Delegation and the regulation of U.S. financial markets

We analyze the institutional determinants of U.S. financial market regulation with a general model of the policy-making process in which legislators delegate authority to regulate financial risk at both the firm and systemic levels. The model explains changes in U.S. financial regulation leading up to the financial crisis. We test the predictions of the general model with a novel, comprehensive data set of financial regulatory laws enacted specifically between 1950 and 2009. The theoretical and empirical analysis finds that economic and political factors impact Congress’ decision to delegate regulatory authority to executive agencies, which in turn impacts the stringency of financial market regulation, and our estimation results indicate that political factors may have been stronger and resulted in inefficiencies.     

Revisiting the ICAPM under the distortion of risk–return tradeoff in short-horizon stock returns

We suggest that the distortion of the positive risk–return relation in the ICAPM is a consequence of trading by informed investors to exploit mispricing. We hypothesize and demonstrate that a non-positive (strongly positive) risk–return relation following positive (negative) market returns is attributed to short-selling (purchasing) of overpriced (underpriced) stocks along with optimistic (pessimistic) expectations conditional on good (bad) market news. We verify this asymmetry in the risk–return relation through the indirect risk–return relation conditional on good (bad) market news. We also find that the attenuation (reinforcement) of the positive risk–return relation is more profound in high- (low-) sentiment periods.     

Exchange rate dynamics and US dollar-denominated sovereign bond prices in emerging markets

Using data on Brazil, Colombia, Mexico, the Philippines, Russia and Turkey, our empirical results show that the exchange rates of their currencies have adequate explanatory power in explaining their US dollar-denominated sovereign bonds, particularly in the post-global financial crisis period. We develop a two-factor pricing model with closed-form solutions for the sovereign bonds in which the correlated factors are foreign exchange rates and US risk-free interest rates that follow a double square-root process relevant in the low interest rate environment. The numerical results and associated error analysis show that the model credit spreads can broadly track the market credit spreads.     

中国农药施用与农业经济增长脱钩状态：时空特征与影响因素

[目的]明确农药施用与农业经济增长关联状态及其影响因素,为实现"控药减害增收"的目标提供借鉴。[方法]基于2005—2015年数据利用脱钩理论和对数平均分解指数法分解进行分析。[结果]中国农业经济增长伴生大量农药施用,仅少数省域表现出农药施用和农业经济增长扩张绝对脱钩的理想状态,东北西北部分省域农业经济增长则以更大幅度的农药投入增长为代价。中西部地区劳动力规模和技术进步效应是推动农药施用与农业经济增长脱钩的因素;东部地区种植规模变化、劳动力规模和技术进步因素均是推动农药施用和农业经济增长脱钩的因素;东北地区仅劳动力规模效应成为推动脱钩的力量。[结论]推动农药施用与农业经济增长脱钩需要强化农业科技的创新与普及,完善农业生产过程中的技术支撑,推动农业病虫害监测预警,加大对环境友好型低污染农药和肥料的推广度;构建农户施药的多重约束机制,完善农业病虫灾害保险减少农户对生产过程的风险感知,发挥农业合作社对农户施药行为的规制作用,完善产品分级认证和安全准入制度;通过农地合理流转和农业机械化等方式集约利用农业生产资源;因地制宜推动农药施用与农业经济增长脱钩,结合区域资源优势和农业发展阶段有针对性地设计对策措施。     

Do Cryptocurrencies Increase the Systemic Risk of the Global Financial Market?

The advance of cryptocurrencies has sparked wide concern over their interplay with the existing global financial market. This paper analyzes the risk spillover relation between cryptocurrencies and major financial assets, and unravels how cryptocurrencies could influence global financial systemic risk. We find that cryptocurrencies function as a separate risk source from traditional assets. Major legislative, financial and technological events in the cryptocurrency market may affect risk spillover dynamics. Although the overall penetration of cryptocurrencies is not yet deep, introducing cryptocurrency can significantly increase the systemic risk to traditional markets during low risk level episodes.     

