Mohammad Reza Nikbakht; Mohammad Reza Asgari; Hamidreza Ganji; Arash Tahriri
Volume 5, Issue 17 , April 2007, , Pages 129-150
Abstract
In this study the existence of abnormal return and its effective factors were examined. The results show that there is positive short term abnormal return during six month after the acceptance of sampled corporations in exchange. Among seven variable s; Size, Horizon, Coefficient of Variances, Stock ...
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In this study the existence of abnormal return and its effective factors were examined. The results show that there is positive short term abnormal return during six month after the acceptance of sampled corporations in exchange. Among seven variable s; Size, Horizon, Coefficient of Variances, Stock Market Return one month before the offering of stock , Audit Firm and Industry Type, only Size (reversely) and Stock Market Return (directly) had a relation with abnormal return; however, multi variable regression analyses demonstrated that al l of the variables can simultaneously justify just around 20% of abnormal return.
Gholamreza Islami; Hossein Zarei
Volume 2, Issue 7 , October 2004, , Pages 97-122
Abstract
This empirical study has been done with the goal of developing auditing knowledge and the efficiency of its operations when using the statistical analytical procedures.
In this research, eight alternative models have been evaluated, including five regression models, one time - series model ( consus ...
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This empirical study has been done with the goal of developing auditing knowledge and the efficiency of its operations when using the statistical analytical procedures.
In this research, eight alternative models have been evaluated, including five regression models, one time - series model ( consus X-Ii) and two non-statistical models (Martingale and sub-Martingale). Both financial and non-financial data were collected from a sample of petrochemical companies for the period march, 1998 through March 2001. The information was used to predict sales revenue and production expense account balances.
According to the results, regression models have better performance for predicting account balances in performing auditing analytical procedures in comparison to Two other models.
Logarithmic regression has been evaluated as the best statistical analytical procedure. The foresaid procedure has a constant performance in sample companies of the industry. In performing statistical analytical procedures, monthly models perform better than seasonal ones. Pooled models have a better ability for prediction than single company models.
Furthermore, the results of this research show incremental benefits of using nonfinancial variable in performing statistical analytical procedures in auditing
