Industry Expertise,Information Leakage and the Choice of M&A Advisors

This paper examines the impacts of M&A advisors’ industry expertise on firms’ choice of advisors in mergers and acquisitions. We show that an investment bank's expertise in merger parties’ industries increases its likelihood of being chosen as an advisor, especially when the acquisition is more complex, and when a firm in M&A has less information about the merger counterparty. However, due to the concerns about information leakage to industry rivals through M&A advisors, acquirers are reluctant to share advisors with rival firms in the same industry, and they are more likely to switch to new advisors if their former advisors have advisory relationship with their industry rivals. In addition, we document that advisors with more industry expertise earn higher advisory fees and increase the likelihood of deal completion.     

The premium of dynamic trading in a discrete-time setting

Chiu and Zhou [Quant. Finance, 2011, 11, 115–123] show that the inclusion of a risk-free asset strictly boosts the Sharpe ratio in a continuous-time setting, which is in sharp contrast to the static single-period case. In this paper, we extend their work to a discrete-time setting. Specifically, we prove that the multi-period mean-variance efficient frontier generated by both risky and risk-free assets is strictly separated from that generated by only risky assets. As a result, we demonstrate that the inclusion of a risk-free asset strictly enhances the best Sharpe ratio of the efficient frontier in a multi-period discrete-time setting. Furthermore, we offer an explicit expression for the enhancement of the best Sharpe ratio, which was referred to as the premium of dynamic trading by Chiu and Zhou [op. cit.], although they do not present a computational formula for it. Our results further show that, in the case with a risk-free asset, if an investor can extract some money from his initial wealth at time 0, the efficient frontier with a risk-free asset can be tangent to that without a risk-free asset. Finally, based on real data from the American market, a numerical example is provided to illustrate the results obtained in this paper; a numerical comparison between the discrete-time case and the continuous-time case is also provided. Our numerical results reveal that the continuous-time model can be considered to be a limit of the discrete-time model.     

环境灾害冲击对银行违约率的影响效应研究:理论与实证分析

本文通过模型模拟和基于中国数据的实证检验,分析了环境灾害损失冲击对于银行违约率的影响。本文模型模拟的结果显示,环境灾害冲击会显著提升银行体系的违约率水平,同时伴随着企业融资溢价水平的提升以及整个经济活动的萎缩;实证研究发现:环境灾害损失冲击会导致银行违约率水平显著提升。且与理论分析一致,本文实证发现宏观经济不确定性水平、企业的资本折损以及全要素生产率的下降在环境灾害影响银行违约率的过程中发挥了显著的传导作用。进一步研究发现,环境灾害冲击及其导致的银行违约率上升还会降低银行的风险偏好水平,降低放贷规模和主动风险承担,并反作用于实体企业,提升企业的融资约束和成本。本文的研究结论丰富了基于中国视角的环境物理风险研究,刻画了环境灾害损失对于银行风险的影响及其后续效应,为政策部门防范气候环境风险提供了借鉴。     

Predicting Prepayment and Default Risks of Unsecured Consumer Loans in Online Lending

Online lending provides a means of fast financing for borrowers based on their creditworthiness. However, borrowers may undermine this agreement due to early repayment or default, which are two major concerns for the platform and lenders, since both affect the profitability of a loan. While default risk is frequently focused on credit scoring literature, prepayment has received much less attention, despite a higher prepayment rate being observed in online lending when compared with default. This article uses multivariate logistic regression to predict the probability of both the underlying prepayment and default risks. Real consumer lending data of 140,605 unsecured loans provides evidence that these two events have their own distinct patterns. We consider systemic risk by incorporating macroeconomic factors in modeling and address the influence of economic conditions, which are lessons learnt from the last financial crisis. The out-of-sample validation has shown that both prepayment and default can be accurately predicted. This article highlights the necessity of regulations on prepayment given the fast growing online lending market.     

When is upstream collusion profitable?

