Logistic Regression In Detecting of Fraudmental Financial Statements with Using Financial Ratios

We examines published data to develop a model for detecting factors associated with Fraudmental financial statements (FFS). Most Fraudmental financial statements in Tehran Stocks Exchange (Tse) Listed Companies، can be identified on the basis of the financial ratios. We use a sample of 68 firms includes 34 with FFS and 34 non- FFS. Nine financial variables are selected for examination as potential predictors of FFS. Univariate and multivariate statistical techniques (logistic regression) are used to develop a model to identify factors associated with FFS. The model is accurate in classifying the total sample correctly with accuracy rates 83/8 per cent. The results therefore demonstrate that the models function effectively in detecting FFS and could be of assistance to Investors and auditors, both internal and external and taxation، Government bodies and to the banking system.