COMPARING THE METHODS OF PREDICTION AND BUSINESS COST ESTIMATION BASED ON INDUSTRY-SPECIFIC, CLUSTERING, AND REGRESSION MODELING

Background: Being the most common, the relative valuation method plays a special role in estimating the value of a business. Many studies consider various applications of multipliers. However, the study results are often contradictory. Objective: This article aims to determine the best method for assigning a fair value to the multiplier of the assessee company. Methods: Within the empirical study, the effectiveness of three forecasting methods (industry-specific, cluster, and regression) was compared. Results: Regression modeling is the most accurate approach and outperforms other methods in terms of MAE and. The best multiplier is considered the one that can reach the maximum metrics for assessing the quality of models. The largest variance within the existing data set can be explained for multiples based on sales P/Sales and EV/Sales. Other issues were also solved in the course of the study. The best method for determining groups of peer companies has been determined. Conclusion: The proposed cluster approach is superior to the industry-specific approach. While comparing these approaches, the authors identify the best measure for calculating the typical value of multipliers within a group of peer companies. The simple average and median indicators were more accurate than the other calculation methods