Who benefits in a crisis? Evidence from hedge fund stock and option holdings

We use a unique data set of hedge fund long equity and equity option positions to investigate a significant lockup-related premium earned during the tech bubble (1999–2001) and financial crisis (2007–2009). Net fund flows are significantly greater among lockup funds during crisis and noncrisis periods. Managers of hedge funds with locked-up capital trade opportunistically against flow-motivated trades of non-lockup managers, consistent with a hypothesis of rent extraction in providing crisis era liquidity. The success of this opportunistic trading is concentrated during periods of high borrowing costs, in less liquid stock markets, and is enhanced by hedging in the equity option market.     

Switching costs and financial stability

We establish that the effect of intensified deposit market competition, measured by reduced switching costs, on the probability of bank failures depends critically on whether we focus on competition with established customer relationships or competition for the formation of such relationships. With inherited customer relationships, intensified competition due to lower switching costs destabilizes the banking market, whereas it stabilizes the market if we focus on competition for the formation of customer relationships. We characterize the factors important for evaluating the effects of intensified competition on stability in a market with unattached as well as locked-in depositors.     

国家科技创新能力时空差异性评价

科技创新规模扩张和科技创新效率提升是增强国家科技创新能力的两条关键途径。基于现有研究鲜有结合科技创新规模和科技创新效率开展国家科技创新能力评价的现状，采用因子分析法，系统筛选国家科技创新规模影响因素，并结合科技创新效率影响因素，完善国家科技创新能力评价指标体系，通过构建DEA Malmquist指数模型，评价不同时期国家科技创新效率变化指数，以及中国与全球10个国家科技创新能力的时空差异性。研究表明，R&D投入强度、R&D研究人员、专利申请量、科技期刊文章数、高科技产品出口额占制成品出口总额的百分比、科技创新效率是影响国家科技创新能力的关键指标；1991-2014年中国科技创新能力水平呈指数增长态势，有力提升了国家科技实力；全球10个国家科技创新能力水平除日本出现一定波动外，其余九国整体呈小幅递增态势。     

科技创新与金融创新耦合系统脆弱性及政府干预

从理论上论述了政府干预科技创新与金融创新耦合系统脆弱性的必要性、途径及作用机制。基于以耦合系统内部结构为表征的实体子系统脆弱性和以公共创新环境、耦合系统综合效益为测评工具的虚像子系统脆弱性3个维度构建耦合系统脆弱性指数，分别采用静态面板固定效应回归及动态面板两阶段系统GMM回归，实证检验了我国政府干预对耦合系统脆弱性的实质影响。研究表明：在各类干预举措中，政府采购政策与知识产权保护政策效应明显，特别是知识产权保护政策效应潜力巨大；财政政策领域明显存在过度干预现象，其它政策效应或不显著或有违初衷，亟待调整与完善。     

社保基金持股与企业盈余质量:A股上市公司的证据

本文利用中国A股上市公司2006-2015年的数据,研究社保基金持股对上市公司盈余质量的影响。我们用上市公司财务重述作为测度盈余质量的指标,发现社保基金持股能够显著降低企业发布财务重述的概率,这表明社保基金对上市公司盈余质量的提高具有促进作用。并且,社保基金的这一治理作用在国有企业、内部治理水平较差以及市场化程度较低地区的上市公司中更加显著。通过双重差分模型和安慰剂检验等方法弱化了内生性问题之后,以上结论依然成立,说明社保基金持股和盈余质量提升之间存在因果关系,我们称之为社保基金的公司治理作用。进一步研究发现,社保基金可以通过抑制控股股东资金占用、增加机构调研次数等途径提升被持股公司的盈余质量。本文有助于认识和评估社保基金持股对于上市公司的监督与治理作用。     

Reverse Payments and Risk of Bankruptcy Under Private Information

Abstract

In the pharmaceutical industry, a reverse payment (pay-for-delay) is a payment from an originator to a generic producer to delay her entry. In some recent cases, the US and EU antitrust authorities have banned these agreements per se, while in others they have used a rule of reason. This paper analyzes their dynamic effects and shows that a ban per se may reduce consumer surplus when the generic producer may go bankrupt and her financial situation is private information. Reverse payments are more beneficial when competition among few players is soft, the economy is in a downturn, and the period of drug usage after patent expiry is long. Results suggest that a rule of reason is more suited than a ban per se.     

信贷管制、隐性契约与贷款利率变相市场化——现象与解释

本文将视角聚焦于利率市场化改革之前,重点研究金融抑制对银企信贷契约的异化。研究发现,在金融抑制背景下银企之间存在以留存贷款为表现的隐性契约,用以帮助银行在满足管制要求的同时追求利润最大化。本文对这一现象进行了理论分析与实证检验,发现隐性契约的发生与否会随着货币政策、企业特征等因素的改变而有所差异,这在一定程度上起到了利率变相市场化的作用。进一步研究则发现,这一隐性契约对企业价值产生了负向影响。     

A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.