eng Science and Education Publishing Journal of Finance and Economics 2328-7276 2023-07-11 11 2 113 130 10.12691/jfe-11-2-5 JFE20231125 article Mohamad Saad Mohamad Saad, saadmohamad313@gmail.com 1 Department of Management, University of Tehran, Kish International Campus, 79416-55665, Kish Island, Islamic Republic of Iran This study examines the information efficiency of eight stock valuation models, including a novel model called NAPV, to accurately estimate stock prices by reflecting all relevant information. An experiment was conducted with 65 traders, 20 evaluators, and a virtual company. The evaluators provided an informationally efficient benchmark. The stock price growth rates generated by each model were compared to this benchmark. The results indicate that NAPV was the most efficient model, accounting for 89% of the variation in the benchmark. Meanwhile, the Constant-Growth DDM, Adjusted Net Asset, and Constant-Growth RIM models explained approximately 30% of the variation. Other models showed no significant relationship. Income-based models were less efficient than other models, some generating no value at times. The two-stage modelĄ¯s sensitivity to estimated terminal value limits its efficiency. The findings suggest that NAPV is a promising tool for valuation, as it can decompose the stock value into key components of value. NAPVĄ¯s full potential requires some regulatory measures and an updated stock pricing mechanism. Implications include shareholders carefully choosing a model, regulators enabling NAPVĄ¯s potential, and developing new models addressing limitations. Future research could explore other influences on modelsĄ¯ efficiency, study implementing regulatory measuresĄ¯ impact, and develop new models. https://pubs.sciepub.com/jfe/11/2/5/jfe-11-2-5.pdf Stock valuation models Information efficiency NAPV model Growth premium Evaluators