THE IMPACT OF BEHAVIORAL FACTORS ON STOCK PRICES

Abstract

This study examines the impact of behavioral factors on stock prices in the Mongolian Stock Exchange using empirical models based on behavioral finance theory. Monthly data from 2019 to 2025 were analyzed using CSAD, CSSD, and AR(1) GLS regression models. The results indicate that herding behaviors and loss aversion bias significantly reduce price volatility under certain market conditions. Conversely, overconfidence bias was found to increase volatility during bullish markets. Sectoral differences in behavioral patterns were evident, with stronger effects observed in food, finance, and light industry sectors, highlighting the theoretical and practical importance of integrating behavioral factors into investment decisions and risk management.