Transforming under deep uncertainty: A strategic perspective on risk management

Companies increasingly face the need for transformation in today’s rapidly changing business environment, characterized by major shifts in technology, regulation, and customer behavior. A lack of strategic risk insight and foresight leaves many incumbents insufficiently prepared in the face of such deep uncertainty. We argue that traditional risk management falls short because it predominantly focuses on strategy execution while leaving strategy formulation largely untouched. Moreover, an administrative-heavy risk management process can create strategic inertia and a misleading sense of control. In today’s dynamic business context, companies must not only increase the speed and impact of their strategy execution but also continuously explore the development of new strategies in response to disruptive events or emerging opportunities. Our research shows how leading companies develop a strategic risk management (SRM) capability to increase their resilience and agility in response to deep uncertainty. SRM takes a strategic, forward-looking perspective and focuses on strengthening processes, people, and practices for purposefully integrating risk into the strategy formulation process. This article offers a framework with three proven configurations of content and timing integration, risk management roles, and leading practices that enable effective SRM.     

农业机械化发展及其服务外包的原因分析——源自冀豫鲁3省问卷调查数据的证明

[目的]在统计描述华北平原农民的机械采纳率和机械采纳方式的基础上,分析农民的机械化需求和农机手的机械服务供给行为及其内在逻辑,从理论和实证两个维度对华北平原地区农业机械技术的特殊实现形式——服务外包做出解释。[方法]运用描述性统计分析和成本收益核算等方法,利用冀豫鲁3省779个农户和45个农机手的实地调研数据分别对农业机械化发展的前提条件和实现方式做出解释。[结果]农业劳动力成本上升与农机购置成本下降,共同刺激了农民的机械技术需求,是华北平原农业机械化快速发展的前提条件;持有农业机械的农民基于理性选择而向其他农民提供农机作业服务,是推动华北平原农业机械化以服务形式实现的主要原因。[结论]相关部门应继续探索高效的农机补贴模式,刺激农民的机械技术需求;农业机械支持政策可适当向农机合作社倾斜,提高农机手的组织化程度和服务数量与质量。     

基于生态位理论的浙江省区域农产品质量竞争力评价研究

[目的]把握区域农产品质量竞争力不仅是促进区域农产品富有竞争力的积极方法,也是稳步提升农产品质量安全的重要做法。[方法]文章运用生态位态势理论,构建了以区域为评价主体的农产品质量竞争力评价体系,并从两个层面对浙江省各地级市农产品质量竞争力进行研究。在纵向层面上,测算了各地级市农产品质量竞争力生态位宽度,对各地级市农产品质量竞争力状态进行了评价和排序。在横向层面上,测算了各地级市农产品质量竞争力生态位重叠度,对各地级市农产品质量竞争力的合作程度进行了评价与区分。最后整合运用生态位协同、生态位扩充等理论,提出浙江省各地级市提升农产品质量竞争力发展策略。[结果]通过区域农产品质量竞争力生态位宽度研究发现,杭州和宁波的农产品质量竞争力较强,其生态位宽度分别为0.103 6和0.103 2,而丽水和舟山农产品质量竞争力相对居后,其生态位宽度分别为0.079 0和0.075 6;通过区域农产品质量竞争力生态位重叠度研究发现,可将全省划分为西北平原区域、东南部沿海区域和西南部山地区域等3个区域,各区域内部地级市可通过协同合作提升农产品质量竞争力。[结论]根据各地级市生态位宽度和生态位重叠度的差异,应采取生态位扩充、生态位协同、生态位分离的策略,从而因地制宜提升区域农产品质量竞争力。     

Predicting credit card delinquencies: An application of deep neural networks

The objective of this paper is twofold. First, it develops a prediction system to help the credit card issuer model the credit card delinquency risk. Second, it seeks to explore the potential of deep learning (also called a deep neural network), an emerging artificial intelligence technology, in the credit risk domain. With real-life credit card data linked to 711,397 credit card holders from a large bank in Brazil, this study develops a deep neural network to evaluate the risk of credit card delinquency based on the client's personal characteristics and the spending behaviours. Compared with machine-learning algorithms of logistic regression, naive Bayes, traditional artificial neural networks, and decision trees, deep neural networks have a better overall predictive performance with the highest F scores and area under the receiver operating characteristic curve. The successful application of deep learning implies that artificial intelligence has great potential to support and automate credit risk assessment for financial institutions and credit bureaus.