We examine how mutual funds’ trading and performance respond to corporate misconduct. We exploit a combined dataset of corporate misconduct and holding information of mutual funds and show that mutual funds tend to sell and buy more stocks of corporations with misconduct. Mutual funds with more misconduct exposure perform significantly worse than those with less misconduct exposure. Specifically, the top quintile portfolio of funds with the highest levels of misconduct exposure underperforms the bottom quintile by 1.57% to 1.97% on an annualized basis. Findings show that mutual funds undergo significant losses by investing in misconduct firms, which is more likely to be motivated by overconfidence than limited recognition.

We investigate a prevalent yet overlooked form of corporate social responsibility (CSR) activities, i.e., government-launched CSR. Contrary to the conventional view that mandatory CSR destroys firm value, we document a positive market reaction to governmentlaunched CSR activities that aim to alleviate poverty. Analyses of operating performance and firm value confirm the positive impact. Further analyses suggest that while governmentlaunched CSR intervenes the operation of the firm by reducing the operating efficiency, firms enjoy higher operating margin, take more market share and save selling expense and labor cost by engaging their operations with the poverty-stricken areas. Participating firms are also rewarded more government subsidy. We further find that government-launched CSR activities achieve the stated objective of poverty relief. However, it also crowds out the firms' investment in other CSR activities. Overall, the evidence indicates that government-launched CSR has economy-wide implications than the traditional CSR.

This paper uses ensemble learning to build a predictive model to analyze the short selling mechanism of short institutions. We demonstrate the value of combining domain knowledge and machine learning methods in financial market. On the basis of the benchmark model, we use three input data: stock price, financial data and textual data and we employ one of the most powerful machine learning methods, ensemble learning, rather than the commonly used method of logistic regression. In specific methods, we use LSTM-AdaBoost and CART-AdaBoost for model prediction. The results show that the model we train have strong prediction ability for short-selling and the company' s financial text data is more likely to have an impression of whether it would be shorted or not.

The existing literature mainly documents the relationship between international and domestic fossil energy markets; however, empirical evidence of the dynamic relationships between fossil energy market and new energy market is lacking. This paper combines TGARCH model and copula model to explore the dynamic linkages and spillover effects between international fossil energy (crude oil, coal and natural gas) markets and China's new energy market using daily data from 4 January 2012 to 3 September 2018. The empirical results indicate that fossil energy returns and new energy returns are positive related over time. And the crude oil returns and new energy returns, as well as the coal returns and new energy returns have lower tail dependence, while there is upper tail dependence structure between natural gas returns and new energy returns. Furthermore, the extreme upside and downside risk spillover from international fossil energy markets to China's new energy market is asymmetric. Among the spillover effects, the downward risk spillover of crude oil market exerts the most significant impact on China's new energy market.

发展绿色金融旨在促进企业生产方式低碳转型，尤其支持企业开展绿色创新。 本文以绿色债券为例，利用双重差分模型研究了绿色金融对企业绿色创新的支持效应。研究发现，发行绿色债券显著提升了企业绿色创新能力， 这主要体现在绿色发明专利和绿色实用新型专利两个方面， 其中发行绿色债券对绿色发明专利的促进作用具有更好的动态持续性。 异质性检验发现，国有企业、非重污染企业、 无第三方认证企业、专利密集型企业在发行绿色债券后绿色创新表现更加积极。 进一步分析发现， 发行绿色债券对企业绿色创新的促进作用源于资源效应和监督效应两个机制。 本文最直接的政策含义是，为企业实现环境保护与竞争力提升的“双赢”和加快发展绿色金融促进企业绿色创新进而更好地实现绿色经济发展提供了有益的理论借鉴。

We examine the effects of controlling shareholder stock pledge on corporate acquisition decisions and associated performance. Consistent with our aggravated expropriation hypothesis, we find that pledging firms in China initiate more takeovers, but these acquisitions conducted by pledging firms experience lower announcement returns. We adopt the difference in differences and the instrumental variable approaches to establish causality. Channel tests further reveal that pledging acquirers overpay for the deals and are more likely to be involved in related party transactions. Cross-sectionally, we find that the relations between the share pledge and corporate acquisitiveness and returns are more pronounced for non-SOEs and firms with high-level excess cash. Lastly, we document that pledging acquirers underperform in the long-run in terms of lower ROAs and a greater likelihood of goodwill impairment. Overall, our findings indicate that controlling shareholders increasingly expropriate minority shareholders through self-serving corporate takeovers after the stock pledge.

