Good Debt or Bad Debt: Detecting Semantic Orientations in Economic Texts
Download full text from publisher
Other versions of this item:
- Pekka Malo & Ankur Sinha & Pekka Korhonen & Jyrki Wallenius & Pyry Takala, 2014. "Good debt or bad debt: Detecting semantic orientations in economic texts," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(4), pages 782-796, April.
References listed on IDEAS
- Nutz, Marcel & van Handel, Ramon, 2013. "Constructing sublinear expectations on path space," Stochastic Processes and their Applications, Elsevier, vol. 123(8), pages 3100-3121.
- Bruno Bouchard & Marcel Nutz, 2011. "Weak Dynamic Programming for Generalized State Constraints," Papers 1105.0745, arXiv.org, revised Oct 2012.
- Marcel Nutz, 2010. "Random G-expectations," Papers 1009.2168, arXiv.org, revised Sep 2013.
- Marcel Nutz & Ramon van Handel, 2012. "Constructing Sublinear Expectations on Path Space," Papers 1205.2415, arXiv.org, revised Apr 2013.
- (**), Hui Wang & Jaksa Cvitanic & (*), Walter Schachermayer, 2001. "Utility maximization in incomplete markets with random endowment," Finance and Stochastics, Springer, vol. 5(2), pages 259-272.
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Paola Cerchiello & Giancarlo Nicola, 2017. "Assessing News Contagion in Finance," DEM Working Papers Series 139, University of Pavia, Department of Economics and Management.
- Paola Cerchiello & Giancarlo Nicola & Samuel Rönnqvist & Peter Sarlin, 2017. "Deep Learning Bank Distress from News and Numerical Financial Data," DEM Working Papers Series 140, University of Pavia, Department of Economics and Management.
- Samuel Ronnqvist & Peter Sarlin, 2016. "Bank distress in the news: Describing events through deep learning," Papers 1603.05670, arXiv.org, revised Dec 2016.
More about this item
NEP fieldsThis paper has been announced in the following NEP Reports:
StatisticsAccess and download statistics
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1307.5336. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (arXiv administrators). General contact details of provider: http://arxiv.org/ .
We have no references for this item. You can help adding them by using this form .