This article reviews the literature on artificial neural networks (ANNs) applied to accounting and finance problems and summarizes the 'suggestions' from this literature. The first section reviews the basic foundation of ANNs to provide a common basis for further elaboration and suggests criteria that should be used to determine whether the use of an ANN is appropriate. The second section of the paper discusses development of ANN models including: selection of the learning algorithm, choice of the error and transfer functions, specification of the architecture, preparation of the data to match the architecture, and training of the network The final section presents some general guidelines and a brief summary of research progress and open research questions. [ABSTRACT FROM AUTHOR] Copyright of International Journal of Intelligent Systems in Accounting Finance & Management is the property of John Wiley & Sons, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
CITATION STYLE
Coakley, J. R., & Brown, C. E. (2000). Artificial neural networks in accounting and finance: modeling issues. International Journal of Intelligent Systems in Accounting, Finance & Management, 9(2), 119–144. https://doi.org/10.1002/1099-1174(200006)9:2<119::aid-isaf182>3.0.co;2-y
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