Using Artificial Neural Networks (ANNs) to Investigate the Usefulness of Accounting Information in the Egyptian Settings

AAA AIS-SET Mid-Year Meeting, 2010

Posted: 14 Nov 2009 Last revised: 14 Jan 2010

Date Written: November 12, 2009

Abstract

The main objective of this study is to investigate the usefulness of accounting information in explaining the stock price performance in the Egyptian stock market. This objective centers on introducing an artificial intelligence technique, namely, Artificial Neural Networks (ANNs), instead of traditional linear regression models often used in prior research. The predictive power of ANNs is tested against the predictive power of traditional linear regression models. Results suggest that the performance of ANNs outperforms that of the traditional linear regression models for some input categories not including the accounting ones. The predictive power of ANNs is almost as same as that of the traditional linear regression models for the input categories that include only accounting variables. The empirical evidence provides little support on the linear regression misspecifications as an explanation for the low documented usefulness (returns-earnings association) of accounting information in prior research.

Keywords: Artificial Neural Networks (ANNs), Association Studies, Usefulness, Technical Analysis, Synergistic Market Analysis, Macroeconomic variables

JEL Classification: G12, M41, M47, C30

Suggested Citation

El Mahdy, Dina, Using Artificial Neural Networks (ANNs) to Investigate the Usefulness of Accounting Information in the Egyptian Settings (November 12, 2009). AAA AIS-SET Mid-Year Meeting, 2010, Available at SSRN: https://ssrn.com/abstract=1505051

Dina El Mahdy (Contact Author)

Morgan State University ( email )

4100 Hillen Rd
Baltimore, MD 21218
United States
443-885-3967 (Phone)
443-885-8251 (Fax)

HOME PAGE: http://www.morgan.edu/

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