Dodd-Frank Act Stress Test Publications
2023 Stress Test Scenarios
Preface
The Federal Reserve promotes a safe, sound, and efficient banking system that supports the U.S. economy through its supervision and regulation of domestic and foreign banks.
As part of its supervision efforts, the Federal Reserve conducts annually a stress test. The stress test assesses how large domestic and foreign banks, as well as savings and loan holding companies, are likely to perform under hypothetical recessions.1 Figure 1 summarizes the stress test cycle.
As part of this cycle, the Federal Reserve publishes four documents, in the following chronological order:
- Stress Test Scenarios describes the hypothetical recessions used in the Federal Reserve's stress test. Stress Test Scenarios is typically published by mid-February.
- Stress Test Methodology provides comprehensive details about the models and methodologies used in the stress test. Stress Test Methodology is typically published at the end of the first quarter.
- Stress Test Results reports the aggregate and individual bank results of the stress test, which assesses whether banks are sufficiently capitalized to absorb losses during a severe recession. Stress Test Results is typically published at the end of the second quarter.
- Large Bank Capital Requirements announces the individual capital requirement for all large banks, which are partially determined by the results of the stress test. Large Bank Capital Requirements is typically published during the third quarter.
These publications can be found on the Stress Test Publications page (https://www.federalreserve.gov/publications/dodd-frank-act-stress-test-publications.htm).
For information on the Federal Reserve's supervision of large financial institutions, see https://www.federalreserve.gov/supervisionreg/large-financial-institutions.htm. For information on the Federal Reserve's supervision of capital-planning processes of banks, see https://www.federalreserve.gov/supervisionreg/stress-tests-capital-planning.htm.
For more information on how the Board promotes the safety and soundness of the banking system, see https://www.federalreserve.gov/supervisionreg.htm.
Executive Summary
The Federal Reserve's stress tests help ensure that large banks are able to lend to households and businesses even in a severe recession. The stress tests evaluate the financial resilience of large banks by estimating bank losses, revenues, expenses, and resulting capital levels—which provide a cushion against losses—under hypothetical recession scenarios into the future.2 The Federal Reserve uses the results of the stress test to set large bank capital requirements.
The severely adverse scenario is characterized by a severe global recession accompanied by a period of heightened stress in both commercial and residential real estate markets, as well as in corporate debt markets. The U.S. unemployment rate rises nearly 6-1/2 percentage points from the starting point of the scenario in the fourth quarter of 2022 to its peak of 10 percent in the third quarter of 2024. The sharp decline in economic activity is also accompanied by an increase in market volatility, widening corporate bond spreads, and a collapse in asset prices, including a 38 percent decline in house prices and a 40 percent decline in commercial real estate prices. The international portion of the scenario features recessions in four countries or country blocs, with heightened stress in advanced economies, followed by declines in inflation and an appreciation in the value of the U.S. dollar against all countries and country bloc's currencies, except for the Japanese yen.
Banks with large trading operations are tested against a global market shock component that stresses their trading, private equity, and certain other fair-valued positions. Furthermore, banks with substantial trading or custodial operations are tested against the default of their largest counterparty (see table 1).
This year, for the first time, the Federal Reserve is publishing an additional, exploratory market shock component (the exploratory market shock) that will be applied only to U.S. global systemically important banks (G-SIBs).3 The purpose of the stress test is to understand a firm's resilience to a range of severe but plausible events, and the exploratory component furthers that purpose by posing a different set of risks than is probed in this year's global market shock component.
For instance, while this year's global market shock is characterized by a severe recession with fading inflation expectations, the exploratory market shock is characterized by a less severe recession with greater inflationary pressures induced by higher inflation expectations. Such differences in scenarios could reveal different losses across banks, depending on the positions held in their portfolios.
Consistent with the nature of an exploratory exercise, the exploratory market shock will not contribute to the capital requirements set by this year's stress test. Instead, it will be used to assess the potential of multiple scenarios to capture a wider array of risks in future stress test exercises. (See box 1 in the "Supervisory Stress Test Scenarios" section.)
The hypothetical scenarios are described in additional detail in this publication.
Table 1. 2023 Stress test banks
Bank | Subject to global market shock | Subject to counterparty default | Subject to exploratory market shock1 |
---|---|---|---|
Bank of America Corporation | X | X | X |
The Bank of New York Mellon Corporation | X | X | |
Barclays US LLC | X | X | |
BMO Financial Corp. | |||
Capital One Financial Corporation | |||
The Charles Schwab Corporation | |||
Citigroup Inc. | X | X | X |
Citizens Financial Group, Inc. | |||
Credit Suisse Holdings (USA), Inc. | X | X | |
DB USA Corporation | X | X | |
The Goldman Sachs Group, Inc. | X | X | X |
JPMorgan Chase & Co. | X | X | X |
M&T Bank Corporation | |||
Morgan Stanley | X | X | X |
Northern Trust Corporation | |||
The PNC Financial Services Group, Inc. | |||
RBC US Group Holdings LLC 2 | |||
State Street Corporation | X | X | |
TD Group US Holdings LLC | |||
Truist Financial Corporation | |||
UBS Americas Holding LLC | |||
U.S. Bancorp | |||
Wells Fargo & Company | X | X | X |
Note: The information listed in this table is based on third quarter 2022 data. BMO Financial Corp., Citizens Financial Group, Inc., and M&T Bank Corporation are on a two-year stress test cycle; therefore, they were included in last year's stress test and would normally be included next in 2024. In connection with their recent applications, the Board required these firms to receive a new capital requirement this year based on the 2023 stress test. The 2023 stress test and capital requirement will include the effects of the recent acquisitions by Citizens Financial Group, Inc. and M&T Bank Corporation.
1. As in the supervisory stress test, the exploratory market shock for The Bank of New York Mellon Corporation and State Street Corporation will only include the counterparty default component. Their exploratory market shock component will not include mark-to-market losses on their trading or credit valuation adjustments exposures. Return to table
2. RBC US Group Holdings LLC elected to opt into the 2023 stress test. Return to table
Supervisory Stress Test Scenarios
The severely adverse scenario describes a hypothetical set of conditions designed to assess the strength and resilience of banks in an adverse economic environment.4 The baseline scenario follows a profile similar to that of average projections from a survey of economic forecasters. These scenarios are not Federal Reserve forecasts.
The scenarios start in the first quarter of 2023 and extend through the first quarter of 2026. Each scenario includes 28 variables; this set of variables is the same as the set provided in last year's supervisory stress test scenarios. The variables describing economic developments within the United States include:
- Six measures of economic activity and prices: quarterly percent changes (at an annual rate) in real and nominal gross domestic product (GDP), real and nominal disposable personal income, the Consumer Price Index for All Urban Consumers (CPI), and the level of the unemployment rate of the civilian non-institutional population aged 16 years and over.
- Four aggregate measures of asset prices or financial conditions: indexes of house prices, commercial real estate prices, equity prices, and stock market volatility.
- Six measures of interest rates: the rate on 3-month Treasury securities; the yield on 5-year Treasury securities; the yield on 10-year Treasury securities; the yield on 10-year BBB-rated corporate securities; the interest rate associated with conforming, conventional, 30-year fixed-rate mortgages; and the prime rate.
The variables describing international economic conditions in each scenario include three variables in four countries or country blocs:
- The three variables for each country or country bloc: quarterly percent changes (at an annual rate) in real GDP and in consumer price indexes or local equivalents, and the level of the U.S. dollar exchange rate.
- Four countries or country blocs: the euro area (the 20 European Union member states that have adopted the euro as their common currency); the United Kingdom; developing Asia (the nominal GDP-weighted aggregate of China, India, South Korea, Hong Kong Special Administrative Region, and Taiwan); and Japan.
Baseline and Severely Adverse Scenarios
The following sections describe this year's baseline and severely adverse scenarios. The variables included in these scenarios are provided in tables at the end of this document.5 Historical data for the domestic and the international variables are reported in tables 2.A and 2.B, respectively.
Baseline Scenario
The baseline scenario for U.S. real activity, inflation, and interest rates (see table 3.A) is similar to the consensus projections from 2023 Blue Chip Financial Forecasts and 2023 Blue Chip Economic Indicators.6 The near-term component of the baseline scenario is similar to the January 2023 release of the Blue Chip publications, while the long-term component of the baseline scenario is similar to the October 2022 release. It is important to emphasize that this scenario is not a Federal Reserve forecast.
The baseline scenario for the United States features an initial slowdown and then a gradual recovery. The unemployment rate rises steadily from just over 3-1/2 percent at the end of 2022 to near 5 percent by the first quarter of 2024, before declining to just over 4-1/2 percent by the end of the scenario. Real GDP growth declines from about 1-3/4 percent at the end of 2022 to around negative 3/4 percent by the middle of 2023 before gradually increasing to about 2-1/4 percent by the second half of 2024 and then settling near 2 percent at the end of the scenario. Inflation, measured as the quarterly change in the CPI and reported as an annualized rate, declines from a little less than 3-1/4 percent to a trough of about 2 percent in the second quarter of 2024 and remains near 2-1/4 percent in the rest of the scenario. The 3-month Treasury rate increases from around 4 percent at the end of 2022 to about 4-3/4 percent in the second quarter of 2023, then declines to about 3 percent by the end of the scenario. Ten-year Treasury yields decline steadily from a bit below 4 percent to around 3-1/4 percent at the end of the scenario. The prime rate follows a path similar to short-term interest rates, while yields on BBB-rated corporate bonds and mortgage rates follow a path similar to long-term interest rates.
Equity prices remain at their level for the fourth quarter of 2022 throughout the scenario. Equity market volatility, as measured by the U.S. Market Volatility Index (VIX), falls modestly in the first three quarters of the scenario before increasing to around 28-1/2, where it stays for the remainder of the scenario. Nominal house prices increase gradually by 2 percent per year and commercial real estate prices increase by 3 percent per year over the scenario.
