NLFF, and bring about discussions across many different disciplines. Keywords: Financial forecasting, Natural language processing, Text mining Predictive analytics, Knowledge engineering , Computational finance 2018-06-14T16:58:47Z 2018-08-05T05:00:07Z 2017-10 2017-04 2018-05-10T03:51:49Z Article http://purl.org/eprint/type/JournalArticle 0269-2821 1573-7462 http://hdl.handle.net/1721.1/116314 Xing, Frank Z., et al. “Natural Language Based Financial Forecasting: A Survey.” Artificial Intelligence Review, vol. 50, no. 1, June 2018, pp. 49–73. https://orcid.org/0000-0002-9038-1622 en https://doi.org/10.1007/s10462-017-9588-9 Artificial Intelligence Review Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ Springer Science+Business Media B.V. application/pdf Springer Netherlands Springer Netherlands |
| spellingShingle | Cambria, Erik Xing, Frank Z. Welsch, Roy E Natural language based financial forecasting: a survey |
| title | Natural language based financial forecasting: a survey |
| title_full | Natural language based financial forecasting: a survey |
| title_fullStr | Natural language based financial forecasting: a survey |
| title_full_unstemmed | Natural language based financial forecasting: a survey |
| title_short | Natural language based financial forecasting: a survey |
| title_sort | natural language based financial forecasting a survey |
| url | http://hdl.handle.net/1721.1/116314 https://orcid.org/0000-0002-9038-1622 |
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