This paper documents a stock-dividend premium of around 10% when controlling for optimistic earnings growth and liquidity improvement. We propose an alternative explanation for the effect of stock dividends from the perspective of investor recognition. First, we find that stock-dividend premiums are positively related to an increase in investor base, particularly for firms with a small investor base. Second, an increase in investor base is due to individual investors, as they, especially those with a stronger propensity to gamble, are net buyers around the announcement of stock dividends, while institutional investors behave in the opposite manner. Finally, we show that after paying stock dividends, firms experience significant increases in speculative features, which are caused by clientele shifts toward individual investors.. As a whole, our results also indicate that an increase in investor base could be related to investors' gambling preferences.

2018年受去杠杠政策影响，大量民营企业陷入流动性危机，为此，国家号召各地政府成立纾困基金纾困上述民营企业。本文以政府对民营上市公司股权纾困的130个样本为例，基于各地政府响应国家号召对民营企业纾困这一准自然实验，用DID等方法检验了政府纾困民营上市公司的经济后果，研究发现：（1）在短期内，政府纾困起到了稳定市场的作用。具体而言，接受政府纾困的民营上市公司公告之后市场有显著的正面反应，同时被纾困方股权质押风险得到了缓解。（2）但在长期来看，政府纾困并没有改善被纾困民营上市公司的经营绩效，这体现在纾困完成后，公司的经营业绩表现更差。（3）并且，在纾困中，纾困双方信息不对称程度越高、代理问题越严重，政府的长期纾困效果越差。换言之，纾困方越有可能成为“接盘侠”。本文为政府维护金融市场稳定发展提供了实证依据，也为后续进一步规范政府纾困行为提供指导性的政策参考。

This study examines the price discovery patterns in the three BRICS countries’ stock index futures markets that were launched after 2000 – China, India, and Russia. We detect two structural breaks in these three futures price series and their underlying spot price series, and use them to form subsamples. Employing a Vector Error Correction Model (VECM) and the Hasbrouck (1995) test, we find the price discovery function of stock index futures markets generally improves over time in China and India, but declines in Russia. A closer examination not only confirms the findings of Yang et al. (2012) and Hou and Li (2013) regarding price discovery in China’s stock index markets, but also reveals the inconsistency of futures’ leading role in the price discovery process. Further, we find some evidence of day-of-the-week effects in earlier part of the sample in China, but not in India or Russia. And our GARCH model results show bidirectional volatility spillover between futures and spot in China and India, but only unidirectional in Russia.

Although China has the largest trading volume of commodity futures, limited studies have been devoted to the term structure of Chinese commodity futures. This paper takes the tools in functional data analysis to understand the term structure of commodity futures and forecast its dynamic changes at both short and long horizons. Functional ANOVA has been applied to examine the calendar e_ect of term structure in level and _nd the seasonality in the commodity futures of coking coal and polypropylene. We use an h-step functional autoregressive (1) model to forecast the dynamic change of term structure. Comparing with native predictor, in-sample and out-of-sample forecasting performance indicate that additional forecasting power is gained by using the functional autoregressive structure. Although the dynamic change at short horizons is not predictable, the forecasts appear much accurate at long horizons due to the stronger temporal dependence. The predictive factor method has a better in-sample _tting, but it cannot outperform the estimated kernel method for out-of-sample testing, except for 1-quarter-ahead forecasting.

By testing properties implied by one-dimensional diffusion option pricing models, we find that call (put) prices in the Chinese 50ETF option market move in opposite (same) direction with the underlying between 13.39% and 27.89% (between 12.45% and 33.98%) of the time for 5-minute and 1-day sampling intervals respectively. Given fundamental different investor structures in U.S. and China option markets, we also observe some important unique features in the 50ETF option price dynamics. More importantly, we demonstrate that these striking violations reduce substantially in 2016 compared with those in 2015, indicating that Chinese stock option market becomes more efficient.

通过从我国22种商品期货提取隐含的便利收益率时间序列，我们发现，期货市场的便利收益率的前两个主成分可以在样本内和样本外显著预测未来通货膨胀率。在控制了利率、M2货币增速等因素的影响后，这一结果仍然成立。我们也用南华商品期货综合指数、南华商品期货各品种指数、南华商品期货大类指数，以及美国商品研究局商品期货指数对我国通货膨胀率进行了样本外预测，结果表明这些指数对于预测我国通货膨胀率同样效果显著。基于商品期货价格的预测模型都明显优于本文的基准模型和朗润预测指数。这表明我国商品期货市场包含了与通货膨胀率相关的重要信息，可以作为未来宏观形势走向和政策实施的重要参考。

本文立足于中国双支柱调控框架，系统地梳理了货币政策与宏观审慎影响银行流动性创造的风险承担机理，并选取 2015-2018年上市商业银行和公司为样本，运用中介效应模型，检验货币政策、宏观审慎、风险承担、流动性创造和企业产出的作用机制。研究结果显示货币政策价格型工具和宏观审慎工具可抑制由数量型工具引发的银行风险承担与流动性创造水平变化系统性风险增大会增加表外流动性创造风险承担是双支柱监管影响银行流动性创造的重要渠道之一流动性创造可通过信贷额度 增加企业营业收入。因此，降低货币政策与宏观审慎的内在冲突，提高银行稳定性，有助于增强流动性创造对企业可持续发展的金融支持 。

本文基于银行信贷创造观，旨在计算出个体银行在多重监管下以利润最大化为目标的信贷创造量。我们建立了静态的多重监管模型用来分析多重监管对银行信贷创造的影响并基于流量存量一致性建立了简化的以商业银行为主体的经济动力系统，借以通过最优控制理论分析银行的动态信贷创造路径。从静态和动态两个角度分析了监管下商业银行的最 优信贷量，有助于理解监管政策和货币政策的宏观经济效果.

本文基于包商银行等事件的现实背景，梳理了近年来出险的几家银行存在的共同特征，挖掘同业业务风险与公司治理薄弱的问题。从银行系统脆弱性特征入手，使用中国银行业数据库(CBD)中2009 年-2019 年的相关数据，通过模拟银行在遭受外来冲击和其他银行通过同业网络进行风险传染的可能违约次数，构造银行脆弱性指标。进一步探究银行内部经营与治理因素对银行脆弱性的影响，主要实证结果表明同业占比过高会加剧银行的系统脆弱性特征，适当的股权集中度和股权制衡度有利于减缓脆弱性；2014 年同业监管政策实施后同业业务对银行脆弱性的提升作用显著减弱。

We study non-performing loan (NPL) transactions in China using proprietary data from a leading market participant. We find these transactions – driven by tighter financial regulation – are consistent with banks concealing non-performing assets from regulators as (i) transaction prices do not compensate for credit risks; (ii) banks fund the NPL transactions and remain responsible for debt collection; and (iii) 70% of NPL packages are re-sold at inflated prices to bank clients. These results imply NPL transactions do not truly resolve NPLs. Recognizing the hidden NPLs implies the total NPLs in China is two to four times the reported amount.