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摘要：The research results show that sign-orientedmodels have better performance in the prediction of abnormal earnings compared totraditional model. Using forecasted abnormal earnings in all of the valuation functionsindicate that none of the studied models can appropriately forecast firm’s value.

this condition has not been included in present research, this method cannot be utilized. Therefore, Pooled Data Method was employed in this research.
There are special tests to survey the stationary of variables in panel data methods; tests such as
Levin and Lin Test, Im, Pesaran and Shin Test, ADF Test, Fisher Test, Breitung Test and Hadri Test,
some of which have been explained by Zaranejad and Anvari (2005). Breitung Test was utilized to
review the stationary of abnormal earnings in this research.

4. Findings of Research
Firstly, in Table 2, a summary on the descriptive statistics of the research variables has been presented
and, then, it is paid to the review of research findings.
Table 2: Descriptive statistics (accounting data in million euros)
Variable N Mean Median Minimum Maximum Skewness Kurtosis
Abnormal earnings 580 22.3678 8.5589 0.31 136.17 2.608 6.945
Earnings 580 1.2115 0.7638 0.4 3.34 1.749 2.635
Lagged book value(bvj,t-1) 580 1.6514 0.8343 0.36 4.44 1.022 -0.226
Cost of equity rate 580 -17.1214 -5.1604 -92.24 0.2 -2.48 6.695
Free of risk return rate 11 0.1732 0.17 0.15 0.2 0.318 -1.552
Systematic risk(βj,t) 580 1.1655 0.3607 0 6.22 2.48 6.695
Market Value of equity 580 17.5731 11.8515 6.06 53.45 1.956 4.426
Fixed conversion rate(1 Euro=13000 Rials) is used to convert accounting data into Euro
4.1. Stationary Test
In panel and time-series data, the required condition for testing data is the dynamics of research variables. So, firstly, to be assured of the trueness of the results gained in next steps, the stationary of the variables of abnormal earnings and book value were tested within the framework of panel data with using Breitung Test. The null hypothesis of this test has been designed on the basis of the lack of stationary; the results of this test have been submitted in Table 3. Table 3: The Results of Abnormal Earnings and Book Values stationary test
Variables Statistic sig Abnormal earnings -6.55 0.000
Book values -2.77 0.0 28
According to the contents of this table, the null hypothesis was failed in a significant level of
1% and the opposite assumption is supported. Thus, the abnormal earnings and book values have
stationary.
International Research Journal of Finance and Economics - Issue 36 (2010) 68
4.2. Assumption on the Existing Forecasting Relationship
For testing this hypothesis in all models, the information related to the years of 1998-2002 was used in
step 1 for the first estimation period and in each of the next periods it has been added one year to the
estimation period in order to use the obtained information for each estimation in next steps to estimate
the firm’s value at the end of the last year of the relevant estimation period. The results associated with
this test have been displayed in Table 4. It should be noted that as a result of existing heterogeneity
among periods, EGLS method by weighing on the periods was applied in this research.
As specified in this table, the obtained coefficients are mostly significant in the levels of 1% to
10% and confirm the existing forecast relationship and models application. The noteworthy point of
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