Further, growing deviations between benchmark and production projections could highlight emerging (or declining) areas of risk. In this regard, a related area of research could address optimal ways for supervisory to assess the signal when benchmark and production model results deviate significantly from one another. Finally, these simpler models could potentially form the basis of a more dynamic, systemfocused stress test analysis that builds in the linkages and feedbacks not currently captured in the CCAR and DFAST stress testing programs. This is a short list of what I see as some important tactical issues in supervisory stress test modeling. But I also want to highlight some bigger picture issues where additional research could help guide the evolution of the supervisory stress testing regime. Recall that I framed my discussion by arguing that supervisory stress testing emerged from the experience of the financial crisis to address both the backward-looking nature of regulatory capital requirements and potential first-mover problems that an individual bank might face in cutting dividends or raising new capital during periods of emerging stress. If that’s the case, how well has the stress testing regime, as incorporated into the SCAP and now the CCAR and proposed Stressed Capital Buffer approaches, addressed these problems? Is the approach working? Does it stand up? It is easy to see that banks have more regulatory capital now than before the financial crisis.

But there is a second set of design choices about how the stress scenario impacts will be modeled. To begin, capital ratios are measured separately for individual institutions, with no attempt to capture dynamic 3/8  BIS central bankers' speeches  interactions, spillovers or specific cross-firm exposures. Similarly, outcomes for the banking sector do not interact dynamically with the macroeconomic scenarios, which are inputs to the calculations. As a result, the calculations are “stand alone” in the sense that the outcomes for any individual institution are independent of those for others in the set of stress-tested firms. Results for the banking system are therefore simply the sum of results for individual institutions, rather than capturing interactions among them. The stand-alone approach reflects the microprudential objectives of the various U.S. supervisory stress test programs, along with practical considerations. While the SCAP and CCAR/DFAST stress tests programs have strong macroprudential elements15 , in each case the results have also been used to make firm-specific supervisory judgments about capital adequacy. This individual firm application pushes towards measurement approaches that capture more detailed, firm-specific characteristics. At the same time, fully dynamic models that capture interactions and exposures among firms or that build in feedback from banking sector outcomes to the macroeconomic scenario can be informationally demanding, computationally intensive and, at the stage of model development prevailing during the SCAP and early phases of the CCAR/DFAST regime, generally would have involved higher level, “industry average” assumptions about the performance of banks under the hypothetical stressed conditions.