The baseline paths for the international variables (see table 3.B) are similar to the trajectories reported in the January 2023 Blue Chip Economic Indicatorsand the International Monetary Fund's October 2022 World Economic Outlook.7 In the baseline scenario, real GDP growth in developing Asia rises from about 4 percent at the end of 2022 to a peak of just under 5 percent by the end of 2023 and declines to around 4-3/4 percent at the end of the scenario. Real GDP growth in the euro area increases from about negative 3/4 percent to a high of just above 2 percent in the third quarter of 2024, before declining to about 1-1/2 percent by the end of the scenario. Real GDP growth in the United Kingdom declines early in the scenario, from around negative 1/4 percent to a bit below negative 2 percent in the second quarter of 2023, before climbing to 2-3/4 percent in the third quarter of 2024 and then falling back to around 2 percent in the second quarter of 2025 and thereafter. GDP growth in Japan starts around 2-3/4 percent and declines to about negative 1/4 percent in the third quarter of 2023 and then grows at an average annualized rate of about 3/4 percent in the remainder of the scenario.
Consumer price inflation in the euro area declines rapidly from about 10-1/4 percent at the end of 2022 to about 1-3/4 percent in the third quarter of 2024 before rising and then settling around 2 percent. Consumer price inflation declines rapidly in the United Kingdom as well, falling from above 8-1/2 percent at the end of 2022 to about 1-1/4 percent in the third quarter of 2024, and then stays below 1 percent for the remainder of the scenario. Inflation in Japan starts near 2-1/2 percent before declining to 1-1/4 percent by the fourth quarter of 2023 and hovers below 1-1/2 percent throughout the remainder of the scenario. Inflation rates in developing Asia start near 3 percent before declining to about 2-1/4 percent in the second quarter of 2025 and remain there for the rest of the scenario.
Severely Adverse Scenario
The severely adverse scenario follows the Board's Policy Statement on the Scenario Design Framework for Stress Testing ("Scenario Design Framework").8 This scenario is characterized by a severe global recession, with prolonged declines in both residential and commercial real estate prices, which spill over into the corporate sector and affect investment sentiment. The developments in foreign economies involve greater stress in advanced foreign economies. This is a hypothetical scenario designed to assess the strength and resilience of banks and does not represent a Federal Reserve forecast.
Consistent with the Scenario Design Framework, under the severely adverse scenario the U.S. unemployment rate climbs to a peak of 10 percent in the third quarter of 2024 (see table 4.A), a roughly 6-1/2 percentage point increase relative to its fourth-quarter 2022 level. Real GDP declines nearly 8-3/4 percent from the fourth quarter of 2022 to its trough in the first quarter of 2024, before recovering. The rising unemployment rate and the rapid decline in aggregate demand for goods and services significantly reduce inflationary pressures. Inflation, measured as the quarterly change in the CPI and reported as an annualized rate, falls from below 3-1/4 percent at the end of 2022 to about 1-1/4 percent in the third quarter of 2023 and then gradually increases to above 1-1/2 percent by the end of the scenario.
Short-term interest rates, as measured by the 3-month Treasury rate, fall significantly to near zero by the third quarter of 2023 and remain there for the remainder of the scenario. Long-term interest rates, as measured by the 10-year Treasury yield, fall by nearly 3-1/4 percentage points by the second quarter of 2023, and then gradually rise in late 2023 to about 1-1/2 percent by the end of the scenario. These interest rate paths imply that the yield curve remains inverted through the second quarter of 2023. Thereafter, the slope of the yield curve becomes positive and steepens over the remainder of the scenario.
Conditions in corporate bond markets deteriorate markedly. The spread between yields on BBB-rated bonds and yields on 10-year Treasury securities widens to 5-3/4 percentage points by the third quarter of 2023, an increase of more than 3-1/2 percentage points relative to the fourth quarter of 2022. Corporate bond spreads then gradually decline to 2-1/4 percentage points by the end of the scenario. The spread between mortgage rates and 10-year Treasury yields widens to 3 percentage points by the third quarter of 2023 before narrowing to about 1-1/2 percentage points at the end of the scenario.
Asset prices drop sharply in the severely adverse scenario. Equity prices fall 45 percent from the fourth quarter of 2022 through the fourth quarter of 2023, and do not return to their initial level until the end of the scenario. The maximum quarterly value of the VIX reaches a peak value of 75 in the second quarter of 2023, then declines to about 32-1/2 at the end of the scenario. House prices and commercial real estate prices also experience large declines. House prices fall sharply through the third quarter of 2024, reaching a trough that is about 38 percent below their level in the fourth quarter of 2022. Commercial real estate prices experience a slightly larger decline, reaching a trough in the fourth quarter of 2024 that is 40 percent below their level at the end of 2022. House prices and commercial real estate prices recover slowly and are well below their fourth quarter of 2022 values at the end of the scenario.
The international component of the severely adverse scenario involves sharp declines in real GDP in three of the four countries or country blocs at the start of the scenario. Japan experiences the most severe contraction, followed by the euro area and United Kingdom, while developing Asia experiences only a moderate decline. In Japan, the euro area, and the United Kingdom, GDP levels surpass their 2022 fourth-quarter levels by the end of the scenario. By contrast, in developing Asia, where output fell less, the level of GDP surpasses its fourth quarter of 2022 level by the end of 2023.
Inflation declines significantly in all four countries or country blocs. All areas experience a period of deflation at various points in the scenario, although deflation is more severe and protracted in Japan and developing Asia. The U.S. dollar appreciates against the euro, the pound sterling, and the currencies of developing Asia, but depreciates against the yen.
Additional Key Features of the Severely Adverse Scenario
Stress on corporate borrower balance sheets and resulting credit losses on corporate loans should be assumed to be higher for lower-rated nonfinancial corporate borrowers. Declines in aggregate U.S. house prices should be assumed to be concentrated in regions that have experienced rapid price gains over the past two years. Declines in commercial real estate prices should be assumed to be concentrated in properties most at risk of a sustained drop in income and asset values: offices that may be affected by remote work or hospitality sectors that continue to be affected by reduced business travel. Declines in U.S. house prices and U.S. commercial real estate prices should also be assumed to be representative of the declines in house prices and commercial real estate prices in foreign regions and economies, especially those that experienced rapid price gains before the pandemic and were significantly affected by the event.
The weakness in euro area economic conditions reflects a broad-based contraction due to geopolitical risks, in part due to the conflict in Ukraine. Conditions across Latin American economies should be assumed to feature a slowdown comparable to the average slowdown in the global economy. Conditions in other emerging economies outside of Latin America should be assumed to feature a slowdown similar to the one in developing Asia.
Comparison of the Severely Adverse Scenario and 2022 Severely Adverse Scenario
The current severely adverse scenario features a greater increase in the unemployment rate in the United States as compared to the 2022 severely adverse scenario. This difference reflects the Scenario Design Framework, which calls for a higher increase in the unemployment rate when the starting level of the unemployment rate is lower.
The current scenario features a significantly higher starting level of interest rates compared to the previous year's scenario, which allows interest rates to decline more forcefully in response to the hypothetical drop in economic activity and inflation. The scenario also features a larger and more rapid decline in house prices as compared to their declines in the previous year's scenario. This larger decline reflects the Scenario Design Framework's response to the significantly higher housing valuations at the end of 2022. The potential for spillover effects in asset markets and sharp revisions in investor sentiment are captured by a decline in equity prices and an increase in corporate bond spreads, although these changes are somewhat less severe relative to last year's scenario. These less severe changes reflect the moves in those markets over the course of 2022 and limits procyclicality in the scenario.
Global Market Shock Component for the Supervisory Severely Adverse Scenario
The global market shock component for the severely adverse scenario (global market shock) is a set of hypothetical shocks to a large set of risk factors reflecting general market distress and heightened uncertainty. Banks with significant trading activity must consider the global market shock as part of their supervisory severely adverse scenario.9 The losses associated with the global market shock are recognized in the first quarter of the scenario and are carried through all subsequent quarters. In addition, certain large and highly interconnected firms must apply the same global market shock to project losses under the counterparty default scenario component. The global market shock is applied to positions held by the banks on a given as-of date, which is October 14, 2022, for the 2023 supervisory stress test.10 These shocks do not represent a forecast of the Federal Reserve.
The design and specification of the global market shock differs from the macroeconomic scenarios for several reasons. First, profits and losses from trading and counterparty credit are measured in mark-to-market terms, while revenues and losses from traditional banking are generally measured using the accrual method. Another key difference is the timing of loss recognition. The global market shock affects the mark-to-market value of trading positions and counterparty credit losses in the first quarter of the scenario. This timing is based on an observation that market dislocations can happen rapidly and unpredictably at any time under stressed conditions. Applying the global market shock in the first quarter ensures that potential losses from trading and counterparty exposures are incorporated into banks' capital ratios in each quarter of the scenario.
The global market shock is specified by a large set of risk factors that include, but are not limited to
- equity prices of key advanced economies and developing and emerging market economies along with selected points along term structures of option-implied volatilities;
- foreign exchange rates of most major and some minor currencies, along with selected points along term structures of option-implied volatilities;
- selected-maturity government yields (e.g., for 10-year U.S. Treasuries), swap rates, and other important interest rates for key advanced economies and developing and emerging market economies;
- selected maturities and expiries of implied volatilities that are key inputs to the pricing of interest rate derivatives;
- selected expiries of futures prices for energy products including crude oil (differentiated by country of origin), natural gas, and power;
- selected expiries of futures prices for metals and agricultural commodities; and
- credit spreads or prices for selected credit-sensitive products, including corporate bonds, credit default swaps (CDS), and loans; non-agency residential mortgage-backed securities (RMBS) and commercial mortgage-backed securities (CMBS); sovereign debt; and municipal bonds.
The Board considers emerging and ongoing areas of financial market vulnerabilities in the development of the global market shock. This assessment of potential vulnerabilities is informed by financial stability reports, supervisory information, and internal and external assessments of potential sources of distress such as geopolitical, economic, and financial market events.
The global market shock includes a standardized set of risk factor shocks to financial market variables that apply to all banks with significant trading activity. Depending on the type of financial market vulnerability that the global market shock is intended to assess, the risk factor shocks could be based on a single historical episode, multiple historical periods, hypothetical events that are based on salient risks, or a hybrid approach comprising some combination of historical episodes and hypothetical events. A market shock based on hypothetical events may result in changes in risk factors that were not observed over history.11
Risk factor shocks are calibrated based on assumed time horizons. The calibration horizons reflect several considerations related to the scenario being modeled. One important consideration is the liquidity characteristics of different risk factors. These characteristics may vary depending on the specified market shock narrative. More specifically, the calibration horizons reflect the variation in the speed at which banks could reasonably close out, or effectively hedge, risk exposures in the event of market stress. The calibration horizons are generally longer than the typical times needed to liquidate exposures under normal conditions because they are designed to capture the unpredictable liquidity conditions that prevail in times of stress.12 In addition, shocks to risk factors in more-liquid markets, such as those for government securities, foreign exchange, or public equities, are calibrated to shorter horizons (such as three months), while shocks to risk factors in less-liquid markets, such as those for non-agency securitized products or private equities, have longer calibration horizons (such as 12 months).
