INVESTIGATING THE ACCURACY OF ALTERNATIVE VALUATION METHODS FOR STOCK VALUATION

Introduction: This study evaluates the predictive accuracy of common equity valuation models employed on the Mongolian Stock Exchange (MSE), a frontier market with an underdeveloped institutional infrastructure. The objective is to determine which valuation approach most effectively explains the deviation between IPO forecasted prices and actual post-IPO market performance. Methods: We analyzed 32 IPO valuation reports issued between 2011 and 2023 by certified Mongolian valuation firms. Five widely used methods – Discounted Cash Flow (DCF), Dividend Discount Model (DDM), Residual Income Model (RIM), Net Asset Valuation (NAV), and Relative Valuation – were identified and assessed. The accuracy of each approach was tested using regression models, with the dependent variable defined as the absolute percentage deviation between the target and realized 12-month average trading price. Results: Empirical research has extensively examined the accuracy of various stock valuation methods, including the DCF model, DDM, RIM, and market multiples such as the P/E and P/B ratio. These studies provide insights into the effectiveness of each approach under different market conditions and firm characteristics. While each valuation method has its advantages and limitations, empirical evidence suggests that the choice of model should be tailored to the specific context, considering factors such as market conditions, firm characteristics, and the availability of reliable data. Although DCF was the most frequently applied method (62.5% of reports), hybrid models – where multiple methods are combined – showed the highest explanatory power (adjusted R² = 0.22). Higher profitability (ROA) significantly improved valuation accuracy, while higher interest rates were associated with reduced accuracy. Single-method models such as DDM, RIM, and NAV did not yield statistically significant improvements in forecast performance. Discussion: Hybrid valuation approaches offer superior predictive accuracy compared to standalone models in frontier markets, such as Mongolia. The results highlight the value of method triangulation and financial performance indicators in improving valuation precision. Policymakers and practitioners should consider encouraging hybrid models to enhance the robustness and reliability of IPO valuations.