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.
odels,some of which have applied them after making some adjustments on some approaches of relevant models. A brief summary on the most important researches will be given below.
Khodadadi et al. (2005) have reviewed seven linear information models with using 15 years time-series data in 21 firms listed on Tehran Stock Exchange. Their research results show that linear information model No. 1, the same model presented by Ohlson (1995) which does not consider the other information variable, has the best function in the forecast of abnormal earnings.
C.M.C Lee, et al. have studied whether traditional criteria (based on dividend, earnings and ratio of book value to market value) can predict stock efficacy better or a criterion based on Ohlson model. They conclude that Ohlson model is more successful in the forecast of stock returns than other methods.
Making a study on the previous researches having been tested Ohlson and Feltham- Ohlson models, K. Lo and T. Lys (2000) concluded that there are empirically many methods to improve the theoretic framework of these models and their validity test.
Dechow et al. (1999) emphasize that linear information models should make a relationship between current information and firm’s value in order to achieve Ohlson and Feltham-Ohlson models considered results.
J. Hand and W. Landsman (1998) found that when the other information variable is ignored in
Ohlson model, the dividend find direct relation with market value of stakeholders’ equity whereas it is
expected that this relation is reverse.
R. Frankel and C.M.C Lee (1998) once tested the Ohlson model with employing historical
information of profit and once more with applying profits predicted by analysts and, thus, they concluded that using the analysts’ forecast would increase the model validity.
T.L. Stober (1996) employed Feltham-Ohlson model in the forecast of abnormal earnings in US and with using a combination of cross-section and time series data in a 10 years period. Bauman (1999)
repeated Stober’s (1996) research but he used time-series data during a 15 years period of time. In two
63 International Research Journal of Finance and Economics - Issue 36 (2010) above mentioned researches though the values of coefficients are as expected, their significance level has not been referred to.
McCrae and Nilsson (2001) have tested Ohlson model in the forecast of abnormal earnings and firm’s value in Sweden. They used cross-section data in their research and proved the efficiency of this model.
Study of Choi, Ohanlon and Pope (2001) is similar to research made by McCrae and Nilsson (2001) but they tested US stock exchange market. They, also, proved the applicability of Ohlson
model.
Moreover, Callen and Morel (2001) tested Ohlson model with using time-series data in a 25-year period of time and with ignoring the other information variable in the United States and they also proved the validity of this model.
When testing Ohlson model in Athena stock exchange, G.A. Karathanasis and S.N. Spilioti(2005) state that in order to overcome the problems caused by statistical methods such as autocorrelation,co-linearity among independent variables and heterogeneous dispersion in employing Ohlson model it is necessary to use a combination of these two types of data (panel data) instead of solely use of cross-section or time series data. In their resear
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