COMMENTS ON: RETHINKING FINANCIAL STABILITY BY AIKMAN, HALDANE, HINTERSCHWEIGER AND KAPADIA

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COMMENTS ON: RETHINKING FINANCIAL STABILITY BY AIKMAN, HALDANE, HINTERSCHWEIGER AND KAPADIA Jeremy Stein Harvard University Peterson Institute Rethinking Macro Policy Conference October 12-13, 2017

DOES IT MAKE SENSE TO HAVE MULTIPLE CONSTRAINTS ON BANK EQUITY CAPITAL? Leading example: banks face both a risk-based capital requirement and an unweighted leverage ratio. SLR has significantly tightened the latter constraint. Arguments against: If leverage ratio binds, all assets are given same risk weight distort away from safe and towards risky. Clear evidence this is happening e.g. in Treasury repo, FX basis market, etc. If banks are heterogeneous, and constraints bind differentially, create incentives for business to migrate in a potentially inefficient manner. E.g. Wells Fargo is more bound by risk-based constraint, so it starts doing more RWA-light broker-dealer type activities. Goldman Sachs is more bound by leverage ratio, so it starts doing more RWAintensive banking activities. Some evidence this migration is happening as well. 2

TABLE 1: DISTANCE FROM REQUIREMENTS Distance from Requirement (%) CCAR SLR Tier 1 Ratio Tier 1 Ratio CCAR SLR G-SIBs: JPMorgan Chase 2.2 1.5 2.4 0.9 Bank of America 2.1 2.0 2.4 1.3 Citigroup Inc. 4.3 2.6 3.5 1.5 Morgan Stanley 8.5 1.4 4.3 0.2 Goldman Sachs 5.6 1.5 2.2 0.1 Wells Fargo 2.3 2.6 3.0 2.3 Bank of New York Mellon 4.5 1.0 5.6 1.8 State Street 4.7 0.9 3.1 0.6 Other Large BHCs: U.S. Bancorp 2.5 4.3 1.9 2.2 PNC Financial Services 3.5 5.6 1.6 2.4 Capital One Financial 3.1 5.5 1.1 2.4 HSBC North America 11.6 4.3 5.6 1.0 TD Group US 5.2 4.1 5.3 2.8 3

TABLE 4: ESTIMATED CAPITAL CHARGES First, pick the most binding constraint (SLR, Tier 1, etc.) for each bank Then compute capital charge under that constraint KK bbbb = kk bb ωω ii, G-SIB Banks: Tightest constraint C&I Capital Charge for asset i bank b Risk weight for i Minimum capital ratio for most binding constraint Residential Mortgages Other Mortgages Credit Cards Other Consumer Treasuries JPMorgan Chase & Co. CCAR SLR 5.7 1.1 5.7 2.8 2.4 1.3 Bank of America Corporation CCAR SLR 5.7 1.1 5.7 2.8 2.4 1.3 Citigroup Inc. CCAR SLR 5.7 1.1 5.7 2.8 2.4 1.3 Morgan Stanley CCAR SLR 5.7 1.1 5.7 2.8 2.4 1.3 Goldman Sachs Group, Inc. CCAR SLR 5.7 1.1 5.7 2.8 2.4 1.3 Wells Fargo & Company Tier 1 Ratio 10.5 5.3 10.5 10.5 10.5 0.0 Bank of New York Mellon Corporation SLR 5.0 5.0 5.0 5.0 5.0 5.0 State Street Corporation CCAR SLR 5.7 1.1 5.7 2.8 2.4 1.3 Other Large BHCs: U.S. Bancorp CCAR Tier 1 Ratio 8.7 1.1 8.7 5.8 5.4-1.7 PNC Financial Services Group, Inc. CCAR Tier 1 Ratio 8.7 1.1 8.7 5.8 5.4-1.7 Capital One Financial Corporation CCAR Tier 1 Ratio 8.7 1.1 8.7 5.8 5.4-1.7 HSBC North America Holdings Inc. CCAR SLR 5.7 1.1 5.7 2.8 2.4 1.3 TD Group US Holdings LLC CCAR SLR 5.7 1.1 5.7 2.8 2.4 1.3 4

TABLE 5: RELATIVE RISK WEIGHTS Scale by Capital Charge on C&I: GSIB Banks: Tightest constraint C&I Residential Mortgages Other Mortgages Credit Cards Other Consumer Treasuries JPMorgan Chase & Co. CCAR SLR 100 19 99 49 42 23 Bank of America Corporation CCAR SLR 100 19 99 49 42 23 Citigroup Inc. CCAR SLR 100 19 99 49 42 23 Morgan Stanley CCAR SLR 100 19 99 49 42 23 Goldman Sachs Group, Inc. CCAR SLR 100 19 99 49 42 23 Wells Fargo & Company Tier 1 Ratio 100 50 100 100 100 0 Bank of New York Mellon Corporation SLR 100 100 100 100 100 100 State Street Corporation CCAR SLR 100 19 99 49 42 23 Other Large BHCs: U.S. Bancorp CCAR Tier 1 Ratio 100 13 100 67 62-19 PNC Financial Services Group, Inc. CCAR Tier 1 Ratio 100 13 100 67 62-19 Capital One Financial Corporation CCAR Tier 1 Ratio 100 13 100 67 62-19 HSBC North America Holdings Inc. CCAR SLR 100 19 99 49 42 23 TD Group US Holdings LLC CCAR SLR 100 19 99 49 42 23 5

FIGURE 2: CONVERGENCE IN BANK BALANCE SHEETS Regress Δ 2012-2016 (RWA/A) vs. (RWA/A) 2012 : β = -0.25; ρ = -0.71. Can instrument for (RWA/A) 2012 with old (RWA/A) 2002 : β = -0.23. 6

DOES IT MAKE SENSE TO HAVE MULTIPLE CONSTRAINTS ON BANK EQUITY CAPITAL? Arguments in favor (this paper): Knightian uncertainty: difficult to estimate correct risk weights. Makes sense not to over-rely on one model. But can have a single constraint with risk weights that average over multiple models. Will probably lead to generally higher risk weights for low-risk assets, in spirit of leverage ratio. Key point: with a single constraint, all banks face the same set of averaged risk weights. With multiple constraints, different banks face different weights, each of which is individually wrong. Risk-based requirements can be easily gamed. Any rule that is set in stone can be easily gamed! This is a fundamental problem for entirely ex ante rules-based approach. Not fixed by adding more rules. Suggests using stress tests as way to fill in contingencies ex post: look where banks are growing rapidly, making abnormal profits then stress those exposures. Completely agree that should reduce reliance on banks internal models in any risk-based regime. 7

GENERAL MESSAGE Advocates of multiple constraints and leverage ratio in particular raise several important issues that absolutely need to be taken on. But these issues can be more efficiently addressed by improving the existing risk-based regime on various dimensions. More robust risk weights for lower risk assets. Less reliance on banks internal models. More explicit use of stress tests to fill in contingencies and combat gaming. Maintaining a too-aggressively-calibrated leverage ratio alongside the riskbased regime creates an unnatural incentive for all players to converge towards a universal banking model. Finally, to the extent that tough leverage ratio reflects a general desire to be more hawkish on overall capital levels, there are better ways to go: Dial up G-SIB surcharges. And/or increase TLAC requirements. 8