我国上市公司大股东违规的行为监测与风险评估

项目名称： 我国上市公司大股东违规的行为监测与风险评估

项目编号： No.71471043

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 管理科学

项目作者： 张金清

作者单位： 复旦大学

项目金额： 57万元

中文摘要： 本项目将首先对我国上市公司有可能违规的大股东以及大股东违规行为的内涵、特征进行深入阐释，在弄清楚大股东违规的主、客观影响因素的前提下建立可以准确刻画大股东违规行为、尤其是隐蔽性强且形式多变等特征的最优决策模型；借助于该模型，考察大股东违规的所有可能影响因素及其作用机制，构建可反映大股东违规行为的监测-判别指标体系及基于其上用以计量大股东违规程度和可能性的测度模型；据此对我国上市公司大股东违规程度和可能性进行监测、判断、进而等级划分，确定不同违规等级之间的临界值及其对应区间，建立我国上市公司大股东违规行为的预警系统，对大股东违规状况及其变化趋势予以判断；根据上述监测、判断结果所确定的不同情况，对大股东违规行为所可能导致的公司价值变化、中小股东以及大股东损益等风险状况进行评估；最后，基于监测、判别与评估的结果，对如何有效监管不同情形下的大股东违规行为提供相应的对策和建议。

中文关键词： 大股东违规；行为监测；风险评估；风险监管

英文摘要： Firstly,the project gives an in-depth interpretation of the connotation and features about the potential large shareholder violators in Chinese listed companies and their violations, and on the premise of figuring out the subjective and objective factors concerning large shareholders' violations, we establish an optimal decision model to portray their highly hidden and changeable violations accurately.By means of the model, we examine all the factors affecting large shareholders' violations and their working mechanisms, then build the measuring model with the indicator system to monitor and discriminate these violations. Accordingly, we monitor, discriminate and rank the possibility and severity for the large shareholders to exercise violations ,obtain the threshold between different ranks, and thereby establish the pre-warning system to monitor and discriminate their violations, so as to estimate the situation and variation trend of large shareholders' violations in China's listed companies. Based on the estimation, we respectively assess the changes in the companies' value, the gains and losses of the minority shareholders and the large shareholders resulting from the violations in different cases. Finally, according to the results of the monitoring, discrimination and assessment, we put forward countermeasures and suggestions on how to effectively supervise large shareholders' violations under different circumstances.

英文关键词： Violations of the Large Shareholder;Behavior Monitoring;Risk Assessment;Risk Supervision