2023 Global Market Shock Component for the Supervisory Severely Adverse Scenario
The global market shock component is characterized by market expectations of severe recessions in the United States and other countries. Financial conditions tighten and inflation expectations decline.
Treasury rates fall as short-term rates decline sharply. Longer-term rates also decrease, although to a lesser extent, reflecting flight-to-safety considerations. Most government interest rates in Europe and other advanced economies fall less than U.S. Treasury rates, contributing to the U.S. dollar depreciating against the euro and other advanced country currencies. The U.S. dollar appreciates against most emerging market currencies, reflecting expectations for more acute recessions in those countries.
Generally, commodity prices fall as demand declines from the expected economic slowdown, though precious metals see price increases. Most emerging market sovereign CDS spreads widen severely reflecting expectations of severe recessions in those countries.
The expected decline in economic activity leads to large public equity price declines across global markets, while financial market uncertainty drives an increase in public equity volatility. Private equity values experience sizable declines as well, in response to a weak economic outlook.
An increase in expected defaults leads to a large widening in corporate credit spreads. A decline in expected demand and falling real estate prices lead to large disruptions in the residential and commercial real estate sectors. As a result, non-agency RMBS and CMBS market values fall significantly.
Comparison of the 2023 Global Market Shock Component and the 2022 Global Market Shock Component
The 2023 global market shock features fading inflationary pressures, while last year's component was characterized by worsening supply chain disruptions that put upward pressure on inflation. Accordingly, the current global market shock mainly differs from the 2022 component in the behavior of interest rates, foreign exchange rates, and commodities prices.
Treasury rates fall in the current component, with large declines specified for shorter tenors and milder declines specified for longer tenors. In the 2022 component, Treasury rates increased across the term structure, resulting in an upward shift in the yield curve. Similarly, inflation breakeven rates decrease in the current component, while they increased in the 2022 component.
The U.S. dollar depreciates against the currencies of advanced countries in the 2023 component, while it mostly appreciated against advanced country currencies in the 2022 component. Non-precious metals and other commodities, such as oil and natural gas, face large price declines in the current component, while commodity prices increased in the 2022 component due to supply chain disruptions.
Box 1. Exploratory Market Shock Component
This year, for the first time, the Federal Reserve is publishing an additional, exploratory market shock component (the exploratory market shock) that will be applied only to U.S. G-SIBs.1 The purpose of the stress test is to understand a firm's resilience to a range of severe but plausible events, and the exploratory component furthers that purpose by posing a different set of risks than is probed in this year's global market shock component.
For instance, while this year's global market shock is characterized by a severe recession with fading inflation expectations, the exploratory market shock is characterized by a less severe recession with greater inflationary pressures induced by higher inflation expectations. Such differences in scenarios could reveal different losses across banks, depending on the positions held in their portfolios.
Consistent with the nature of an exploratory exercise, the exploratory market shock will not contribute to the capital requirements set by this year's stress test. Instead, it will be used to assess the potential of multiple scenarios to capture a wider array of risks in future stress test exercises.
Firm-specific results from the exploratory market shock will be published along with those from the severely adverse scenario in June 2023.
Exploratory Market Shock Description
The exploratory market shock is characterized by a recession with inflationary pressures induced by higher inflation expectations.
Treasury rates increase as short-term rates rise sharply, while longer-term rates increase to a lesser extent. Longer-term government bond rates increase more in Europe compared to the United States, driven by higher inflationary expectations for that region.
The U.S. dollar appreciates against the euro, Swiss franc, and pound sterling as stresses in Europe and its surrounding areas are expected to be particularly intense.
The expected fall in economic activity leads to public equity price declines across global markets, and financial market uncertainty drives increases in public equity volatility. Private equity values experience sizeable declines driven by a weak economic outlook.
Market expectations for reduced economic activity combined with higher funding costs cause corporate credit spreads to widen. Non-agency RMBS market values suffer as home prices decline from lower demand due to higher interest rates.
Commodity prices rise from the threat of worsening supply chain disruptions, with European natural gas prices trending higher.
1. The U.S. G-SIBs are Bank of America Corporation, The Bank of New York Mellon Corporation, Citigroup Inc., The Goldman Sachs Group, Inc., JPMorgan Chase & Co., Morgan Stanley, State Street Corporation, and Wells Fargo & Company. As in the supervisory stress test, The Bank of New York Mellon Corporation and State Street Corporation are only required to incorporate an additional counterparty default component into their exploratory market shock component. The Bank of New York Mellon Corporation and State Street Corporation will not be required to apply the exploratory market shock component to calculate mark-to-market losses on their trading or credit valuation adjustments exposures. Return to text
