Systemic risk
How much each big US bank co-moves with system-wide tail risk
Four academic market-based measures, computed from bank equity returns only: LRMES (the returns-based core of SRISK), MES, Delta-CoVaR, and the system-level absorption ratio. This is not a dollar SRISK capital-shortfall level (that needs consolidated-holding-company market cap and book debt, which this repo does not hold), and it is not investment advice.
Data as of Jul 6, 2026 (system-mean LRMES from bank equity returns)
Systemic risk
System-mean LRMES barely moved through the COVID crash
Source: FinObservatory systemic engine (absorbed from argus), current revision Month-end mean across covered banks; GARCH(1,1)+DCC(1,1) filter, Brownlees-Engle 2017. Methodology
Top LRMES contributors
The ten banks with the highest latest LRMES, the returns-based systemic-vulnerability core of SRISK. Share is each bank’s LRMES as a fraction of the aggregate across all 28 covered banks. Regionals dominate the top of the list, consistent with the 2023 episode.
| # | Bank | LRMES | LRMES share | MES |
|---|---|---|---|---|
| 1 | ZION Zions Bancorporation, N.A. | 0.4960 | 4.9% | -0.0464 |
| 2 | WAL Western Alliance Bancorporation | 0.4952 | 4.9% | -0.0597 |
| 3 | CFG Citizens Financial Group, Inc. | 0.4464 | 4.4% | -0.0314 |
| 4 | RF Regions Financial Corporation | 0.4331 | 4.3% | -0.0318 |
| 5 | HBAN Huntington Bancshares Incorporated | 0.4304 | 4.2% | -0.0282 |
| 6 | ALLY Ally Financial Inc. | 0.4283 | 4.2% | -0.0354 |
| 7 | FITB Fifth Third Bancorp | 0.4124 | 4.0% | -0.0298 |
| 8 | FHN First Horizon Corporation | 0.4093 | 4.0% | -0.0380 |
| 9 | EWBC East West Bancorp, Inc. | 0.4090 | 4.0% | -0.0344 |
| 10 | KEY KeyCorp | 0.4068 | 4.0% | -0.0308 |
Source: FinObservatory systemic engine (absorbed from argus), current revision Each bank at its own most-recent observation; LRMES per Brownlees-Engle 2017, MES per Acharya et al. 2017. Methodology
Delta-CoVaR leaders
Banks whose own distress most worsens the system’s tail Value-at-Risk (most negative first). Delta-CoVaR weights toward the largest, most-connected names, a different lens from LRMES.
| # | Bank | Delta-CoVaR | As of |
|---|
Source: FinObservatory systemic engine (absorbed from argus), current revision Rolling quantile regression, 252-day window, q = 0.05; Adrian-Brunnermeier 2016. Methodology
Systemic risk
Bank co-movement spiked during the COVID crash
Source: FinObservatory systemic engine (absorbed from argus), current revision Rolling PCA, top 20% of eigenvalues, 27-bank fresh panel; Kritzman et al. 2011. Shaded: COVID crash and the 2023 SVB / regionals episode. Methodology
All covered banks
Every covered bank at its own most-recent observation. Click a column header to sort; click a row to expand its four measures and definitions. A single dashboard rather than per-bank pages: the universe is small (28 banks) and the listed-BHC tickers do not map cleanly onto the FDIC subsidiary-bank CERTs used by the bank scorecards.
| Bank | |||
|---|---|---|---|
| 0.4960 | 4.9% | -0.0464 | |
| 0.4952 | 4.9% | -0.0597 | |
| 0.4464 | 4.4% | -0.0314 | |
| 0.4331 | 4.3% | -0.0318 | |
| 0.4304 | 4.2% | -0.0282 | |
| 0.4283 | 4.2% | -0.0354 | |
| 0.4124 | 4.0% | -0.0298 | |
| 0.4093 | 4.0% | -0.0380 | |
| 0.4090 | 4.0% | -0.0344 | |
| 0.4068 | 4.0% | -0.0308 | |
| 0.3975 | 3.9% | -0.0270 | |
| 0.3932 | 3.9% | -0.0256 | |
| 0.3900 | 3.8% | -0.0272 | |
| 0.3878 | 3.8% | -0.0281 | |
| 0.3755 | 3.7% | -0.0263 | |
| 0.3724 | 3.7% | -0.0454 | |
| 0.3716 | 3.6% | -0.0374 | |
| 0.3508 | 3.4% | -0.0426 | |
| 0.3338 | 3.3% | -0.0181 | |
| 0.3101 | 3.0% | -0.0265 | |
| 0.2976 | 2.9% | -0.0234 | |
| 0.2912 | 2.9% | -0.0310 | |
| 0.2905 | 2.9% | -0.0126 | |
| 0.2755 | 2.7% | -0.0148 | |
| 0.2705 | 2.7% | -0.0137 | |
| 0.2595 | 2.5% | -0.0218 | |
| 0.2529 | 2.5% | -0.0196 | |
| 0.1972 | 1.9% | -0.0229 |
Source: Equity returns via Yahoo Finance (argus collector), internal use LRMES/MES/CoVaR/Delta-CoVaR from bank equity returns; internal-use Yahoo-derived input, display aggregates only. Methodology
G-SIB designations
The official supervisory counterpart to the market-based measures above: the Financial Stability Board’s annual list of global systemically important banks and their capital-surcharge buckets, a higher bucket meaning a higher systemic tier. The 2025 list names 29 banks; JP Morgan Chase sits alone in the top occupied bucket (4). These are consolidated holding-company designations, so the names are not linked to the FDIC-subsidiary bank scorecards, which key on insured-bank CERTs, a different legal entity.