Motivated by the recent antitrust cases in which Japanese auto parts suppliers colluded to raise supply prices against their long‐term collaborators, the Japanese carmakers, we study the conditions under which an upstream collusion is profitable even after compensating downstream direct purchasers. Oligopoly competition in successive industries is shown to give rise to a vertical externality and a horizontal externality. If a collusive price of intermediate goods better balances the two externalities, the collusion will raise the joint profit of all firms in the two industries and is therefore profitable for the upstream after compensation of downstream firms.     

家庭债务与居民消费：一个文献综述

近年来我国家庭杠杆率快速上升,家庭债务与居民消费关系引发热议,相关文献 反映出：（1）家庭适度负债能促进消费增长;（2）家庭杠杆率上升存在临界值;（3）快速加 杠杆是主要风险来源;（4）识别家庭债务异质性可以缓解信贷约束。目前我国家庭杠杆率依 然处于合理区间,但需重视快速加杠杆带来的风险隐患。为保持居民消费平稳增长,本文提出 从供给侧优化金融条件,从需求侧约束快速加杠杆行为,并发挥减税的收入调节作用等建议。     

行政法视域下的信用惩戒若干基本理论问题——兼论我国《行政处罚法》增设“信用惩戒条款”的可行性

行政主体以履行行政管理职责和提供公共服务为目的,依托负面信用信息给予相对人以惩处的一类行政行为,可用“信用惩戒”来指称.完整的信用惩戒呈现阶段性法律构造,包括失信信息归集、评价、列入、公布、惩处、约束等阶段,平衡论可为其提供理论支撑.运用行政过程论分析法律性质后发现,信用惩戒具有制裁性,必须明确其制度依据.该目的只有通...     

重大突发公共卫生事件公益性捐赠个人所得税税前扣除问题研究

公益性捐赠税前扣除对于促进重大突发公共卫生事件中的公益性捐赠有着重要作用.新冠疫情期间,国家从扣除比例、捐款程序、发票等方面放宽了公益性捐赠税前扣除的限制,有效激励了疫情期间的公益性捐赠.但仍然存在捐赠品界定不合理、不清晰,税收优惠集中于疫中支持,税收优惠缺乏稳定法律法规体系等问题.本文通过借鉴美国相关经验,提出了我国重大突发公共卫生事件中公益性捐赠个税扣除体系构建思路.     

关联担保、被担保企业的盈余特征与担保企业的债务契约

本文从担保视角考察了被担保企业的盈余特征对担保企业债务契约的影响,以及双方的关联关系在其中的作用。实证检验发现,被担保企业盈余质量越高,担保企业获取的债务契约越有利,银行能够部分识别被担保企业的盈余信息,盈余信息对银行是有利用价值的。进一步研究发现,当担保双方具有关联关系时,被担保企业的盈余特征与担保企业的债务契约之间的关系会弱化,关联关系事实上部分替代了企业盈余特征所起到的信息作用。     

劳动力保护与企业风险——来自2008年新《劳动合同法》的证据

本文利用2003—2015年我国A股上市公司数据,借助2008年新《劳动合同法》的实施对劳动密集度不同的行业影响不同,识别了劳动力保护对以股价波动性衡量的企业风险的因果影响。结果显示,受新《劳动合同法》实施影响越大的企业,其股价波动性越小,即劳动力保护降低了企业风险。这一结论在经过平行趋势检验、排除同期其它政策的影响、使用不同方法计算企业风险和劳动密集度、使用平衡面板等一系列稳健性检验后,仍然成立。机制分析表明,新《劳动合同法》的实施会增加企业的杠杆率和违约概率,企业出于“风险规避”的动机会增加现金持有,以抓住未来的优良投资机会。由于国有企业对劳动力保护制度的执行度更强,杠杆率高和流动比率低的企业有更强的“风险规避”动机,因此新《劳动合同法》实施后,国有企业风险出现更大幅度的下降。本文的结论表明,在防范控制企业风险过程中,劳动力保护措施是可选的有效政策工具。