This paper examines the association between acquisition performance commitment and earnings management in an emerging market where investor protection mechanisms are not well established. Based on a sample of acquisition transactions by listed firms in China during 2008-2017, we find evidence that firms committed to certain performance targets in acquisition transactions tend to engage in earnings management to meet their commitments. This phenomenon is more pronounced at the later stage of the commitment period. Further, the positive relation between performance commitment and earnings management is attenuated by a stronger governance structure. Finally, we find firms that managed to just meet performance targets experience worsened accounting-based and market-based performances and higher probability of goodwill impairments immediately after the commitment period. This paper contributes to the acquisition literature by providing evidence from an emerging market of post-contractual opportunistic behavior.

救助财务困境企业有助于恢复市场微观主体活力，进而保持金融和社会稳定。但区别于银行和风险投资机构所开展的顺周期投资，困境企业救助属于逆周期投资，具有更高的行为风险和经营风险。金融资产管理公司作为困境企业救助专业性机构，如何开展投资前的救助对象筛选与投资后的风险控制，目前学术界对该问题尚缺乏研究。本文基于金融资产管理公司主导的18家财务困境企业救助的多案例编码研究及典型交易模式分析，构建了财务困境救助的投前企业筛选与投后风险分配的理论模型。本文发现，投前企业筛选主要识别抵偿价值、经营恢复价值和重组价值，投后风险控制关注行为风险抑制和经营风险分配。本文研究成果对逆周期投资价值识别、风险识别与控制等研究做出了重要的贡献，对社会机构参与困境企业救助有实践意义。

Using Chinese data, we investigate the impact of the China Semi-Mandatory Payout Policy that sets an explicit requirement that firms need to distribute at least 20% of their average annual net profits as cash/stock dividends accumulatively in three consecutive years before refinancing via seasoned equity offerings. Firms with the payout level below (above) the cutoff imposed by the Semi-Mandatory Payout Policy are regarded as Treated (Control) group. We find that Treated firms are more likely to cut investment, especially long-term innovation investment, and perform poorly compared to Control group due to lack of money. Treated firms also tend to use earnings management assisting in financing through the debt market as an alternative way to raise money. The negative impact of cutting investment caused by the Semi-Mandatory Payout Policy is more pronounced for firms suffering from severe financial constraints, firms having good corporate governance, and firms located in less financial development areas. We attribute findings to the difficulty of accessing capital that is implicitly increased the China Semi-Mandatory Payout Policy, which alters firms’ behavior leading to insufficient investments and destroys firms’ value.

本文以《关于实施上市公司股息红利差别化个人所得税政策有关问题的通知》的实施为自然实验，考察降低股利税对公司现金分红的影响。研究发现：（1）在股利税降低的年份，上市公司分红水平和意愿显著提高，并且管理层持股越多，现金分红增加的可能性越大，而在股利税不变的年份则不存在这种关系，表明降低股利税能够激励管理层增加现金分红。（2）降低股利税对管理层增加现金分红的激励作用仅在公司治理水平较高或法律环境较好时显著，表明现金分红是公司治理的“果”而不是“因”。（3）股利税降低仅能激励非国有企业的管理层增加现金分红。（4）投资者认可管理层因股利税降低而增加现金分红的行为。本文的政策含义在于，降低股利税能够达到促进上市公司进行分红的目的，但要从根本上提高我国上市公司分红水平，关键在于进一步完善上市公司的治理机制。