Counterparty Default Component for the Supervisory Severely Adverse Scenario
Large banks with substantial trading or custodial operations are required to incorporate a counterparty default scenario component into their supervisory severely adverse scenario for 2023 and recognize associated losses in the first quarter of the scenario.13 This component involves the unexpected default of the firm's largest counterparty.14
In connection with the counterparty default scenario component, these banks are required to estimate and report the potential losses and related effects on capital associated with the unexpected default of the counterparty that would generate the largest losses across their derivatives and securities financing transactions, including securities lending or borrowing and repurchase or reverse repurchase agreement activities. The counterparty default scenario component is an add-on to the Federal Reserve's severely adverse scenario.
The largest counterparty of each bank will be determined by net stressed losses. Net stressed losses are estimated by applying the global market shock to revalue securities financing transactions and derivatives, including collateral posted or received. The as-of date for the counterparty default scenario component is October 14, 2022, which is the same as-of date for the global market shock component.15
Variables for the Supervisory Stress Test Scenarios
Table 2.A. Historical data: Domestic variables, Q1:2000–Q4:2022
Percent, unless otherwise indicated
Date | Real GDP growth |
Nominal GDP growth |
Real dispos- able income growth |
Nominal dispos- able income growth |
Unem- ployment rate |
CPI inflation rate |
3-month Treasury rate |
5-year Treasury yield |
10-year Treasury yield |
BBB corpo- rate yield |
Mort- gage rate |
Prime rate |
Level | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Dow Jones Total Stock Market Index | House Price Index |
Com- mercial Real Estate Price Index |
Market Volatility Index |
|||||||||||||
Q1 2000 | 1.5 | 4.2 | 7.2 | 10.7 | 4.0 | 4.0 | 5.5 | 6.6 | 6.7 | 8.3 | 8.3 | 8.7 | 14,296 | 102 | 125 | 27.0 |
Q2 2000 | 7.5 | 10.2 | 4.9 | 6.9 | 3.9 | 3.2 | 5.7 | 6.5 | 6.4 | 8.6 | 8.3 | 9.2 | 13,619 | 105 | 134 | 33.5 |
Q3 2000 | 0.4 | 2.8 | 5.3 | 8.0 | 4.0 | 3.7 | 6.0 | 6.1 | 6.1 | 8.2 | 8.0 | 9.5 | 13,613 | 107 | 143 | 21.9 |
Q4 2000 | 2.4 | 4.6 | 2.5 | 4.9 | 3.9 | 2.9 | 6.0 | 5.6 | 5.8 | 8.0 | 7.6 | 9.5 | 12,176 | 110 | 146 | 31.7 |
Q1 2001 | -1.3 | 1.3 | 3.3 | 6.4 | 4.2 | 3.9 | 4.8 | 4.9 | 5.3 | 7.5 | 7.0 | 8.6 | 10,646 | 112 | 144 | 32.8 |
Q2 2001 | 2.5 | 5.0 | -1.0 | 0.8 | 4.4 | 2.8 | 3.7 | 4.9 | 5.5 | 7.5 | 7.1 | 7.3 | 11,407 | 114 | 144 | 34.7 |
Q3 2001 | -1.6 | 0.0 | 9.0 | 9.2 | 4.8 | 1.1 | 3.2 | 4.6 | 5.3 | 7.2 | 7.0 | 6.6 | 9,563 | 116 | 146 | 43.7 |
Q4 2001 | 1.1 | 2.4 | -6.5 | -6.3 | 5.5 | -0.3 | 1.9 | 4.2 | 5.1 | 7.1 | 6.8 | 5.2 | 10,708 | 118 | 139 | 35.3 |
Q1 2002 | 3.4 | 4.7 | 9.7 | 10.6 | 5.7 | 1.3 | 1.7 | 4.5 | 5.4 | 7.4 | 7.0 | 4.8 | 10,776 | 121 | 143 | 26.1 |
Q2 2002 | 2.5 | 3.9 | 3.3 | 6.4 | 5.8 | 3.2 | 1.7 | 4.5 | 5.4 | 7.5 | 6.8 | 4.8 | 9,384 | 124 | 142 | 28.4 |
Q3 2002 | 1.6 | 3.6 | 0.6 | 2.7 | 5.7 | 2.2 | 1.6 | 3.4 | 4.5 | 7.2 | 6.3 | 4.8 | 7,774 | 127 | 144 | 45.1 |
Q4 2002 | 0.5 | 2.8 | 2.6 | 4.5 | 5.9 | 2.4 | 1.3 | 3.1 | 4.3 | 6.9 | 6.1 | 4.5 | 8,343 | 129 | 150 | 42.6 |
Q1 2003 | 2.1 | 4.1 | -0.2 | 2.9 | 5.9 | 4.2 | 1.2 | 2.9 | 4.2 | 6.2 | 5.8 | 4.3 | 8,052 | 132 | 155 | 34.7 |
Q2 2003 | 3.6 | 5.1 | 5.1 | 5.5 | 6.1 | -0.7 | 1.0 | 2.6 | 3.8 | 5.3 | 5.5 | 4.2 | 9,342 | 135 | 154 | 29.1 |
Q3 2003 | 6.8 | 9.3 | 7.2 | 10.0 | 6.1 | 3.0 | 0.9 | 3.1 | 4.4 | 5.6 | 6.0 | 4.0 | 9,650 | 139 | 150 | 22.7 |
Q4 2003 | 4.7 | 7.3 | 1.1 | 3.1 | 5.8 | 1.5 | 0.9 | 3.2 | 4.4 | 5.4 | 5.9 | 4.0 | 10,800 | 143 | 152 | 21.1 |
Q1 2004 | 2.3 | 5.2 | 1.8 | 5.0 | 5.7 | 3.4 | 0.9 | 3.0 | 4.1 | 5.0 | 5.6 | 4.0 | 11,039 | 148 | 161 | 21.6 |
Q2 2004 | 3.2 | 6.5 | 4.2 | 7.1 | 5.6 | 3.2 | 1.1 | 3.7 | 4.7 | 5.7 | 6.1 | 4.0 | 11,145 | 154 | 169 | 20.0 |
Q3 2004 | 3.8 | 6.5 | 2.9 | 4.9 | 5.4 | 2.6 | 1.5 | 3.5 | 4.4 | 5.4 | 5.9 | 4.4 | 10,894 | 159 | 180 | 19.3 |
Q4 2004 | 4.2 | 7.4 | 5.2 | 8.8 | 5.4 | 4.4 | 2.0 | 3.5 | 4.3 | 5.1 | 5.7 | 4.9 | 11,952 | 165 | 180 | 16.6 |
Q1 2005 | 4.5 | 7.9 | -4.8 | -2.5 | 5.3 | 2.0 | 2.5 | 3.9 | 4.4 | 5.2 | 5.8 | 5.4 | 11,637 | 172 | 185 | 14.7 |
Q2 2005 | 2.0 | 5.0 | 3.9 | 6.6 | 5.1 | 2.7 | 2.9 | 3.9 | 4.2 | 5.4 | 5.7 | 5.9 | 11,857 | 179 | 189 | 17.7 |
Q3 2005 | 3.2 | 7.0 | 1.7 | 6.1 | 5.0 | 6.2 | 3.4 | 4.0 | 4.3 | 5.4 | 5.8 | 6.4 | 12,283 | 185 | 198 | 14.2 |
Q4 2005 | 2.3 | 5.6 | 3.4 | 6.7 | 5.0 | 3.8 | 3.8 | 4.4 | 4.6 | 5.8 | 6.2 | 7.0 | 12,497 | 190 | 204 | 16.5 |
Q1 2006 | 5.5 | 8.5 | 8.3 | 10.6 | 4.7 | 2.1 | 4.4 | 4.6 | 4.7 | 5.8 | 6.2 | 7.4 | 13,122 | 193 | 211 | 14.6 |
Q2 2006 | 1.0 | 4.6 | 1.5 | 5.1 | 4.6 | 3.7 | 4.7 | 5.0 | 5.2 | 6.3 | 6.6 | 7.9 | 12,809 | 193 | 219 | 23.8 |
Q3 2006 | 0.6 | 3.4 | 0.8 | 3.7 | 4.6 | 3.8 | 4.9 | 4.8 | 5.0 | 6.3 | 6.6 | 8.3 | 13,323 | 191 | 225 | 18.6 |
Q4 2006 | 3.4 | 5.0 | 5.2 | 4.5 | 4.4 | -1.6 | 4.9 | 4.6 | 4.7 | 6.0 | 6.2 | 8.3 | 14,216 | 191 | 230 | 12.7 |
Q1 2007 | 1.2 | 5.1 | 3.0 | 6.8 | 4.5 | 4.0 | 5.0 | 4.6 | 4.8 | 6.0 | 6.2 | 8.3 | 14,354 | 189 | 237 | 19.6 |
Q2 2007 | 2.6 | 5.3 | 1.8 | 5.3 | 4.5 | 4.6 | 4.7 | 4.7 | 4.9 | 6.2 | 6.4 | 8.3 | 15,163 | 184 | 246 | 18.9 |
Q3 2007 | 2.4 | 4.6 | 0.7 | 3.0 | 4.7 | 2.6 | 4.3 | 4.5 | 4.8 | 6.5 | 6.6 | 8.2 | 15,318 | 178 | 251 | 30.8 |
Q4 2007 | 2.5 | 4.2 | 0.6 | 4.8 | 4.8 | 5.0 | 3.4 | 3.8 | 4.4 | 6.3 | 6.2 | 7.5 | 14,754 | 173 | 250 | 31.1 |
Q1 2008 | -1.6 | -0.2 | 0.7 | 4.0 | 5.0 | 4.4 | 2.1 | 2.8 | 3.9 | 6.4 | 5.9 | 6.2 | 13,284 | 166 | 230 | 32.2 |
Q2 2008 | 2.3 | 4.4 | 8.0 | 12.3 | 5.3 | 5.3 | 1.6 | 3.2 | 4.1 | 6.7 | 6.1 | 5.1 | 13,016 | 158 | 234 | 24.1 |
Q3 2008 | -2.1 | 0.9 | -7.8 | -3.8 | 6.0 | 6.3 | 1.5 | 3.1 | 4.1 | 7.1 | 6.3 | 5.0 | 11,826 | 151 | 228 | 46.7 |
Q4 2008 | -8.5 | -7.6 | 4.4 | -2.1 | 6.9 | -8.9 | 0.3 | 2.2 | 3.7 | 9.7 | 5.8 | 4.1 | 9,057 | 144 | 221 | 80.9 |
Q1 2009 | -4.6 | -4.8 | -0.9 | -3.5 | 8.3 | -2.7 | 0.2 | 1.9 | 3.2 | 9.1 | 5.1 | 3.3 | 8,044 | 139 | 208 | 56.7 |
Q2 2009 | -0.7 | -1.4 | 2.2 | 3.8 | 9.3 | 2.1 | 0.2 | 2.3 | 3.7 | 8.1 | 5.0 | 3.3 | 9,343 | 139 | 171 | 42.3 |
