The Influence of Investor Sentiment, Investor Overconfidence, and Investor Attention on the Risk of Stock Price Fall with Analyst Herding as a Moderating Variable in Southeast Asia

This study aims to analyze the influence of investor sentiment, investor overconfidence, and investor attention on stock price crash risk, as well as to examine the role of analyst herding behavior as a moderating variable among technology sector companies listed on the Indonesia Stock Exchange (IDX), Singapore Exchange (SGX), Bursa Malaysia (KLSE), and the Stock Exchange of Thailand (SET) during the 2021–2025 period. The study employs a quantitative approach using secondary data obtained from financial statements, stock trading data, and corporate annual reports. The sample was determined using a saturated sampling technique, resulting in 468 observations. Stock price crash risk is proxied using Negative Conditional Skewness (NCSKEW) and Down-to-up Volatility (DUVOL). Data analysis was conducted using descriptive statistics, classical assumption tests, Moderated Regression Analysis (MRA), F-tests, t-tests, the coefficient of determination, and robustness tests. The research results indicate that investor sentiment, investor overconfidence, and investor attention do not significantly affect stock price crash risk, whether measured using the NCSKEW or DUVOL proxies. Furthermore, analyst herding does not moderate the relationship between these behavioral factors—investor sentiment, overconfidence, and attention—and stock price crash risk. Robustness tests employing both crash risk proxies and regression model comparisons yield consistent conclusions. These findings suggest that the examined investor behavioral factors fail to explain the variation in stock price crash risk among technology sector companies in Southeast Asia, implying the existence of other factors outside the research model that may influence such risk.