This paper studies the magnet effect of market-wide circuit breakers and examines its possible forms using high-frequency data from the Chinese stock index futures market. Unlike previous studies that mainly analyzed the price trend and volatility, this paper is the first to consider the intraday price jump behavior in studying the magnet effect. We find that when a market-wide trading halt is imminent, the probability of a price decrease and the level of market volatility remain stable. However, the conditional probability of observing a price jump increases significantly, leading to a higher possibility of triggering market-wide circuit breakers, which is in support of the magnet effect hypothesis. In addition, we find a significant increase in liquidity demand and insignificant change in liquidity supply ahead of a market-wide trading halt, suggesting that the deterioration of market liquidity may play an important role in explaining the magnet effect.

本文研究了新三板于2016年首次实施的分层制度对挂牌公司股票流动性、估值水平与资本投资效率的影响。实证结果表明，相比于基础层公司，进入创新层使得挂牌公司股票的实际成交交易日的间隔天数平均减少了7.71个交易日，以市净率所衡量的公司估值水平提升了11.6%。从对公司实体的长远影响来看，以投资现金流敏感度衡量的资本投资效率也得到了显著提升，并且进入创新层有效降低了融资约束引发的投资现金流敏感性。本文的研究结果表明，相比于基础层公司，新三板分层制度的实施不仅使得创新层公司的股票流动性和估值水平得到了提升，还有效地提升了公司实体的资本投资效率。

本文选用 2011-2018 年省级面板数据作为研究样本， 构建线性面板模型及面板门槛模型， 验证数字普惠金融的发展对城乡收入差距的影响及其门槛效应， 并进一步进行中介效应检验。 研究结果显示， 数字普惠金融的发展能有效缩小城乡居民收入差距， 且具有门槛效应， 在经济发展初期， 这一收敛作用效果更为明显。 中介效应分析推断出数字普惠金融能缩小城乡居民收入差距并且促进经济发展， 而经济发展水平的提升却能小幅度地扩大城乡居民收入差距， 但总体来说， 仍以数字普惠金融对城乡居民收入差距的收敛作用为主导效应。

近几年， 全球数字经济快速发展， 再加上新冠肺炎疫情的冲击， 金融机构的数字化转型已成为明显趋势。 数字经济的发展催生了海量数据需求， 促使数据行业快速成长。 而数据机构作为数据市场的重要参与者， 不断地渗入到金融服务领域之中， 改变了金融行业的结构， 推动了普惠金融的发展， 同时也产生了包括数据隐私泄露、 算法歧视、 数据垄断等在内的一系列风险。 如何做到既鼓励金融机构利用数据机构的服务实现产业赋能， 又有效规避双方合作过程中存在的风险， 成为了大数据时代金融监管的研究热点。 本文首先按照金融机构与数据机构合作的四大主要应用场景具体分析了数据机构在金融领域的功能， 以及双方在开放合作过程中存在的风险隐患。 其次， 本文选取美国、 欧盟、 英国、 新加坡、 中国香港五个代表性国家和地区详细梳理了国际上为了防范第三方数据公司为金融机构带来的风险相关的监管经验。 最后， 借鉴国际经验， 结合国内对于金融领域第三方数据公司的监管现状， 以及我国国情， 提出四点监管对策建议。

Using a comprehensive dataset of Chinese corporate bond issuances, we uncover substantial evidence of issuance overpricing: the yield spread of newly issued bonds at their first secondary-market trading day is on average 5.35 bps higher than the issuance spread. This overpricing is robust across subsamples of bond issuances with different credit ratings, maturities, issuance types, and issuer status. We further provide extensive evidence to support a hypothesis that competition among underwriters drives this overpricing through two specific channels—either through rebates to participants in issuance auctions or through direct auction bidding by the underwriters for themselves or their clients.

Studying China’s credit market, we find improved price efficiency and, paradoxically, worsening segmentation as perceived government support for state-owned enterprises (SOEs) caused non-SOE credit spreads to explode rather dramatically relative to their SOE counterparts amid government-led credit tightening. Interestingly, the post-2018 credit-market stress helped improve price efficiency within non-SOEs, while SOEs saw no such improvement and instead became sensitive to issuer-level measures of government support, marking a shift of SOE premium beyond the SOE label. We further document the real impact of the deepening credit misallocations: non-SOEs in aggregate are losing their long-standing advantage in profitability over SOEs in China.

This paper studies the economic impact of the emergence of FinTech platforms on financial intermediation. In China, platform distributions of mutual funds emerged in 2012 and grew quickly into a formidable presence. Utilizing the staggered fund entrance onto platforms, we find markedly increased flow sensitivities to performance. Akin to the winner-take-all phenomenon in the platform economy, net flow captured by top 10% performing funds more than triples its pre-platform level. This pattern of platform-induced performance chasing is further confirmed using private data from Howbuy, a top platform in China. Consistent with this added incentive of becoming top performers in the era of large-scale platforms, fund managers increase risk taking to enhance the probability of becoming top performers. Meanwhile, organizational cohesiveness of fund families weakens as platforms level the playing field for all funds.

We examine whether investor behavior can be influenced by the social norms to which they are exposed. Specifically, we test two competing hypotheses regarding the influence of social trust on the disposition effect related to mutual fund investment. On the one hand, a higher level of social trust may elicit stronger investor reactions by increasing the credibility of the performance numbers reported by funds. This results in higher flow-performance sensitivity, which mitigates investors’ tendency to sell winners and hold onto losers. On the other hand, societal trust may reduce concerns about expropriation, thereby weakening investors’ need to react to poor performance. The resulting lower flow-performance sensitivity increases the disposition effect. Based on a proprietary dataset of complete account-level trading information for all investors in a large mutual fund family in China, we find compelling evidence 1) of a significant disposition effect among fund investors; 2) that a higher degree of social trust is associated with higher flow-performance sensitivity; and 3) that (high) trust-induced flows mitigate the disposition effect. Our results suggest that, in addition to cognitive biases, investor behavior is also strongly influenced by social norms.

本文基于城投债和地方债的发行和交易数据构建了各省地方债务风险综合指标，发现各省风险有共同的趋势，存在风险联动现象。为了研究我国地方政府债务省际风险传导机制，本文运用含外生变量的结构化向量自回归模型（SVAR）来识别风险传导途径和重点风险地区。 实证发现本文设定的风险关联关系矩阵是地方债务风险传导的重要途径， 可以很好的解释地方债务风险的共同趋势。进一步地，我们通过广义预测误差方差分解衡量了各省的风险传导性， 并在此基础上通过脉冲响应分析发现吉林省风险正向冲击对其他省份有持续显著的正向影响。此外， 本文还从地方财政收入构成角度考察了影响地方债务风险传导性的主要因素。 本文的研究为防控和治理地方债务风险具有重要价值。

We study the consequences of market uncertainty on international trade. An increase in foreign market uncertainty dampens China's aggregate exports on both the extensive and intensive margins. The adverse effects are more pronounced in industries facing tighter financial constraints than in others. We propose a dynamic trade model to explain the facts. Greater uncertainty depresses a firm's expected value of exporting and borrowing capacity, leading to fewer exporters and a smaller average size of exports. Under calibrated parameters, the uncertainty shock accounts for a sizable fraction of China's trade collapse in the 2008 financial crisis and the recent trade war.