Q3 2009 | 1.5 | 1.9 | -4.8 | -2.1 | 9.6 | 3.5 | 0.2 | 2.5 | 3.8 | 6.5 | 5.2 | 3.3 | 10,813 | 140 | 166 | 31.3 |
Q4 2009 | 4.3 | 5.7 | 0.8 | 3.9 | 9.9 | 3.2 | 0.1 | 2.3 | 3.7 | 5.8 | 4.9 | 3.3 | 11,385 | 140 | 154 | 30.7 |
Q1 2010 | 2.0 | 3.1 | 3.1 | 4.7 | 9.8 | 0.6 | 0.1 | 2.4 | 3.9 | 5.6 | 5.0 | 3.3 | 12,033 | 140 | 160 | 27.3 |
Q2 2010 | 3.9 | 6.0 | 6.8 | 7.5 | 9.6 | -0.1 | 0.1 | 2.3 | 3.6 | 5.4 | 4.9 | 3.3 | 10,646 | 139 | 172 | 45.8 |
Q3 2010 | 3.1 | 4.4 | 2.6 | 3.4 | 9.5 | 1.2 | 0.2 | 1.6 | 2.9 | 4.8 | 4.4 | 3.3 | 11,814 | 137 | 171 | 32.9 |
Q4 2010 | 2.1 | 4.5 | 1.5 | 4.1 | 9.5 | 3.3 | 0.1 | 1.5 | 3.0 | 4.7 | 4.4 | 3.3 | 13,132 | 135 | 172 | 23.5 |
Q1 2011 | -1.0 | 1.1 | 3.9 | 7.4 | 9.0 | 4.3 | 0.1 | 2.1 | 3.5 | 5.0 | 4.8 | 3.3 | 13,909 | 134 | 178 | 29.4 |
Q2 2011 | 2.7 | 5.5 | -1.0 | 2.9 | 9.1 | 4.6 | 0.0 | 1.8 | 3.3 | 4.8 | 4.7 | 3.3 | 13,844 | 134 | 175 | 22.7 |
Q3 2011 | -0.2 | 2.3 | 1.8 | 3.7 | 9.0 | 2.6 | 0.0 | 1.1 | 2.5 | 4.5 | 4.3 | 3.3 | 11,677 | 134 | 173 | 48.0 |
Q4 2011 | 4.6 | 5.1 | 1.1 | 2.5 | 8.6 | 1.8 | 0.0 | 1.0 | 2.1 | 4.8 | 4.0 | 3.3 | 13,019 | 134 | 183 | 45.5 |
Q1 2012 | 3.3 | 5.8 | 7.6 | 10.4 | 8.3 | 2.3 | 0.1 | 0.9 | 2.1 | 4.4 | 3.9 | 3.3 | 14,628 | 136 | 183 | 23.0 |
Q2 2012 | 1.8 | 3.5 | 3.6 | 4.6 | 8.2 | 0.8 | 0.1 | 0.8 | 1.8 | 4.3 | 3.8 | 3.3 | 14,100 | 139 | 182 | 26.7 |
Q3 2012 | 0.7 | 2.8 | -2.6 | -1.5 | 8.0 | 1.8 | 0.1 | 0.7 | 1.6 | 3.9 | 3.6 | 3.3 | 14,895 | 142 | 185 | 20.5 |
Q4 2012 | 0.4 | 2.5 | 11.6 | 14.2 | 7.8 | 2.7 | 0.1 | 0.7 | 1.7 | 3.6 | 3.4 | 3.3 | 14,835 | 145 | 188 | 22.7 |
Q1 2013 | 3.5 | 5.2 | -14.9 | -13.6 | 7.7 | 1.6 | 0.1 | 0.8 | 1.9 | 3.7 | 3.5 | 3.3 | 16,396 | 148 | 191 | 19.0 |
Q2 2013 | 0.6 | 1.7 | 3.0 | 3.3 | 7.5 | -0.4 | 0.1 | 0.9 | 2.0 | 3.8 | 3.7 | 3.3 | 16,771 | 152 | 202 | 20.5 |
Q3 2013 | 3.2 | 5.2 | 1.5 | 3.2 | 7.2 | 2.2 | 0.0 | 1.5 | 2.7 | 4.7 | 4.4 | 3.3 | 17,718 | 156 | 213 | 17.0 |
Q4 2013 | 2.9 | 5.4 | 1.2 | 2.9 | 6.9 | 1.5 | 0.1 | 1.4 | 2.8 | 4.5 | 4.3 | 3.3 | 19,413 | 159 | 213 | 20.3 |
Q1 2014 | -1.4 | 0.3 | 5.1 | 7.1 | 6.7 | 2.5 | 0.0 | 1.6 | 2.8 | 4.4 | 4.4 | 3.3 | 19,711 | 161 | 210 | 21.4 |
Q2 2014 | 5.2 | 7.6 | 5.4 | 7.5 | 6.2 | 2.1 | 0.0 | 1.7 | 2.7 | 4.0 | 4.2 | 3.3 | 20,569 | 162 | 219 | 17.0 |
Q3 2014 | 4.7 | 6.6 | 4.6 | 5.8 | 6.1 | 1.0 | 0.0 | 1.7 | 2.5 | 3.9 | 4.1 | 3.3 | 20,459 | 164 | 223 | 17.0 |
Q4 2014 | 1.8 | 2.5 | 5.7 | 5.2 | 5.7 | -1.0 | 0.0 | 1.6 | 2.3 | 4.0 | 4.0 | 3.3 | 21,425 | 167 | 231 | 26.3 |
Q1 2015 | 3.3 | 3.1 | 5.4 | 3.7 | 5.5 | -2.6 | 0.0 | 1.5 | 2.0 | 3.9 | 3.7 | 3.3 | 21,708 | 169 | 241 | 22.4 |
Q2 2015 | 2.3 | 4.6 | 1.1 | 3.1 | 5.4 | 2.8 | 0.0 | 1.5 | 2.2 | 3.9 | 3.8 | 3.3 | 21,631 | 171 | 246 | 18.9 |
Q3 2015 | 1.3 | 2.5 | 2.3 | 3.3 | 5.1 | 1.5 | 0.0 | 1.6 | 2.3 | 4.3 | 4.0 | 3.3 | 19,959 | 174 | 246 | 40.7 |
Q4 2015 | 0.6 | 0.5 | 2.5 | 2.1 | 5.0 | 0.0 | 0.1 | 1.6 | 2.2 | 4.4 | 3.9 | 3.3 | 21,101 | 176 | 244 | 24.4 |
Q1 2016 | 2.4 | 2.0 | 3.1 | 3.3 | 4.9 | -0.2 | 0.3 | 1.4 | 2.0 | 4.5 | 3.7 | 3.5 | 21,179 | 178 | 240 | 28.1 |
Q2 2016 | 1.2 | 4.1 | -0.7 | 1.9 | 4.9 | 3.2 | 0.3 | 1.3 | 1.8 | 3.9 | 3.6 | 3.5 | 21,622 | 180 | 248 | 25.8 |
Q3 2016 | 2.4 | 3.6 | 1.9 | 3.5 | 4.9 | 1.7 | 0.3 | 1.2 | 1.6 | 3.5 | 3.4 | 3.5 | 22,469 | 183 | 257 | 18.1 |
Q4 2016 | 2.0 | 4.2 | 2.1 | 4.1 | 4.8 | 2.6 | 0.4 | 1.7 | 2.2 | 3.9 | 3.8 | 3.5 | 23,277 | 186 | 257 | 22.5 |
Q1 2017 | 1.7 | 3.9 | 4.0 | 6.4 | 4.6 | 2.8 | 0.6 | 2.0 | 2.5 | 4.0 | 4.2 | 3.8 | 24,508 | 188 | 253 | 13.1 |
Q2 2017 | 2.0 | 3.3 | 4.0 | 5.1 | 4.4 | 0.5 | 0.9 | 1.8 | 2.3 | 3.8 | 4.0 | 4.0 | 25,125 | 191 | 266 | 16.0 |
Q3 2017 | 3.4 | 5.4 | 2.3 | 3.8 | 4.3 | 1.9 | 1.0 | 1.8 | 2.3 | 3.7 | 3.9 | 4.3 | 26,149 | 194 | 269 | 16.0 |
Q4 2017 | 4.1 | 7.0 | 1.6 | 4.2 | 4.2 | 3.2 | 1.2 | 2.1 | 2.4 | 3.7 | 3.9 | 4.3 | 27,673 | 197 | 273 | 13.1 |
Q1 2018 | 2.8 | 5.3 | 4.1 | 7.1 | 4.0 | 3.3 | 1.6 | 2.5 | 2.8 | 4.1 | 4.3 | 4.5 | 27,383 | 200 | 275 | 37.3 |
Q2 2018 | 2.8 | 6.4 | 3.4 | 5.6 | 3.9 | 2.3 | 1.8 | 2.8 | 2.9 | 4.5 | 4.5 | 4.8 | 28,314 | 202 | 276 | 23.6 |
Q3 2018 | 2.9 | 4.3 | 4.3 | 5.8 | 3.8 | 1.7 | 2.0 | 2.8 | 2.9 | 4.5 | 4.6 | 5.0 | 30,190 | 204 | 276 | 16.1 |
Q4 2018 | 0.7 | 2.6 | 4.4 | 6.0 | 3.8 | 1.5 | 2.3 | 2.9 | 3.0 | 4.8 | 4.8 | 5.3 | 25,725 | 206 | 273 | 36.1 |
Q1 2019 | 2.2 | 3.8 | 5.3 | 6.1 | 3.9 | 1.0 | 2.4 | 2.5 | 2.7 | 4.5 | 4.4 | 5.5 | 29,194 | 208 | 285 | 25.5 |
Q2 2019 | 2.7 | 5.0 | 0.0 | 2.4 | 3.6 | 3.2 | 2.3 | 2.1 | 2.4 | 4.0 | 4.0 | 5.5 | 30,244 | 210 | 299 | 20.6 |
Q3 2019 | 3.6 | 5.0 | 3.3 | 4.4 | 3.6 | 1.5 | 2.0 | 1.7 | 1.8 | 3.4 | 3.7 | 5.3 | 30,442 | 212 | 296 | 24.6 |
Q4 2019 | 1.8 | 3.3 | 2.6 | 4.1 | 3.6 | 2.5 | 1.6 | 1.6 | 1.8 | 3.3 | 3.7 | 4.8 | 33,035 | 215 | 294 | 20.6 |
Q1 2020 | -4.6 | -3.1 | 2.4 | 3.9 | 3.8 | 1.3 | 1.1 | 1.2 | 1.4 | 3.4 | 3.5 | 4.4 | 25,985 | 218 | 299 | 82.7 |
Q2 2020 | -29.9 | -30.9 | 46.5 | 43.8 | 13.0 | -3.4 | 0.1 | 0.4 | 0.7 | 3.4 | 3.2 | 3.3 | 31,577 | 220 | 295 | 57.1 |
Q3 2020 | 35.3 | 40.1 | -15.3 | -12.4 | 8.8 | 4.8 | 0.1 | 0.3 | 0.6 | 2.4 | 3.0 | 3.3 | 34,306 | 227 | 301 | 33.6 |
Q4 2020 | 3.9 | 6.6 | -9.0 | -7.5 | 6.8 | 2.2 | 0.1 | 0.4 | 0.9 | 2.3 | 2.8 | 3.3 | 39,220 | 235 | 313 | 40.3 |
Q1 2021 | 6.3 | 11.7 | 52.4 | 59.2 | 6.2 | 4.1 | 0.1 | 0.6 | 1.4 | 2.4 | 2.9 | 3.3 | 41,603 | 243 | 314 | 37.2 |
Q2 2021 | 7.0 | 13.8 | -28.8 | -24.2 | 5.9 | 8.2 | 0.0 | 0.8 | 1.6 | 2.6 | 3.0 | 3.3 | 44,904 | 255 | 322 | 27.6 |
Q3 2021 | 2.7 | 9.0 | -4.6 | 0.8 | 5.1 | 6.7 | 0.0 | 0.8 | 1.4 | 2.4 | 2.9 | 3.3 | 44,706 | 266 | 346 | 25.7 |
Q4 2021 | 7.0 | 14.3 | -4.9 | 1.0 | 4.2 | 7.9 | 0.1 | 1.2 | 1.6 | 2.7 | 3.1 | 3.3 | 48,634 | 277 | 358 | 31.1 |
Q1 2022 | -1.6 | 6.6 | -10.6 | -3.9 | 3.8 | 9.2 | 0.3 | 1.9 | 2.0 | 3.5 | 3.8 | 3.3 | 45,847 | 290 | 350 | 36.5 |
Q2 2022 | -0.6 | 8.5 | -2.3 | 4.8 | 3.6 | 10.5 | 1.1 | 3.0 | 3.0 | 4.9 | 5.3 | 3.9 | 37,977 | 298 | 349 | 34.8 |
Q3 2022 | 3.2 | 7.7 | 1.0 | 5.4 | 3.6 | 5.7 | 2.7 | 3.3 | 3.2 | 5.3 | 5.6 | 5.4 | 36,098 | 298 | 358 | 32.6 |
Q4 2022 | 1.7 | 5.7 | 2.1 | 6.0 | 3.6 | 3.1 | 4.0 | 4.1 | 3.9 | 6.1 | 6.7 | 6.8 | 38,521 | 300 | 358 | 33.6 |
Note: Refer to Notes Regarding Scenario Variables for more information on the definitions and sources of historical observations of the variables in the table.
