Institutional investor horizon and stock price synchronicity: Do product market competition and analyst coverage matter?

This paper provides new insights into the relation between institutional investment horizon and stock price synchronicity and investigates whether this relationship depends on the intensity of product market competition and analyst coverage. Based on a sample of French listed companies, we find that long-term (short-term) institutional investors are associated with lower (higher) stock price synchronicity. The results also show that the negative effect of long-term institutional investors is more accentuated for firms in less competitive markets and with high analyst coverage. An additional analysis shows that the synchronicity reduction effect does not vary during the financial crisis. Overall, these findings suggest that unlike their short-term counterparts, long term investors reduce asymmetric information and help disseminate firm-specific information into stock prices.     

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.     

银行业联合授信制度制约企业的非效率投资了吗*——基于沪深A股公司的分析

中国银保监会出台联合授信管理制度旨在抑制企业过度融资行为，提高资金使用效率。为检验该制度是否达到预期效果，采用2014—2018年沪深A股上市公司样本，运用非平衡面板数据回归实证考察联合授信机制对企业非效率投资的影响，发现联合授信对企业的非效率投资（包含投资不足和投资过度）呈现显著抑制效应，其中联合授信对投资过度的抑制效应最大。进一步研究发现，相较于国有、大规模、低负债、高盈利等异质属性的企业，联合授信对非国有、小规模、高负债、低盈利等属性企业的非效率投资（尤其是投资过度）抑制效应更为显著。     

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.     

Farm Capital Investment and Deviations from the Optimal Path

We identify farms’ optimal investment path in capital assets and compare it with their actual investment to assess the direction and extent of deviation from the optimal investment. A probit model is further used to investigate the determinants of the probability that a farmer over‐ or under‐invests in capital assets. We use a panel dataset of Dutch dairy farms over the period 2003–2013, and find that most farms under‐invest in capital assets during the study period. Although the number of farms that had over‐invested in capital assets is relatively small, these farms account for the biggest share of total investment in capital assets. The probit results show that liquidity, agricultural support payments, age, land tenure and standard output size are important variables explaining the likelihood of over‐and under‐investment.     

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.     

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.