FSB 2025 list, by bucket
| Bucket | Banks |
|---|---|
| 41 | JP Morgan ChaseUSA |
| 34 | Bank of AmericaUSA, CitigroupUSA, HSBCGBR, Industrial and Commercial Bank of ChinaCHN |
| 29 | Agricultural Bank of ChinaCHN, BNP ParibasFRA, Bank of ChinaCHN, BarclaysGBR, China Construction BankCHN, Goldman SachsUSA, Groupe Crédit AgricoleFRA, Mitsubishi UFJ FGJPN, UBSCHE |
| 115 | Bank of CommunicationsCHN, Bank of New York MellonUSA, Deutsche BankDEU, Groupe BPCEFRA, INGNLD, Mizuho FGJPN, Morgan StanleyUSA, Royal Bank of CanadaCAN, SantanderESP, Société GénéraleFRA, Standard CharteredGBR, State StreetUSA, Sumitomo Mitsui FGJPN, Toronto DominionCAN, Wells FargoUSA |
Bucket history, 2011–2025
Each cell is the bank’s FSB bucket that year; a brighter fill is a higher bucket (larger capital surcharge). A blank cell means the bank was not on that year’s list. The 2011 column carries no bucket (the FSB introduced buckets in 2012), so it marks designation only. Current members first, then banks that have since left the list.
| Bank | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| JP Morgan ChaseUSA | · | 4 | 4 | 4 | 4 | 4 | 4 | 4 | 4 | 3 | 4 | 4 | 4 | 4 | 4 |
| Bank of AmericaUSA | · | 2 | 2 | 2 | 2 | 3 | 3 | 2 | 2 | 2 | 2 | 3 | 3 | 2 | 3 |
| CitigroupUSA | · | 4 | 3 | 3 | 3 | 4 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 |
| HSBCGBR | · | 4 | 4 | 4 | 4 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 |
| Industrial and Commercial Bank of ChinaCHN | 1 | 1 | 1 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 3 | ||
| Agricultural Bank of ChinaCHN | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 2 | 2 | 2 | |||
| Bank of ChinaCHN | · | 1 | 1 | 1 | 1 | 1 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 |
| BarclaysGBR | · | 3 | 3 | 3 | 3 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 |
| BNP ParibasFRA | · | 3 | 3 | 3 | 3 | 3 | 2 | 2 | 2 | 2 | 3 | 2 | 2 | 2 | 2 |
| China Construction BankCHN | 1 | 1 | 2 | 1 | 1 | 2 | 2 | 1 | 2 | 2 | 2 | ||||
| Goldman SachsUSA | · | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 1 | 2 | 2 | 2 | 2 | 2 |
| Groupe Crédit AgricoleFRA | · | 1 | 2 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 2 | 2 |
| Mitsubishi UFJ FGJPN | · | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 |
| UBSCHE | · | 2 | 2 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 2 | 2 | 2 |
| Bank of CommunicationsCHN | 1 | 1 | 1 | ||||||||||||
| Bank of New York MellonUSA | · | 2 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Deutsche BankDEU | · | 4 | 3 | 3 | 3 | 3 | 3 | 3 | 2 | 2 | 2 | 2 | 2 | 2 | 1 |
| Groupe BPCEFRA | · | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |
| INGNLD | · | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Mizuho FGJPN | · | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Morgan StanleyUSA | · | 2 | 2 | 2 | 2 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Royal Bank of CanadaCAN | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ||||||
| SantanderESP | · | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Société GénéraleFRA | · | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Standard CharteredGBR | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |
| State StreetUSA | · | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Sumitomo Mitsui FGJPN | · | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Toronto DominionCAN | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ||||||||
| Wells FargoUSA | · | 1 | 1 | 1 | 1 | 2 | 2 | 2 | 2 | 1 | 1 | 1 | 1 | 1 | 1 |
| Credit SuisseCHE(left 2022) | · | 2 | 2 | 2 | 2 | 2 | 1 | 1 | 1 | 1 | 1 | 1 | |||
| UniCreditITA(left 2022) | · | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |||
| NordeaSWE(left 2017) | · | 1 | 1 | 1 | 1 | 1 | 1 | ||||||||
| Royal Bank of ScotlandGBR(left 2017) | · | 2 | 2 | 2 | 1 | 1 | 1 | ||||||||
| BBVAESP(left 2014) | 1 | 1 | 1 | ||||||||||||
| CommerzbankDEU(left 2011) | · | ||||||||||||||
| DexiaBEL(left 2011) | · | ||||||||||||||
| Lloyds Banking GroupGBR(left 2011) | · |
Designation history, 2011–2025
A bucket is a capital-surcharge tier: higher means more systemic. The 29 null buckets are an explicit state, not zero and not an unlisted bank: they are the 2011 designation-only rows, before the FSB began publishing bucket assignments in 2012.