Table 2.B. Historical data: International variables, Q1:2000–Q4:2022
Percent, unless otherwise indicated
Date | Euro area realGDP growth |
Euro area inflation | Euro area bilateral dollar exchange rate (USD/euro) |
Developing Asia real GDP growth |
Developing Asia inflation |
Developing Asia bilateral dollar exchange rate (F/USD, index)1 |
Japan real GDP growth |
Japan inflation |
Japan bilateral dollar exchange rate (yen/USD) |
U.K. real GDP growth |
U.K. inflation |
U.K. bilateral dollar exchange rate (USD/pound) |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Q1 2000 | 5.1 | 2.6 | 0.957 | 7.3 | 1.5 | 100.0 | 7.0 | -0.5 | 102.7 | 4.7 | 0.3 | 1.592 |
Q2 2000 | 3.7 | 0.9 | 0.955 | 6.9 | -0.3 | 100.7 | 1.9 | -1.1 | 106.1 | 2.6 | 0.5 | 1.513 |
Q3 2000 | 2.3 | 3.4 | 0.884 | 7.8 | 2.2 | 101.4 | 0.1 | -0.4 | 107.9 | 2.1 | 1.0 | 1.479 |
Q4 2000 | 2.8 | 2.8 | 0.939 | 3.6 | 2.5 | 105.2 | 4.0 | -1.0 | 114.4 | 1.7 | 1.9 | 1.496 |
Q1 2001 | 4.1 | 1.2 | 0.879 | 4.8 | 1.7 | 106.1 | 3.0 | 0.7 | 125.5 | 3.5 | -0.1 | 1.419 |
Q2 2001 | 0.4 | 4.0 | 0.847 | 5.3 | 2.1 | 106.2 | -3.0 | -1.9 | 124.7 | 1.5 | 3.2 | 1.408 |
Q3 2001 | 0.3 | 1.5 | 0.910 | 4.9 | 1.3 | 106.5 | -4.3 | -0.7 | 119.2 | 1.9 | 1.0 | 1.469 |
Q4 2001 | 0.4 | 1.7 | 0.890 | 8.4 | 0.0 | 106.9 | -1.4 | -1.8 | 131.0 | 0.7 | -0.1 | 1.454 |
Q1 2002 | 0.6 | 3.1 | 0.872 | 7.8 | 0.5 | 107.4 | 0.7 | -1.2 | 132.7 | 1.4 | 2.0 | 1.425 |
Q2 2002 | 2.1 | 2.0 | 0.986 | 8.1 | 1.1 | 104.8 | 3.3 | 0.3 | 119.9 | 2.1 | 0.9 | 1.525 |
Q3 2002 | 1.5 | 1.6 | 0.988 | 7.3 | 1.5 | 105.5 | 1.3 | -0.4 | 121.7 | 2.9 | 1.3 | 1.570 |
Q4 2002 | 1.0 | 2.3 | 1.049 | 6.7 | 0.7 | 104.5 | 1.1 | -0.8 | 118.8 | 3.4 | 1.9 | 1.610 |
Q1 2003 | -1.3 | 3.3 | 1.090 | 6.6 | 3.6 | 105.5 | 0.3 | 0.0 | 118.1 | 2.6 | 1.7 | 1.579 |
Q2 2003 | 0.4 | 0.5 | 1.150 | 1.9 | 1.1 | 104.0 | 2.8 | 0.3 | 119.9 | 3.5 | 0.2 | 1.653 |
Q3 2003 | 2.1 | 2.1 | 1.165 | 14.6 | 0.1 | 102.6 | 1.2 | -0.7 | 111.4 | 4.0 | 1.7 | 1.662 |
Q4 2003 | 3.0 | 2.3 | 1.260 | 12.8 | 5.5 | 103.4 | 4.4 | -0.7 | 107.1 | 3.1 | 1.7 | 1.784 |
Q1 2004 | 2.0 | 2.2 | 1.229 | 5.8 | 4.0 | 101.4 | 3.0 | 0.6 | 104.2 | 1.8 | 1.4 | 1.840 |
Q2 2004 | 2.5 | 2.6 | 1.218 | 7.1 | 4.1 | 102.8 | 0.0 | -0.3 | 109.4 | 2.1 | 0.8 | 1.813 |
Q3 2004 | 0.9 | 2.0 | 1.242 | 8.3 | 4.1 | 102.7 | 2.5 | -0.1 | 110.2 | 1.0 | 1.1 | 1.809 |
Q4 2004 | 1.6 | 2.4 | 1.354 | 6.3 | 0.8 | 98.9 | -0.7 | 2.0 | 102.7 | 1.3 | 2.4 | 1.916 |
Q1 2005 | 0.8 | 1.4 | 1.297 | 10.6 | 2.9 | 98.5 | 2.1 | -1.2 | 107.2 | 3.0 | 2.6 | 1.889 |
Q2 2005 | 2.5 | 2.2 | 1.210 | 8.7 | 1.5 | 98.9 | 3.1 | -1.0 | 110.9 | 3.8 | 1.8 | 1.793 |
Q3 2005 | 3.0 | 3.1 | 1.206 | 9.4 | 2.4 | 98.5 | 4.1 | -1.1 | 113.3 | 3.5 | 2.8 | 1.770 |
Q4 2005 | 2.6 | 2.5 | 1.184 | 11.6 | 1.6 | 98.1 | 0.7 | 0.4 | 117.9 | 4.2 | 1.4 | 1.719 |
Q1 2006 | 3.5 | 1.7 | 1.214 | 10.8 | 2.4 | 96.7 | 0.6 | 1.1 | 117.5 | 1.4 | 1.9 | 1.739 |
Q2 2006 | 4.5 | 2.5 | 1.278 | 7.2 | 3.2 | 96.6 | 0.6 | 0.4 | 114.5 | 0.9 | 3.0 | 1.849 |
Q3 2006 | 2.4 | 2.0 | 1.269 | 10.2 | 2.2 | 96.3 | -0.8 | 0.4 | 118.0 | 0.6 | 3.3 | 1.872 |
Q4 2006 | 4.8 | 0.9 | 1.320 | 11.4 | 3.6 | 94.5 | 5.5 | -0.6 | 119.0 | 1.8 | 2.6 | 1.959 |
Q1 2007 | 2.4 | 2.3 | 1.337 | 13.8 | 3.6 | 93.9 | 2.7 | -0.7 | 117.6 | 4.2 | 2.5 | 1.969 |
Q2 2007 | 2.9 | 2.3 | 1.352 | 10.5 | 4.9 | 91.8 | 0.1 | 0.4 | 123.4 | 2.7 | 1.8 | 2.006 |
Q3 2007 | 1.8 | 2.1 | 1.422 | 8.6 | 7.6 | 90.5 | -2.1 | 0.3 | 115.0 | 3.1 | 0.3 | 2.039 |
Q4 2007 | 2.1 | 4.9 | 1.460 | 13.1 | 5.9 | 89.4 | 1.8 | 2.0 | 111.7 | 2.7 | 4.0 | 1.984 |
Q1 2008 | 2.1 | 4.2 | 1.581 | 7.0 | 8.1 | 88.0 | 1.4 | 1.4 | 99.9 | 2.0 | 3.4 | 1.986 |
Q2 2008 | -1.3 | 3.2 | 1.575 | 6.0 | 6.3 | 88.7 | -2.4 | 1.7 | 106.2 | -1.9 | 5.8 | 1.991 |
Q3 2008 | -2.1 | 3.2 | 1.408 | 2.9 | 3.0 | 91.6 | -4.8 | 3.8 | 105.9 | -5.9 | 5.9 | 1.780 |
Q4 2008 | -7.1 | -1.4 | 1.392 | 0.6 | -1.1 | 92.3 | -9.5 | -2.4 | 90.8 | -8.6 | 0.4 | 1.462 |
Q1 2009 | -11.8 | -1.0 | 1.326 | 4.2 | -1.4 | 94.3 | -17.9 | -3.5 | 99.2 | -7.5 | -0.2 | 1.430 |
Q2 2009 | -0.1 | 0.0 | 1.402 | 15.0 | 2.3 | 92.3 | 8.0 | -1.5 | 96.4 | -1.1 | 2.3 | 1.645 |
Q3 2009 | 1.6 | 1.1 | 1.463 | 12.6 | 4.1 | 91.3 | -0.2 | -1.5 | 89.5 | 0.5 | 3.6 | 1.600 |
Q4 2009 | 1.7 | 1.6 | 1.433 | 9.7 | 5.0 | 90.7 | 5.1 | -1.4 | 93.1 | 1.4 | 2.8 | 1.617 |
Q1 2010 | 1.8 | 1.8 | 1.353 | 9.6 | 4.4 | 89.8 | 4.3 | 1.0 | 93.4 | 3.9 | 4.2 | 1.519 |
Q2 2010 | 3.9 | 1.9 | 1.229 | 9.5 | 3.4 | 91.1 | 4.8 | -1.4 | 88.5 | 4.7 | 3.3 | 1.495 |
Q3 2010 | 1.7 | 1.6 | 1.360 | 8.8 | 4.2 | 88.4 | 7.5 | -2.0 | 83.5 | 2.6 | 2.2 | 1.573 |
Q4 2010 | 2.4 | 2.6 | 1.327 | 9.6 | 7.5 | 87.4 | -3.2 | 1.4 | 81.7 | 0.6 | 3.9 | 1.539 |
Q1 2011 | 3.7 | 3.7 | 1.418 | 9.6 | 6.2 | 86.5 | -4.1 | -0.4 | 82.8 | 1.0 | 7.0 | 1.605 |
Q2 2011 | -0.1 | 3.1 | 1.452 | 6.8 | 5.4 | 85.3 | -3.5 | -0.7 | 80.6 | 0.2 | 4.6 | 1.607 |
Q3 2011 | 0.6 | 1.3 | 1.345 | 5.6 | 5.3 | 87.4 | 10.1 | 0.4 | 77.0 | 0.6 | 3.5 | 1.562 |
Q4 2011 | -1.7 | 3.5 | 1.297 | 6.5 | 3.0 | 87.3 | -0.5 | -0.6 | 77.0 | -0.2 | 3.4 | 1.554 |
Q1 2012 | -0.9 | 2.9 | 1.333 | 7.6 | 3.2 | 86.3 | 5.7 | 2.3 | 82.4 | 3.4 | 2.3 | 1.599 |
Q2 2012 | -1.1 | 2.2 | 1.267 | 5.8 | 3.9 | 88.1 | -3.6 | -1.4 | 79.8 | -0.2 | 1.9 | 1.569 |
Q3 2012 | -0.4 | 1.5 | 1.286 | 6.6 | 2.2 | 86.3 | -1.5 | -2.0 | 77.9 | 5.1 | 2.1 | 1.613 |
Q4 2012 | -1.8 | 2.6 | 1.319 | 7.2 | 3.5 | 86.0 | -0.3 | 0.1 | 86.6 | -0.4 | 4.2 | 1.626 |
Q1 2013 | -1.3 | 1.3 | 1.282 | 6.7 | 4.6 | 86.3 | 5.7 | 0.6 | 94.2 | 0.9 | 3.0 | 1.519 |
Q2 2013 | 2.1 | 0.2 | 1.301 | 6.2 | 2.8 | 87.2 | 3.6 | 0.0 | 99.2 | 2.7 | 1.5 | 1.521 |
Q3 2013 | 1.2 | 1.1 | 1.354 | 7.7 | 3.6 | 86.6 | 3.9 | 2.7 | 98.3 | 3.0 | 2.1 | 1.618 |
Q4 2013 | 1.2 | 0.5 | 1.378 | 6.8 | 3.8 | 85.8 | -0.5 | 2.4 | 105.3 | 2.6 | 1.7 | 1.657 |
Q1 2014 | 1.7 | 0.9 | 1.378 | 6.1 | 1.4 | 86.9 | 3.3 | 1.0 | 103.0 | 3.8 | 1.8 | 1.668 |
