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Macroprudential oversight, risk communication and visualization

Journal of Financial Stability 2016 27, 160-179 open access
This paper discusses the role of risk communication in macroprudential oversight and of visualization in risk communication. Beyond the increase in data availability and precision, the transition from firm-centric to system-wide supervision imposes vast data needs. Moreover, in addition to internal communication as in any organization, broad and effective external communication of timely information related to systemic risks is a key mandate of macroprudential supervisors. This further stresses the importance of simple representations of complex data. The present paper focuses on the background and theory of information visualization and visual analytics, as well as techniques within these fields, as potential means for risk communication. We define the task of visualization in risk communication, discuss the structure of macroprudential data, and review visualization techniques applied to systemic risk. We conclude that two essential, yet rare, features for supporting the analysis of big data and communication of risks are analytical visualizations and interactive interfaces. For visualizing the so-called macroprudential data cube, we provide the VisRisk platform with three modules: plots, maps and networks. While VisRisk is herein illustrated with five web-based interactive visualizations of systemic risk indicators and models, the platform enables and is open to the visualization of any data from the macroprudential data cube.

Evaluating measures of adverse financial conditions

Journal of Financial Stability 2016 27, 234-249
Timely identification and anticipation of adverse conditions in the financial system are critical for macroprudential policy. However, there is no consensus on how to evaluate the quality of systemic measures. This paper provides a framework to compare measures of systemic conditions. We illustrate the proposed tests with a case study of US measures from 1976 to 2013. We find that measures which include information from multiple markets improve identification of critical system states. However, tested measures show limited capacity to anticipate critical episodes.