All 29 null buckets are 2011 designation-only rows: the FSB named G-SIBs that year but did not begin publishing bucket assignments until 2012.
Year-to-year list changes
Entries and exits are computed mechanically from adjacent annual lists. A bank is an exit only when it is present in year N and absent in year N+1, so the table stops at the 2025 list and does not infer a departure after the latest publication.
| Transition | Banks on list | Entries | Exits | Bucket changes |
|---|---|---|---|---|
| 2011 to 2012 | 29 to 28 | BBVAESP, Standard CharteredGBR | CommerzbankDEU, DexiaBEL, Lloyds Banking GroupGBR | First published buckets: 26 continuing 2011 designations, bucket 1 (12), bucket 2 (8), bucket 3 (2), bucket 4 (4). |
| 2012 to 2013 | 28 to 29 | Industrial and Commercial Bank of ChinaCHN | none | Moved up: Groupe Crédit Agricole 1 to 2FRA Moved down: Bank of New York Mellon 2 to 1USA, Citigroup 4 to 3USA, Deutsche Bank 4 to 3DEU |
| 2013 to 2014 | 29 to 30 | Agricultural Bank of ChinaCHN | none | Moved down: Groupe Crédit Agricole 2 to 1FRA, UBS 2 to 1CHE |
| 2014 to 2015 | 30 to 30 | China Construction BankCHN | BBVAESP | Moved down: Royal Bank of Scotland 2 to 1GBR |
| 2015 to 2016 | 30 to 30 | none | none | Moved up: Bank of America 2 to 3USA, Citigroup 3 to 4USA, Industrial and Commercial Bank of China 1 to 2CHN, Wells Fargo 1 to 2USA Moved down: Barclays 3 to 2GBR, HSBC 4 to 3GBR, Morgan Stanley 2 to 1USA |
| 2016 to 2017 | 30 to 30 | Royal Bank of CanadaCAN | Groupe BPCEFRA | Moved up: Bank of China 1 to 2CHN, China Construction Bank 1 to 2CHN Moved down: BNP Paribas 3 to 2FRA, Citigroup 4 to 3USA, Credit Suisse 2 to 1CHE |
| 2017 to 2018 | 30 to 29 | Groupe BPCEFRA | NordeaSWE, Royal Bank of ScotlandGBR | Moved down: Bank of America 3 to 2USA, China Construction Bank 2 to 1CHN |
| 2018 to 2019 | 29 to 30 | Toronto DominionCAN | none | Moved down: Deutsche Bank 3 to 2DEU |
| 2019 to 2020 | 30 to 30 | none | none | Moved up: China Construction Bank 1 to 2CHN Moved down: Goldman Sachs 2 to 1USA, JP Morgan Chase 4 to 3USA, Wells Fargo 2 to 1USA |
| 2020 to 2021 | 30 to 30 | none | none | Moved up: BNP Paribas 2 to 3FRA, Goldman Sachs 1 to 2USA, JP Morgan Chase 3 to 4USA |
| 2021 to 2022 | 30 to 30 | none | none | Moved up: Bank of America 2 to 3USA Moved down: BNP Paribas 3 to 2FRA, China Construction Bank 2 to 1CHN |
| 2022 to 2023 | 30 to 29 | Bank of CommunicationsCHN | Credit SuisseCHE, UniCreditITA | Moved up: Agricultural Bank of China 1 to 2CHN, China Construction Bank 1 to 2CHN, UBS 1 to 2CHE |
| 2023 to 2024 | 29 to 29 | none | none | Moved up: Groupe Crédit Agricole 1 to 2FRA Moved down: Bank of America 3 to 2USA |
| 2024 to 2025 | 29 to 29 | none | none | Moved up: Bank of America 2 to 3USA, Industrial and Commercial Bank of China 2 to 3CHN Moved down: Deutsche Bank 2 to 1DEU |
Count by jurisdiction over time
This is the one aggregate worth keeping: how many listed G-SIBs sit in each home jurisdiction each year. Zero is a real zero here. It is not the same thing as the 2011 no-bucket state above.