Q2 2014 | 0.8 | -0.4 | 1.369 | 7.4 | 2.6 | 86.7 | -7.0 | 8.3 | 101.3 | 3.5 | 1.4 | 1.711 |
Q3 2014 | 2.0 | 0.1 | 1.263 | 6.6 | 2.5 | 87.0 | 0.3 | 1.9 | 109.7 | 3.1 | 0.8 | 1.622 |
Q4 2014 | 1.4 | 0.0 | 1.210 | 5.8 | 0.9 | 88.1 | 1.9 | -0.8 | 119.9 | 2.6 | -0.3 | 1.558 |
Q1 2015 | 2.6 | -0.8 | 1.074 | 6.3 | 0.9 | 88.1 | 6.4 | 0.1 | 120.0 | 1.7 | -1.3 | 1.485 |
Q2 2015 | 1.9 | 2.4 | 1.115 | 6.9 | 2.8 | 88.5 | 0.5 | 1.1 | 122.1 | 2.6 | 0.8 | 1.573 |
Q3 2015 | 1.7 | -0.2 | 1.116 | 6.5 | 2.8 | 91.1 | 0.4 | 0.3 | 119.8 | 1.7 | 0.7 | 1.512 |
Q4 2015 | 1.9 | -0.4 | 1.086 | 5.7 | 1.1 | 92.3 | -0.7 | -0.8 | 120.3 | 3.0 | 0.0 | 1.475 |
Q1 2016 | 2.2 | -1.4 | 1.139 | 7.0 | 3.0 | 91.8 | 3.0 | -0.5 | 112.4 | 1.5 | 0.0 | 1.438 |
Q2 2016 | 0.9 | 1.5 | 1.103 | 6.9 | 3.0 | 94.2 | -0.6 | 0.0 | 102.8 | 2.5 | 0.7 | 1.324 |
Q3 2016 | 1.9 | 1.3 | 1.124 | 6.6 | 1.2 | 93.7 | 0.8 | -0.4 | 101.2 | 1.8 | 2.0 | 1.302 |
Q4 2016 | 3.1 | 1.7 | 1.055 | 5.8 | 1.6 | 97.6 | 0.6 | 2.1 | 116.8 | 2.6 | 2.1 | 1.234 |
Q1 2017 | 2.8 | 2.6 | 1.070 | 6.2 | 1.3 | 95.2 | 3.3 | -0.5 | 111.4 | 3.0 | 3.8 | 1.254 |
Q2 2017 | 3.2 | 0.5 | 1.141 | 6.7 | 2.3 | 94.8 | 1.3 | 0.7 | 112.4 | 2.2 | 3.1 | 1.300 |
Q3 2017 | 3.1 | 1.1 | 1.181 | 5.8 | 2.3 | 93.7 | 3.4 | 0.4 | 112.6 | 2.1 | 2.2 | 1.340 |
Q4 2017 | 3.3 | 1.7 | 1.202 | 6.0 | 2.4 | 91.1 | 0.5 | 1.6 | 112.7 | 2.5 | 3.1 | 1.353 |
Q1 2018 | 0.0 | 1.8 | 1.232 | 8.5 | 2.5 | 89.1 | 0.4 | 2.2 | 106.2 | 0.6 | 2.5 | 1.403 |
Q2 2018 | 2.2 | 2.2 | 1.168 | 6.4 | 1.9 | 93.5 | 1.1 | -1.1 | 110.7 | 1.8 | 1.9 | 1.320 |
Q3 2018 | 0.0 | 2.8 | 1.162 | 2.9 | 3.0 | 97.3 | -2.0 | 1.8 | 113.5 | 2.2 | 2.5 | 1.305 |
Q4 2018 | 2.6 | 1.0 | 1.146 | 5.3 | 1.0 | 96.3 | -0.5 | 0.7 | 109.7 | 1.0 | 2.1 | 1.276 |
Q1 2019 | 2.5 | -0.5 | 1.123 | 8.4 | 1.1 | 94.4 | 0.9 | -0.5 | 110.7 | 2.5 | 0.9 | 1.303 |
Q2 2019 | 1.3 | 2.2 | 1.137 | 6.3 | 5.0 | 96.5 | 1.2 | 1.2 | 107.8 | 0.4 | 2.6 | 1.270 |
Q3 2019 | 0.8 | 1.2 | 1.091 | 0.5 | 3.5 | 99.9 | 0.9 | 0.0 | 108.1 | 2.5 | 1.7 | 1.231 |
Q4 2019 | 0.1 | 1.3 | 1.123 | 3.9 | 6.4 | 97.9 | -10.4 | 1.3 | 108.7 | -0.1 | 0.4 | 1.327 |
Q1 2020 | -12.8 | -0.5 | 1.102 | -23.4 | 3.7 | 101.5 | 1.8 | 0.1 | 107.5 | -10.2 | 2.0 | 1.245 |
Q2 2020 | -38.5 | -1.2 | 1.124 | 35.0 | -1.9 | 97.5 | -28.2 | -0.8 | 107.8 | -61.0 | -1.7 | 1.237 |
Q3 2020 | 59.3 | 0.4 | 1.172 | 20.0 | 2.1 | 95.8 | 24.2 | -0.5 | 105.6 | 84.9 | 1.7 | 1.292 |
Q4 2020 | -1.0 | 0.4 | 1.223 | 12.7 | -0.4 | 92.8 | 7.9 | -2.5 | 103.2 | 4.9 | 0.1 | 1.366 |
Q1 2021 | -0.2 | 4.6 | 1.174 | 5.6 | 3.2 | 93.5 | -0.6 | 1.8 | 110.6 | -4.1 | 2.4 | 1.380 |
Q2 2021 | 8.2 | 1.9 | 1.185 | 4.3 | 2.4 | 91.7 | 1.3 | -1.6 | 111.1 | 28.8 | 4.0 | 1.381 |
Q3 2021 | 9.3 | 4.6 | 1.158 | 0.6 | 1.2 | 93.0 | -1.8 | 1.6 | 111.5 | 7.1 | 4.7 | 1.347 |
Q4 2021 | 2.2 | 7.6 | 1.132 | 7.7 | 2.7 | 92.5 | 4.9 | 0.4 | 115.2 | 6.2 | 8.6 | 1.350 |
Q1 2022 | 2.5 | 10.6 | 1.109 | 6.1 | 2.0 | 92.9 | -1.8 | 3.0 | 121.4 | 2.5 | 7.7 | 1.315 |
Q2 2022 | 3.2 | 9.5 | 1.047 | -2.8 | 6.9 | 98.5 | 4.5 | 4.7 | 135.7 | 0.2 | 16.0 | 1.216 |
Q3 2022 | 1.3 | 9.7 | 0.978 | 6.3 | 2.5 | 104.1 | -0.8 | 3.4 | 144.7 | -1.2 | 8.0 | 1.113 |
Q4 2022 | -0.7 | 10.1 | 1.070 | 4.0 | 3.0 | 101.4 | 2.7 | 2.5 | 131.8 | -0.2 | 8.5 | 1.208 |
Note: Refer to Notes Regarding Scenario Variables for more information on the definitions and sources of historical observations of the variables in the table.
1. F/USD denotes foreign currency index, relative to the U.S. dollar, obtained as a weighted average of the exchange rates of the countries in the developing Asia bloc. Return to table
Table 3.A. Supervisory baseline scenario: Domestic variables, Q1:2023–Q1:2026
Percent, unless otherwise indicated
Date | Real GDP growth |
Nominal GDP growth |
Real dispos- able income growth |
Nominal dispos- able income growth |
Unem- ployment rate |
CPI inflation rate |
3-month Treasury rate |
5-year Treasury yield |
10-year Treasury yield |
BBB corpo- rate yield |
Mort- gage rate |
Prime rate |
Level | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Dow Jones Total Stock Market Index | House Price Index |
Com- mercial Real Estate Price Index |
Market Volatility Index |
|||||||||||||
Q1 2023 | -0.5 | 2.9 | 1.8 | 5.1 | 3.9 | 3.2 | 4.7 | 4.0 | 3.9 | 5.9 | 6.2 | 7.4 | 38,521 | 301 | 361 | 30.7 |
Q2 2023 | -0.9 | 2.1 | 0.7 | 3.5 | 4.3 | 2.9 | 4.8 | 4.0 | 3.8 | 5.8 | 5.9 | 7.6 | 38,521 | 303 | 364 | 29.0 |
Q3 2023 | 0.0 | 2.6 | 1.5 | 4.0 | 4.6 | 2.7 | 4.6 | 3.9 | 3.7 | 5.6 | 5.6 | 7.4 | 38,521 | 304 | 366 | 27.2 |
Q4 2023 | 0.9 | 3.4 | 2.0 | 4.3 | 4.8 | 2.4 | 4.4 | 3.7 | 3.6 | 5.5 | 5.4 | 7.2 | 38,521 | 306 | 369 | 28.4 |
Q1 2024 | 1.5 | 3.9 | 2.4 | 4.6 | 4.9 | 2.2 | 4.0 | 3.6 | 3.5 | 5.4 | 5.2 | 6.8 | 38,521 | 307 | 372 | 28.5 |
Q2 2024 | 1.9 | 4.1 | 2.4 | 4.5 | 4.9 | 2.1 | 3.7 | 3.5 | 3.4 | 5.3 | 5.0 | 6.5 | 38,521 | 309 | 375 | 28.6 |
Q3 2024 | 2.2 | 4.3 | 2.4 | 4.3 | 4.8 | 2.2 | 3.3 | 3.4 | 3.3 | 5.3 | 4.9 | 6.2 | 38,521 | 310 | 377 | 28.4 |
Q4 2024 | 2.3 | 4.4 | 2.4 | 4.4 | 4.7 | 2.1 | 3.1 | 3.3 | 3.3 | 5.2 | 4.9 | 6.0 | 38,521 | 312 | 380 | 28.4 |
Q1 2025 | 2.2 | 4.4 | 2.1 | 4.2 | 4.6 | 2.2 | 3.0 | 3.2 | 3.3 | 5.2 | 4.8 | 5.9 | 38,521 | 314 | 383 | 28.5 |
Q2 2025 | 2.1 | 3.9 | 2.0 | 4.1 | 4.6 | 2.2 | 3.0 | 3.1 | 3.3 | 5.2 | 4.8 | 5.9 | 38,521 | 315 | 386 | 28.5 |
Q3 2025 | 2.1 | 3.8 | 2.0 | 4.0 | 4.6 | 2.2 | 3.0 | 3.0 | 3.3 | 5.2 | 4.8 | 5.9 | 38,521 | 317 | 389 | 28.5 |
Q4 2025 | 2.1 | 3.8 | 2.0 | 4.0 | 4.6 | 2.2 | 3.0 | 3.0 | 3.2 | 5.2 | 4.8 | 5.9 | 38,521 | 318 | 392 | 28.5 |
Q1 2026 | 2.0 | 3.9 | 2.0 | 4.0 | 4.6 | 2.2 | 3.0 | 2.9 | 3.2 | 5.2 | 4.8 | 5.9 | 38,521 | 320 | 395 | 28.4 |
Note: Refer to Notes Regarding Scenario Variables for more information on the definitions and sources of historical observations of the variables in the table.
