Predicting future earnings change using numeric and textual information in financial reports

Kuo Tay Chen; Tsai Jyh Chen; Ju Chun Yen

doi:10.1007/978-3-642-01393-5_7

Predicting future earnings change using numeric and textual information in financial reports

Kuo Tay Chen, Tsai Jyh Chen, Ju Chun Yen

Graduate Institute of Accounting

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

The main propose of this study is to build a more powerful earning prediction model by incorporating risk information disclosed in the textual portion of financial reports. We adopt the single-index model developed by Weiss, Naik and Tsai as a foundation. However, other than the traditionally used numeric financial information, our model adds textual information about risk sentiment contained in financial reports. We believe such a model can reduce specification errors resulting from pre-assuming linear relationship, thus can predict future earnings more accurately. The empirical results show that the modified model does significantly improve the accuracy of earning prediction.

Original language	English
Title of host publication	Intelligence and Security Informatics - Pacific Asia Workshop, PAISI 2009, Proceedings
Pages	54-63
Number of pages	10
DOIs	https://doi.org/10.1007/978-3-642-01393-5_7
State	Published - 2009
Event	Pacific Asia Workshop on Intelligence and Security Informatics, PAISI 2009 - Bangkok, Thailand Duration: 27 Apr 2009 → 27 Apr 2009

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5477
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	Pacific Asia Workshop on Intelligence and Security Informatics, PAISI 2009
Country/Territory	Thailand
City	Bangkok
Period	27/04/09 → 27/04/09

Keywords

Earnings prediction
Risk sentiment
Single-index model
Textual information

Access to Document

10.1007/978-3-642-01393-5_7

Cite this

Chen, K. T., Chen, T. J., & Yen, J. C. (2009). Predicting future earnings change using numeric and textual information in financial reports. In Intelligence and Security Informatics - Pacific Asia Workshop, PAISI 2009, Proceedings (pp. 54-63). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5477). https://doi.org/10.1007/978-3-642-01393-5_7

Chen, Kuo Tay ; Chen, Tsai Jyh ; Yen, Ju Chun. / Predicting future earnings change using numeric and textual information in financial reports. Intelligence and Security Informatics - Pacific Asia Workshop, PAISI 2009, Proceedings. 2009. pp. 54-63 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "The main propose of this study is to build a more powerful earning prediction model by incorporating risk information disclosed in the textual portion of financial reports. We adopt the single-index model developed by Weiss, Naik and Tsai as a foundation. However, other than the traditionally used numeric financial information, our model adds textual information about risk sentiment contained in financial reports. We believe such a model can reduce specification errors resulting from pre-assuming linear relationship, thus can predict future earnings more accurately. The empirical results show that the modified model does significantly improve the accuracy of earning prediction.",

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Chen, KT, Chen, TJ & Yen, JC 2009, Predicting future earnings change using numeric and textual information in financial reports. in Intelligence and Security Informatics - Pacific Asia Workshop, PAISI 2009, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5477, pp. 54-63, Pacific Asia Workshop on Intelligence and Security Informatics, PAISI 2009, Bangkok, Thailand, 27/04/09. https://doi.org/10.1007/978-3-642-01393-5_7

Predicting future earnings change using numeric and textual information in financial reports. / Chen, Kuo Tay; Chen, Tsai Jyh; Yen, Ju Chun.

Intelligence and Security Informatics - Pacific Asia Workshop, PAISI 2009, Proceedings. 2009. p. 54-63 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5477).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - The main propose of this study is to build a more powerful earning prediction model by incorporating risk information disclosed in the textual portion of financial reports. We adopt the single-index model developed by Weiss, Naik and Tsai as a foundation. However, other than the traditionally used numeric financial information, our model adds textual information about risk sentiment contained in financial reports. We believe such a model can reduce specification errors resulting from pre-assuming linear relationship, thus can predict future earnings more accurately. The empirical results show that the modified model does significantly improve the accuracy of earning prediction.

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Chen KT, Chen TJ, Yen JC. Predicting future earnings change using numeric and textual information in financial reports. In Intelligence and Security Informatics - Pacific Asia Workshop, PAISI 2009, Proceedings. 2009. p. 54-63. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-01393-5_7

Predicting future earnings change using numeric and textual information in financial reports

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