Does Investor Sentiment Moderate the Link Between Ownership Structure, Debt, and Stock Price Crash Risk in the Indonesian Technology Sector? - Lisa Kustina; Doni Juliansyah (International Journal of Business Economics (IJBE), 2025)
Purpose – Conducting this research will help to look into how ownership structure, debt maturity, and investor sentiment affect the chance of a stock price crash risk among technology businesses that are traded on the IDX stock market between 2020 and 2022. The goal is to identify the key elements determining the likelihood of collisions.Methodology – A quantitative method employing binary logistic regression is utilised to investigate the impact of ownership structure, debt maturity, and investor sentiment on the likelihood of stock price crashes. Ownership composition, debt maturity, sentiment indicators, and stock price data from 172 firm-month observations are among the secondary data included in the investigation.Findings – According to the findings, Investor Sentiment (X3) substantially enhances the chance of a stock price crash (Y). While Debt Maturity (X2) and Ownership Structure (X1) are not significant on their own, their interaction with Investor Sentiment (X3) exerts a considerable moderating influence. Associated with Investor Sentiment (X3) and crash risk is substantially influenced by diverse Ownership Structure (X1) types, implying that market sentiment's effect depends on ownership characteristics.Originality/Novelty – This research contributes to the restricted field of empirical studies conducted with regard to the possibility of stock market crises occurring in developing economies, particularly in the technology sector in Indonesia. By incorporating Debt Maturity (X2) and Investor Sentiment (X3) as explanatory variables, it offers a more detailed understanding of factors leading to crash risk.Implications – The results provide helpful information for technology companies' risk management plans. They advise investors and policymakers to carefully monitor ownership trends, debt maturity, and investor sentiment to better predict and minimise the danger of stock market crashes.