Please use this identifier to cite or link to this item:
http://hdl.handle.net/10071/29448| Author(s): | Trigueiros, D. Berry, R. H. |
| Editor: | Robert R Trippi Efraim Turban |
| Date: | 1993 |
| Title: | Applying neural networks to the extraction of knowledge from accounting reports: A classification study |
| Book title/volume: | Neural networks in finance and investing: Using artificial intelligence to improve real-world performance |
| Pages: | 103 - 123 |
| Reference: | Trigueiros, D., & Berry, R. H. (1993). Applying neural networks to the extraction of knowledge from accounting reports: A classification study. Em R. R Trippi, & E. Turban (Eds.). Neural networks in finance and investing: Using artificial intelligence to improve real-world performance (pp. 103-123). Probus. http://hdl.handle.net/10071/29448 |
| ISBN: | 9781557384522 |
| Keywords: | Neural networks Financial modelling Predictors selection |
| Abstract: | This study develops a new approach to the problem of extracting meaningful information from samples of accounting reports. Neural networks are shown to be capable of building structures similar to financial ratios, which are optimal in the context of the particular problem being dealt with. This approach removes the need for an analyst to search for appropriate ratios before model building can begin. |
| Peerreviewed: | yes |
| Access type: | Open Access |
| Appears in Collections: | ISTAR-CLI - Capítulos de livros internacionais |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| bookPart_34151.pdf | 853,04 kB | Adobe PDF | View/Open |
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