Should Bank Stress Tests Be Fair?

58 Pages Posted: 20 Jul 2022

See all articles by Paul Glasserman

Paul Glasserman

Columbia University - Columbia Business School

Mike Li

Columbia University - Columbia Business School

Date Written: June 15, 2022


Regulatory stress tests have become the primary tool for setting capital requirements at the largest U.S. banks. The Federal Reserve uses confidential models to evaluate bank-specific outcomes for bank-specific portfolios in shared stress scenarios. As a matter of policy, the same models are used for all banks, despite considerable heterogeneity across institutions; individual banks have contended that some models are not suited to their businesses. Motivated by this debate, we ask, what is a fair aggregation of individually tailored models into a common model? We argue that simply pooling data across banks treats banks equally but is subject to two deficiencies: it may distort the impact of legitimate portfolio features, and it is vulnerable to implicit misdirection of legitimate information to infer bank identity. We compare various notions of regression fairness to address these deficiencies, considering both forecast accuracy and equal treatment. In the setting of linear models, we argue for estimating and then discarding centered bank fixed effects as preferable to simply ignoring differences across banks. We present evidence that the overall impact can be material. We also discuss extensions to nonlinear models.

Keywords: Finance, Bank Stress Tests, Econometrics, Fairness, Risk Management

JEL Classification: G21, G28, C01, C10, C54

Suggested Citation

Glasserman, Paul and Li, Mike, Should Bank Stress Tests Be Fair? (June 15, 2022). Available at SSRN: or

Paul Glasserman

Columbia University - Columbia Business School ( email )

3022 Broadway
403 Uris Hall
New York, NY 10027
United States
212-854-4102 (Phone)
212-316-9180 (Fax)

Mike Li (Contact Author)

Columbia University - Columbia Business School ( email )

New York, NY
United States

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