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.     

The Effect Of Advertising Content Control On Advertising Effectiveness In The Different Forced Exposure Circumstance

With advances in new technology, various formats of online advertising (e.g., in-stream video advertising) often force e-consumers to watch the advertisement during their goal-oriented activities, and this advertising interruption often makes them feel intruded upon and irritated. To reduce such negative reactions toward involuntary advertising exposures, this study examines whether offering e-consumers the option to choose advertising content can influence ad effectiveness in different degrees of forced exposure circumstance. Using a 2 (advertising content control: customization option vs. no option) × 2 (level of forced exposure: pre-rolls vs. rich media banners) factorial experiment, the researcher noted that advertising customization features generate a greater sense of relevance and increased advertising memory, which in turn may lead to more positive attitudes toward the ad regardless of the levels of forced exposure. The findings have theoretical and practical implications on the use of involuntary advertising interruptions in the web interface.     

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.     

Litigation risk: Measurement and impact on M&A transaction terms

The purpose of the paper is to propose an original proprietary proxy of a firm's litigation risk. We extend the scope of litigation risk outside of the conflicts with shareholders and the domain of security litigation. We demonstrate that the source of the risk of litigation can be found in the firm's policies and in its management's operational or strategic decisions, even if a sector conditioning effect exists. Based on a sample of 465 US M&A transactions between 2000 and 2014, we provide evidence that the level of litigation risk, at the acquirer's level, has a positive and significant impact on the takeover premium. We also provide evidence that a significant relationship exists between the acquirer's litigation risk and the means of payment. An extension of the sample to international transactions is used as a robustness check; it confirms the previous results.     

Uncertainty,Control, and Karl Polanyi’s Protective Response

Post-Keynesian institutionalist economists like Wallace Peterson and John Kenneth Galbraith recognized that the impact of uncertainty on economic wellbeing depends in part on the degree of control people have over the sources and consequences of it. Given the inability of government and other large institutions to reduce uncertainty or to provide citizens with the ability to manage it, mediating structures are considered as an alternative means of promoting economic security. The article concludes by describing and evaluating several of these alternatives.