[We examine the effects of price disclosure on market performance in a continuous experimental multiple-dealer market in which seven professional market makers trade a single security. The dealers trade with one another and with computerized informed and liquidity traders. Our key comparison is between fully public price queues (pretrade transparent market) and bilateral quoting (pretrade opaque). We find that opening spreads are wider and trading volume is lower in the opaque markets due to higher search costs there. More importantly, however, higher search costs also induce more aggressive pricing strategies, so that price discovery is much faster in the opaque markets.]

This paper provides an overview of visual analytics—the science of analytical reasoning enhanced by interactive visualizations tightly coupled with data analytics software—and discusses its potential benefits in monitoring systemic financial stability. The core strength of visual analytics is to combine visualization's high-bandwidth information channel to the human analyst with the flexibility and power of rapid-iteration analytics. This combination is especially valuable in the context of macroprudential supervision, which is increasingly dominated by large volumes of dynamic and heterogeneous data. Our contribution is to describe and categorize the analytical challenges faced by macroprudential supervisors, and to indicate where and how visual analytics can increase supervisors’ comprehension of the data stream, helping to transform it into actionable knowledge to support informed decision- and policy-making. The paper concludes with suggestions for a research agenda.

We examine the effects of price disclosure on market performance in a continuous experimental multiple-dealer market in which seven professional market makers trade a single security. The dealers trade with one another and with computerized informed and liquidity traders. Our key comparison is between fully public price queues (pretrade transparent market) and bilateral quoting (pretrade opaque). We find that opening spreads are wider and trading volume is lower in the opaque markets due to higher search costs there. More importantly, however, higher search costs also induce more aggressive pricing strategies, so that price discovery is much faster in the opaque markets.

We develop metrics to assess the complexity of a bank holding company (BHC), based on its ownership structure. Large BHCs have intricate ownership hierarchies involving hundreds or even thousands of legal entities that may contribute to increased operational risk and greater opacity. Our measures are mathematically grounded, intuitive, and easy to implement. They may be particularly useful in the context of resolution, where regulators often face significant time pressure and coordination challenges. We use regulatory filing data from the Federal Reserve to validate the measures, demonstrating that they provide a useful complement to balance sheet information in assessing BHC complexity. Notably, the proposed measures are highly correlated with existing complexity indicators that are not based on organizational structure and are less correlated with size than these existing complexity measures. We show that the proposed measures provide additional explanatory power for the regulatory indicators, even after controlling for size.