It is a rare day when the Wall Street Journal does not include an announcement that a company is taking a restructuring charge. Nowadays it is often assumed that this charge is being taken for the purpose of managing earnings. The problems associated with earnings management are not limited to Wall Street but can be found throughout the world's financial markets. Ongoing developments in artificial intelligence technology hold considerable promise for helping monitor and detect financial fraud and abuse. The objective of this paper is twofold: first, to illustrate how neural nets, a branch of artificial intelligence, can be used to analyze the impact of corporate restructuring announcements on stock performance and second, to propose the need for a balanced approach using both tighter accounting standards and ex-post analysis for better control of excessive earnings management practices.
Hall, Owen P. Jr. and McPeak, Charles J.
"Using Neural Net Technology to Analyze Corporate Restructuring Announcements,"
Journal of International Information Management: Vol. 12
, Article 3.
Available at: https://scholarworks.lib.csusb.edu/jiim/vol12/iss2/3