| Jurisdiction | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| USAlatest 8, peak 8 | 8 | 8 | 8 | 8 | 8 | 8 | 8 | 8 | 8 | 8 | 8 | 8 | 8 | 8 | 8 |
| CHNlatest 5, peak 5 | 1 | 1 | 2 | 3 | 4 | 4 | 4 | 4 | 4 | 4 | 4 | 4 | 5 | 5 | 5 |
| FRAlatest 4, peak 4 | 4 | 4 | 4 | 4 | 4 | 4 | 3 | 4 | 4 | 4 | 4 | 4 | 4 | 4 | 4 |
| GBRlatest 3, peak 4 | 4 | 4 | 4 | 4 | 4 | 4 | 4 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 |
| JPNlatest 3, peak 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 |
| CANlatest 2, peak 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 2 | 2 | 2 | 2 | 2 | 2 | 2 |
| CHElatest 1, peak 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 1 | 1 | 1 |
| DEUlatest 1, peak 2 | 2 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| ESPlatest 1, peak 2 | 1 | 2 | 2 | 2 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| NLDlatest 1, peak 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| BELlatest 0, peak 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| ITAlatest 0, peak 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 |
| SWElatest 0, peak 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Source: FSB, 2025 List of Global Systemically Important Banks (G-SIBs), and 2011-2025 archive Transcribed verbatim from the FSB's annual PDF lists; bucket 5 has never been populated, and the 29 null buckets are the 2011 designation-only list before FSB began publishing bucket assignments in 2012. Jurisdiction is the bank's headquarters/home-regulator domicile, assigned here (the FSB lists do not print it). Methodology
Long-run academic benchmarks
Three independent academic series shown as context, not systemic-risk measures: none feed the LRMES, MES, CoVaR, or absorption-ratio computations above.
Long-run academic benchmarks
US market volatility sits at the 42nd percentile of its record
Source: Ken French Data Library (Fama-French factors) Free with citation, academic research and teaching use; std. dev. of monthly Mkt-RF x sqrt(12). Methodology
Banking-industry cost of capital and beta
Damodaran’s US industry cross-section (2026-01-05): money-center and regional banks against the whole-market baseline. A textbook CAPM/WACC yardstick alongside the market-implied LRMES/MES/CoVaR measures above.
| Industry (US) | Firms | Levered beta | Unlevered beta | Cost of equity | WACC |
|---|---|---|---|---|---|
| Bank (Money Center) | 15 | 0.76 | 0.34 | 7.3% | 5.0% |
| Banks (Regional) | 568 | 0.40 | 0.29 | 5.7% | 5.0% |
| Total Market | 5994 | 0.91 | 0.72 | 8.0% | 7.0% |
Source: Damodaran Online, NYU Stern (industry cost of capital and betas) Free, acknowledgement welcomed but not required; single cross-sectional snapshot, not a time series. Methodology
Long-run academic benchmarks
Global real rates ended the record far below their historical high
Source: Schmelzing (2020), Bank of England SWP 845 Methodology
Nine centuries of British macro, beginning in 1086
The Bank’s research compilation reaches from 1086 to 2016 across seven sections. Each chart below states its own, shorter span; the table shows how far each section actually reaches.
Nine centuries of British macro
Bank Rate closes its three-century record at the all-time low
Source: Bank of England, A millennium of macroeconomic data for the UK, version 3.1 Worksheet A31. Interest rates. Bank of England copyright; non-commercial re-use permitted. Methodology
Nine centuries of British macro
Britain’s pre-industrial inflation was far more volatile than its postwar record
Source: Bank of England, A millennium of macroeconomic data for the UK, version 3.1 Worksheet A47. Wages and prices. Bank of England copyright; non-commercial re-use permitted. Methodology
The compilation’s reach varies by section
First and last observation years describe section-level reach, not continuous coverage for every series. Counts are distinct published series names.
| Section | Series | First year | Last year |
|---|---|---|---|
| Labour, capital and productivity | 9 | 1086 | 2016 |
| Money and Credit | 8 | 1086 | 2016 |
| National Accounts | 16 | 1086 | 2016 |
| Wages and Prices | 10 | 1209 | 2016 |
| Fiscal | 5 | 1689 | 2016 |
| Financial markets | 12 | 1694 | 2016 |
| Trade | 3 | 1772 | 2016 |
Source: Bank of England, A millennium of macroeconomic data for the UK, version 3.1 Section minima and maxima across published observations. Bank of England copyright; non-commercial re-use permitted. Methodology
See the full methodology for the measures, windows, universe, the repaired engine input contract, method labels and numerical fallbacks, original output provenance, crisis-anchor validation, and why the dollar SRISK level is a documented open gap.