Modeling of Minimizing Uncertainty Based on Accounting Data Quality Proxies by Decision Tree methodology: Evidence for Information-Uncertainty Theory
Quarterly Journal of Securities Exchange

Quarterly Journal of Securities Exchange

Modeling of Minimizing Uncertainty Based on Accounting Data Quality Proxies by Decision Tree methodology: Evidence for Information-Uncertainty Theory

Authors
Hossein Etemadi
Reza Hesarzadeh
Ali Rahmani
Adel Azar
Abstract
Accounting is the science of presenting information and consequently decreasing uncertainty. So, accounting data capacity for reducing uncertainty determines accounting data quality. This study, applying empirical analyses is using data from fiscal years 2001 to 2010 of the companies listed on Tehran Stock Exchange. The study examines the relationship between quality measures and measure of uncertainty. Then, using fuzzy decision tree methodology, counterbalancing measures of quality and combination of quality measures that can lead to the minimization of uncertainty, will be identified. The findings of the first phase show that there are significant relationships between some measures; second, some measures can reduce uncertainty and also, dimension of measures can be reduced. The findings of the second phase show three-way interaction to minimize uncertainty.
Keywords
Critique
Decision Tree
Event Study.
Financial Reporting Quality
Measures
Theory
Uncertainty