ESG评级能抑制大股东掏空行为吗？——基于我国A股上市公司的实证研究

以2011—2022年沪深A股非金融上市公司为研究对象,从资金占用和关联交易两个角度实证检验ESG评级对大股东掏空行为的影响及作用机制。研究发现,ESG评级能够显著抑制大股东掏空行为。机制检验结果表明,ESG评级不仅可以通过提升信息透明度（激励内部信息披露和吸引分析师关注）、强化中小股东退出威胁等渠道抑制大股东掏空行为,还能够通过提高内部控制质量来抑制资金占用类掏空行为。异质性分析发现,在高质量法律环境和高股权制衡的情况下,ESG评级对大股东掏空行为的抑制作用更加显著;在国有企业中,ESG评级能够更加显著地抑制大股东通过关联交易掏空公司的行为。研究结论为加强股东治理、保护投资者提供了经验证据,对企业ESG实践和资本市场高质量发展具有重要意义。     

Mixture of MLP-experts for trend forecasting of time series: A case study of the Tehran stock exchange

A new method for forecasting the trend of time series, based on mixture of MLP experts, is presented. In this paper, three neural network combining methods and an Adaptive Network-Based Fuzzy Inference System (ANFIS) are applied to trend forecasting in the Tehran stock exchange. There are two experiments in this study. In experiment I, the time series data are the Kharg petrochemical company’s daily closing prices on the Tehran stock exchange. In this case study, which considers different schemes for forecasting the trend of the time series, the recognition rates are 75.97%, 77.13% and 81.64% for stacked generalization, modified stacked generalization and ANFIS, respectively. Using the mixture of MLP experts (ME) scheme, the recognition rate is strongly increased to 86.35%. A gain and loss analysis is also used, showing the relative forecasting success of the ME method with and without rejection criteria, compared to a simple buy and hold approach. In experiment II, the time series data are the daily closing prices of 37 companies on the Tehran stock exchange. This experiment is conducted to verify the results of experiment I and to show the efficiency of the ME method compared to stacked generalization, modified stacked generalization and ANFIS.     

浅谈改装车备胎升降机构的运用

备胎升降机构是改装车的重要部件之一,文章对备胎升降机构在改装车上的运用作了简要介绍及展望。