About: Forecasting corporate financial performance using sentiment in annual reports for stakeholders' decision-making

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	This paper is aimed at examining the role of annual reports' sentiment in forecasting financial performance. The sentiment (tone, opinion) is assessed using several categorization schemes in order to explore various aspects of language used in the annual reports of U.S. companies. Further, we employ machine learning methods and neural networks to predict financial performance expressed in terms of the Z-score bankruptcy model. Eleven categories of sentiment (ranging from negative and positive to active and common) are used as the inputs of the prediction models. Support vector machines provide the highest forecasting accuracy. This evidence suggests that there exist non-linear relationships between the sentiment and financial performance. The results indicate that the sentiment information is an important forecasting determinant of financial performance and, thus, can be used to support decision-making process of corporate stakeholders. This paper is aimed at examining the role of annual reports' sentiment in forecasting financial performance. The sentiment (tone, opinion) is assessed using several categorization schemes in order to explore various aspects of language used in the annual reports of U.S. companies. Further, we employ machine learning methods and neural networks to predict financial performance expressed in terms of the Z-score bankruptcy model. Eleven categories of sentiment (ranging from negative and positive to active and common) are used as the inputs of the prediction models. Support vector machines provide the highest forecasting accuracy. This evidence suggests that there exist non-linear relationships between the sentiment and financial performance. The results indicate that the sentiment information is an important forecasting determinant of financial performance and, thus, can be used to support decision-making process of corporate stakeholders. (en)
Title	Forecasting corporate financial performance using sentiment in annual reports for stakeholders' decision-making Forecasting corporate financial performance using sentiment in annual reports for stakeholders' decision-making (en)
skos:prefLabel	Forecasting corporate financial performance using sentiment in annual reports for stakeholders' decision-making Forecasting corporate financial performance using sentiment in annual reports for stakeholders' decision-making (en)
skos:notation	RIV/00216275:25410/14:39898554!RIV15-GA0-25410___
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(GA13-10331S)
http://linked.open...iv/cisloPeriodika	4
http://linked.open...vai/riv/dodaniDat	2015
http://linked.open...aciTvurceVysledku	Hájek, Petr Olej, Vladimír Myšková, Renáta
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Univerzita Pardubice / Fakulta ekonomicko-správní
http://linked.open...dnocenehoVysledku	17189
http://linked.open...ai/riv/idVysledku	RIV/00216275:25410/14:39898554
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	opinion mining; sentiment analysis; annual reports; bankruptcy forecasting; financial distress; financial performance (en)
http://linked.open.../riv/klicoveSlovo	sentiment analysis financial performance annual reports financial distress opinion mining bankruptcy forecasting
http://linked.open...odStatuVydavatele	LT - Litevská republika
http://linked.open...ontrolniKodProRIV	[B81ED4DF9FC2]
http://linked.open...i/riv/nazevZdroje	Technological and Economic Development of Economy
http://linked.open...in/vavai/riv/obor	AE
http://linked.open...ichTvurcuVysledku	3 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	The role of text information in corporate financial distress prediction models – country-specific and industry-specific approaches
http://linked.open...UplatneniVysledku	2014
http://linked.open...v/svazekPeriodika	20
http://linked.open...iv/tvurceVysledku	Hájek, Petr Myšková, Renáta Olej, Vladimír
http://linked.open...ain/vavai/riv/wos	000346354400006
issn	2029-4913
number of pages	18 (xsd:int)
http://bibframe.org/vocab/doi	10.3846/20294913.2014.979456
http://localhost/t...ganizacniJednotka	25410

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