Journal article
On the predictive ability of narrative disclosures in annual reports
European journal of operational research, Vol.202(3), pp.789-801
2010
DOI: 10.1016/j.ejor.2009.06.023
Abstract
We investigate whether narrative disclosures in 10-K and 10K-405 filings contain value-relevant information for predicting market performance. We apply text classification techniques from computer science to machine code text disclosures in a sample of 4280 filings by 1236 firms over five years. Our methodology develops a model using documents and actual performance for a training sample. This model, when applied to documents from a test set, leads to performance prediction. We find that a portfolio based on model predictions earns significantly positive size-adjusted returns, indicating that narrative disclosures contain value-relevant information. Supplementary analyses show that the text classification model captures information not contained in document-level features of clarity, tone and risk sentiment considered in prior research. However, we find that the narrative score is not providing information incremental to traditional predictors such as size, market-to-book and momentum, but rather affects investors’ use of price momentum as a factor that predicts excess returns.
Details
- Title: Subtitle
- On the predictive ability of narrative disclosures in annual reports
- Creators
- Ramji Balakrishnan - The University of Iowa, Tippie College of Business, Iowa City, IA 52246, USAXin Ying Qiu - Christopher Newport University, Luter School of Business, Newport News, VA 23606, USAPadmini Srinivasan - The University of Iowa, Computer Science Department and Tippie College of Business, Iowa City, IA 52246, USA
- Resource Type
- Journal article
- Publication Details
- European journal of operational research, Vol.202(3), pp.789-801
- Publisher
- Elsevier B.V
- DOI
- 10.1016/j.ejor.2009.06.023
- ISSN
- 0377-2217
- eISSN
- 1872-6860
- Language
- English
- Date published
- 2010
- Academic Unit
- Nursing; Computer Science; Business Analytics; Accounting
- Record Identifier
- 9984003182902771
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