Discount Rate Methods (Ke, WACC, and Kd): Accuracy and Robustness Analysis

Abstract

This study examines the accuracy and robustness of three widely used corporate valuation methods: Weighted Average Cost of Capital (WACC), Cost of Equity (Ke), and Cost of Debt (Kd). The sample comprised 22 industrial companies listed on the New York Stock Exchange (NYSE) between 2021 and 2024. Error metrics (MAE, MAPE, RMSE, and bias), equivalence tests (ANOVA and Kruskal-Wallis), and correlation and regression analyses were applied. Results indicate statistical equivalence in predictive performance across the three methods and a very high correlation among their estimates (r>0.98). Nevertheless, Ke outperforms in terms of correlation with market prices (r=0.803) and explanatory power (R²=0.644), while Kd achieves the lowest RMSE and bias. At the sector level, methods remain consistent, though accuracy varies across subsectors. Overall, the findings suggest that the choice of valuation method depends more on theoretical foundations and industry context than on empirical differences in predictive accuracy.