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Rough Sets Bankruptcy Prediction Models Versus Auditor Signalling Rates

Rough set prediction capability was compared with actual auditor signaling rates for a large sample of United States companies from 1991 to 1997 time period. Prior bankruptcy prediction research was carefully reviewed to identify 11 possible predictive factors which had both significant theoretical support and were present in multiple studies. Rough sets theory was used to develop two different bankruptcy prediction models, each containing four variables from the 11 possible predictive variables. In contrast with prior rough sets theory research which suggested that rough sets theory offered significant bankruptcy predictive improvements for auditors, the rough sets models did not provide any significant comparative advantage with regard to prediction accuracy over the actual auditors' methodologies.

Identiferoai:union.ndltd.org:ETSU/oai:dc.etsu.edu:etsu-works-15256
Date01 December 2003
CreatorsMcKee, Thomas E.
PublisherDigital Commons @ East Tennessee State University
Source SetsEast Tennessee State University
Detected LanguageEnglish
Typetext
SourceETSU Faculty Works

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