Comparison of RW and PW models in profit forecasting for small and medium companies

This article aims to compare RW and PW models in profit forecasting for small and medium-sized companies. The research method is applicable in terms of its purpose, and it is an inductive and quantitative research in terms of the implementation logic and the nature of the data. Financial statements in the period of 2011 to 2021 have been used to collect data. In order to select the appropriate statistical sample, the systematic elimination sampling method was used. In this method, firstly, the small and medium-sized companies are identified, according to the number of employees and the nominal value of the capital, and conditions are defined for the selection of the sample, and those that do not have the mentioned conditions are removed from the sample. These conditions are determined according to the hypothesis test model and research variables. Also, in this article, the panel model and Eviuse software have been used to extract the proposed model from the principal component analysis approach and to fit the model to the observations. According to the results obtained from the analysis presented in this research, it can be seen that the new model provided for profit forecasting is more effective than the profit forecasting of RW and PW models, and this issue confirms the ability of regression models to forecast profit in the field of financial and profitability strategies for small and medium-sized companies.