Abstract

This study investigates whether regulating the stock pricing mechanism by adopting an agreed-upon efficient stock valuation model can enhance the stock market efficiency. The study involves a simulated stock market experiment with 65 traders who provide daily stock price predictions for a virtual company under unregulated and regulated scenarios. In the regulated scenario, traders agree on one of three valuation models to generate stock prices. Moreover, 20 evaluators acted as “Homo-Economicus” to determine a stock's fair value trend, serving as a benchmark to assess the information efficiency of the simulated market. The study finds that the NAPV-regulated market shows a strong linear relationship and high R-squared, indicating the highest level of information efficiency, while the DDM- and RIM-regulated markets show moderate correlations. The study suggests that modernizing the stock pricing mechanism, by regulating shareholders to mutually agree on one efficient stock valuation model to be used by the company to generate fair values alternative to market prices, could significantly enhance the stock market efficiency by focusing on fundamentals rather than irrational speculators. However, model choice matters, as NAPV explains more variation. The study suggests that appropriate regulation is crucial for realizing this potential. Although the results are promising, limitations like small evaluator samples, inability of models to always generate stock values, and trader biases should be considered. Future research with larger samples and more models could strengthen these insights.

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