Special Treatment Zhongcheng Information Disclosure Violations and Financial Fraud

This thesis focuses on the typical case of Special Treatment Zhongcheng (formerly Qingdao Zhongcheng), comprehensively using empirical research methods to conduct a systematic and in-depth analysis of the company’s specific means of information disclosure violations and financial fraud. In the research process, it innovatively adopts the event study method to meticulously analyze the abnormal stock price fluctuations before and after the exposure of fraud, striving to accurately reveal the impact of fraudulent acts on the capital market. Meanwhile, the paper also deeply explores the penalty measures taken by regulatory authorities for such violations and the company’s response strategies in the face of crises. The research results show that ST Zhongcheng manipulated financial statements through a series of complex and hidden fraudulent means, including fabricating revenue, inflating assets, and concealing major litigations, eventually triggering a cliff-like decline in stock prices and causing severe damage to the vital interests of investors. This study expects to provide useful references for regulatory authorities to optimize regulatory policies, investors to enhance risk identification capabilities, and listed companies to strengthen compliance management, so as to help improve the capital market regulatory system and enhance enterprises’ awareness of compliant operations.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-11-13
DOI
https://doi.org/10.1051/shsconf/202522504018/pdf
Primary Topic
Auditing, Earnings Management, Governance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Special Treatment Zhongcheng Information Disclosure Violations and Financial Fraud

Springer Link (Chiba Institute of Technology)
Auditing, Earnings Management, Governance
article

Special Treatment Zhongcheng Information Disclosure Violations and Financial Fraud

article en

Abstract

This thesis focuses on the typical case of Special Treatment Zhongcheng (formerly Qingdao Zhongcheng), comprehensively using empirical research methods to conduct a systematic and in-depth analysis of the company’s specific means of information disclosure violations and financial fraud. In the research process, it innovatively adopts the event study method to meticulously analyze the abnormal stock price fluctuations before and after the exposure of fraud, striving to accurately reveal the impact of fraudulent acts on the capital market. Meanwhile, the paper also deeply explores the penalty measures taken by regulatory authorities for such violations and the company’s response strategies in the face of crises. The research results show that ST Zhongcheng manipulated financial statements through a series of complex and hidden fraudulent means, including fabricating revenue, inflating assets, and concealing major litigations, eventually triggering a cliff-like decline in stock prices and causing severe damage to the vital interests of investors. This study expects to provide useful references for regulatory authorities to optimize regulatory policies, investors to enhance risk identification capabilities, and listed companies to strengthen compliance management, so as to help improve the capital market regulatory system and enhance enterprises’ awareness of compliant operations.

Springer Link (Chiba Institute of Technology)
Peace, Justice and strong institutions
Openalex Percentile: Top 29%
Auditing, Earnings Management, Governance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.