It was widely acknowledged at the workshop that the United States currently lacks the technical tools to monitor and manage systemic financial risk with sufficient comprehensiveness and precision. While some of the building blocks are available, many workshop participants pointed to major gaps that remain. Andrew Lo of the Massachusetts Institute of Technology presented a simple mnemonic for capturing the range of information that a systemic risk regulator will need to monitor: namely, the “four L’s” of leverage, linkages, liquidity, and losses across the financial system. Assembling a holistic perspective will require significant additional data as well as new models and research. Myron Scholes of Stanford University pointed out that even with information on leverage and linkages, liquidity and losses can only be simulated with interacting models. Other elements identified in the workshop were capital, maturity mismatch, and risk concentrations.
Christine Cumming of the Federal Reserve Bank of New York added that risk at the firm level cannot be truly assessed unless the much broader context of overall risk positions and risk dynamics in the financial system is understood. Decision makers at financial institutions, given access to more reliable knowledge about their total risk exposure with respect to proposed actions, should be better able to manage those risks. This more complete understanding could provide help to the following:
Institutions, in recognizing how they share in creating and being affected by systemic risk;
Markets, in setting values; and
Regulators charged with moderating markets and firms.
Market efficiency will be enhanced by improved intelligence about what is going on in the system as a whole. Yaacov Mutnikas of Algorithmics observed that risk analysis has developed almost exclusively to manage firm-specific risks, and that the aggregate of firm risk is not necessarily equal to systemic risk. Firm-based analysis ideally takes into account the market responses and stresses that information about losses in other financial firms produces, so it provides partial analysis of feedback effects. Full analysis of system risks, however, must incorporate more complex interactions, which, as recent experience has shown, can be especially dangerous. Furthermore, individual firms have their own scenarios of concern, which are not necessarily those of greatest significance to the overall system. Thus, to manage systemic risk, new analysis capabilities and appropriate data will be needed.
Although this one-day workshop was not aimed at developing consensus conclusions, there were some recurring themes that are relevant for policy makers:
Today’s tools of financial risk analysis will need to be augmented to provide information needed for the regulation of systemic financial risk. As implied above, existing capabilities to value individual instruments and manage firm-specific risks and capture system-wide exposures are not a sufficient foundation for systemic risk management.
The new understanding that is necessary for systemic risk management calls for new, or extended, mathematical models. These models would be designed to capture better the extensive linkages among firms and markets, the dynamic interactions among the firms