Số 238 | Tháng 01/2026
Tác động của thông báo vi phạm đến rủi ro sụt giảm giá cổ phiếu trên thị trường chứng khoán Việt Nam
Nguyễn Duy Linh, Đào Thị Minh Anh, Phan Vũ Thuỳ An, Lê Hoàng Phước Đạt, Đỗ Hoàng Khương, Nguyễn Minh Thư
Tóm tắt:
Mục tiêu nghiên cứu: Bài viết tập trung phân tích tác động của thông báo vi phạm (TBVP) đến rủi ro sụt giảm giá cổ phiếu (RRSGGCP) trên thị trường chứng khoán (TTCK) Việt Nam trong giai đoạn 2018–2023. Từ kết quả thực nghiệm, nghiên cứu cung cấp hàm ý chính sách cho các bên liên quan trên TTCK Việt Nam.
Thiết kế nghiên cứu/phương pháp/tiếp cận: Sau khi dữ liệu được thu thập tự động bằng Python, các kiểm định được thực hiện và cho thấy mô hình tác động cố định (FEM) phù hợp hơn OLS và REM. Cuối cùng, mô hình bình phương tối thiểu tổng quát khả thi (FGLS) được dùng để khắc phục hiện tượng tự tương quan và phương sai sai số thay đổi, đảm bảo độ tin cậy của kết quả ước lượng.
Kết quả nghiên cứu chính: TBVP được công bố giúp môi trường thông tin minh bạch hơn, do đó làm giảm RRSGGCP. Đồng thời, các nhóm TBVP liên quan đến gian lận tài chính có tác động rõ rệt hơn so với những TBVP quy định hoạt động.
Giá trị đóng góp mới: RRSGGCP dưới tác động của TBVP đã được phân tích tại các thị trường phát triển và mới nổi, tuy nhiên đề tài này vẫn chưa nhận được nhiều sự quan tâm tại thị trường cận biên như Việt Nam. Vì vậy, nghiên cứu này nhằm cung cấp thêm bằng chứng thực nghiệm về tác động nghịch chiều của TBVP đến RRSGGCP trên TTCK Việt Nam.
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The Impact of Violation Announcements on Stock Price Crash Risk: Evidence from Vietnam
Abstract:
Purpose: The study focuses on analyzing the impact of FRAUD announcements (FA) on stock price crash risk (SPCR) in Vietnam’s stock market during the period 2018-2023. Based on the empirical findings, this study provides policy implications for relevant stakeholders in Vietnam’s stock market.
Design/Methodology/Approach: After the data were automatically collected using Python, diagnostic tests were performed, indicating that the Fixed Effects Model (FEM) is more appropriate OLS and the Random Effects Model (REM). Finally, the Feasible Generalized Least Squares (FGLS) method is used to address autocorrelation and heteroskedasticity, ensuring the reliability of the estimation results.
Findings: The findings reveal that the disclosure of FRAUD announcements contributes to a more transparent information environment, thereby reducing stock price crash risk. Moreover, FRAUD announcements related to financial misconduct exhibit a more pronounced effect compared to those concerning operational non-compliance.
Originality/value: While the impact of FRAUD announcements on stock price crash risk has been extensively analyzed in developed and emerging markets, this topic has received limited attention in frontier markets such as Vietnam. Therefore, this study aims to provide further empirical evidence on the negative impact of FRAUD announcements on stock price crash risk in the Vietnamese stock market.