Table 3.B. Supervisory baseline scenario: International variables, Q1:2023–Q1:2026
Percent, unless otherwise indicated
Date | Euro area realGDP growth |
Euro area inflation | Euro area bilateral dollar exchange rate (USD/euro) |
Developing Asia real GDP growth |
Developing Asia inflation |
Developing Asia bilateral dollar exchange rate (F/USD, index)1 |
Japan real GDP growth |
Japan inflation |
Japan bilateral dollar exchange rate (yen/USD) |
U.K. real GDP growth |
U.K. inflation |
U.K. bilateral dollar exchange rate (USD/pound) |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Q1 2023 | -0.6 | 6.1 | 1.069 | 4.3 | 2.8 | 101.5 | 1.2 | 2.1 | 130.9 | -1.3 | 7.2 | 1.215 |
Q2 2023 | -0.2 | 4.8 | 1.067 | 4.6 | 2.6 | 101.6 | 0.1 | 1.7 | 130.1 | -2.1 | 6.0 | 1.222 |
Q3 2023 | 0.3 | 3.8 | 1.066 | 4.8 | 2.6 | 101.7 | -0.2 | 1.4 | 129.3 | -2.0 | 4.7 | 1.230 |
Q4 2023 | 0.8 | 2.9 | 1.065 | 4.9 | 2.6 | 101.8 | 0.3 | 1.2 | 128.4 | -0.9 | 3.6 | 1.237 |
Q1 2024 | 1.6 | 2.3 | 1.065 | 4.9 | 2.7 | 101.8 | 1.4 | 1.2 | 128.4 | 1.1 | 2.5 | 1.237 |
Q2 2024 | 2.0 | 1.9 | 1.065 | 4.9 | 2.7 | 101.8 | 2.1 | 1.2 | 128.4 | 2.3 | 1.7 | 1.237 |
Q3 2024 | 2.1 | 1.7 | 1.065 | 4.8 | 2.7 | 101.8 | 2.1 | 1.2 | 128.4 | 2.7 | 1.1 | 1.237 |
Q4 2024 | 1.9 | 1.8 | 1.065 | 4.8 | 2.6 | 101.8 | 1.6 | 1.3 | 128.4 | 2.6 | 0.8 | 1.237 |
Q1 2025 | 1.6 | 2.0 | 1.065 | 4.8 | 2.5 | 101.8 | 0.5 | 1.3 | 128.4 | 2.2 | 0.6 | 1.237 |
Q2 2025 | 1.4 | 2.1 | 1.065 | 4.8 | 2.3 | 101.8 | -0.1 | 1.4 | 128.4 | 2.0 | 0.6 | 1.237 |
Q3 2025 | 1.4 | 2.2 | 1.065 | 4.8 | 2.3 | 101.8 | -0.3 | 1.4 | 128.4 | 1.9 | 0.6 | 1.237 |
Q4 2025 | 1.4 | 2.1 | 1.065 | 4.7 | 2.3 | 101.8 | -0.1 | 1.4 | 128.4 | 2.0 | 0.7 | 1.237 |
Q1 2026 | 1.4 | 1.9 | 1.065 | 4.7 | 2.4 | 101.8 | 0.2 | 1.4 | 128.4 | 2.1 | 0.9 | 1.237 |
Note: Refer to Notes Regarding Scenario Variables for more information on the definitions and sources of historical observations of the variables in the table.
1. F/USD denotes foreign currency index, relative to the U.S. dollar, obtained as a weighted average of the exchange rates of the countries in the developing Asia bloc. Return to table
Table 4.A. Supervisory severely adverse scenario: Domestic variables, Q1:2023–Q1:2026
Percent, unless otherwise indicated
Date | Real GDP growth |
Nominal GDP growth |
Real dispos- able income growth |
Nominal dispos- able income growth |
Unem- ployment rate |
CPI inflation rate |
3-month Treasury rate |
5-year Treasury yield |
10-year Treasury yield |
BBB corpo- rate yield |
Mort- gage rate |
Prime rate |
Level | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Dow Jones Total Stock Market Index | House Price Index |
Com- mercial Real Estate Price Index |
Market Volatility Index |
|||||||||||||
Q1 2023 | -12.5 | -10.1 | -7.9 | -5.8 | 5.6 | 2.3 | 1.7 | 1.2 | 1.1 | 5.8 | 4.0 | 4.7 | 24,338 | 249 | 348 | 70.0 |
Q2 2023 | -6.7 | -5.3 | -3.0 | -1.8 | 6.8 | 1.5 | 1.0 | 0.9 | 0.8 | 6.3 | 3.7 | 4.0 | 22,132 | 229 | 337 | 75.0 |
Q3 2023 | -8.0 | -7.0 | -3.4 | -2.4 | 8.1 | 1.3 | 0.1 | 0.8 | 0.8 | 6.5 | 3.8 | 3.1 | 21,502 | 213 | 323 | 65.4 |
Q4 2023 | -5.9 | -4.9 | -2.1 | -0.9 | 9.2 | 1.3 | 0.1 | 0.8 | 0.8 | 6.6 | 3.8 | 3.1 | 21,186 | 202 | 301 | 58.0 |
Q1 2024 | -1.8 | -0.7 | 0.3 | 1.6 | 9.7 | 1.4 | 0.1 | 0.9 | 0.9 | 6.4 | 3.8 | 3.1 | 21,817 | 194 | 277 | 52.1 |
Q2 2024 | 0.6 | 1.9 | 1.5 | 2.8 | 9.9 | 1.4 | 0.1 | 0.9 | 1.0 | 6.1 | 3.7 | 3.1 | 22,762 | 190 | 255 | 47.4 |
Q3 2024 | 0.9 | 2.2 | 1.7 | 2.9 | 10.0 | 1.4 | 0.1 | 1.0 | 1.1 | 5.8 | 3.5 | 3.1 | 24,023 | 186 | 234 | 43.6 |
Q4 2024 | 6.3 | 7.6 | 5.3 | 6.6 | 9.5 | 1.5 | 0.1 | 1.0 | 1.2 | 5.5 | 3.4 | 3.1 | 25,599 | 191 | 215 | 40.6 |
Q1 2025 | 5.9 | 7.2 | 5.3 | 6.7 | 9.0 | 1.5 | 0.1 | 1.0 | 1.3 | 5.1 | 3.3 | 3.1 | 27,490 | 196 | 218 | 38.2 |
Q2 2025 | 5.6 | 6.4 | 5.1 | 6.5 | 8.6 | 1.5 | 0.1 | 1.0 | 1.3 | 4.8 | 3.2 | 3.1 | 29,381 | 202 | 220 | 36.2 |
Q3 2025 | 5.3 | 6.3 | 4.8 | 6.3 | 8.2 | 1.6 | 0.1 | 1.0 | 1.4 | 4.5 | 3.1 | 3.1 | 32,217 | 207 | 223 | 34.7 |
Q4 2025 | 5.0 | 6.1 | 4.5 | 6.0 | 7.8 | 1.6 | 0.1 | 1.0 | 1.5 | 4.1 | 3.1 | 3.1 | 35,369 | 212 | 226 | 33.4 |
Q1 2026 | 4.7 | 6.0 | 4.2 | 5.7 | 7.5 | 1.6 | 0.1 | 1.1 | 1.5 | 3.8 | 3.1 | 3.1 | 38,521 | 216 | 228 | 32.4 |
Note: Refer to Notes Regarding Scenario Variables for more information on the definitions and sources of historical observations of the variables in the table.
Table 4.B. Supervisory severely adverse scenario: International variables, Q1:2023–Q1:2026
Percent, unless otherwise indicated
Date | Euro area realGDP growth |
Euro area inflation | Euro area bilateral dollar exchange rate (USD/euro) |
Developing Asia real GDP growth |
Developing Asia inflation |
Developing Asia bilateral dollar exchange rate (F/USD, index)1 |
Japan real GDP growth |
Japan inflation |
Japan bilateral dollar exchange rate (yen/USD) |
U.K. real GDP growth |
U.K. inflation |
U.K. bilateral dollar exchange rate (USD/pound) |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Q1 2023 | -5.8 | 5.3 | 1.061 | -1.7 | 0.8 | 102.2 | -8.9 | 0.6 | 128.7 | -4.2 | 6.8 | 1.198 |
Q2 2023 | -5.2 | 3.4 | 1.053 | -0.4 | -0.7 | 103.1 | -6.5 | -0.3 | 127.9 | -4.6 | 5.2 | 1.188 |
Q3 2023 | -4.3 | 2.4 | 1.032 | 1.9 | -0.6 | 105.2 | -4.7 | -0.8 | 127.6 | -3.8 | 4.0 | 1.165 |
Q4 2023 | -4.1 | 1.2 | 1.015 | 2.5 | -1.2 | 106.9 | -4.2 | -1.2 | 127.1 | -3.6 | 2.7 | 1.146 |
Q1 2024 | -3.9 | 0.3 | 1.011 | 4.4 | -1.0 | 107.3 | -3.8 | -1.5 | 126.5 | -3.4 | 1.3 | 1.141 |
Q2 2024 | -3.7 | -0.3 | 1.007 | 5.4 | -1.0 | 107.7 | -3.3 | -1.7 | 126.3 | -3.2 | 0.2 | 1.137 |
Q3 2024 | 1.0 | -0.5 | 1.009 | 3.8 | -1.1 | 107.5 | 1.0 | -1.4 | 126.5 | 1.0 | -0.4 | 1.139 |
Q4 2024 | 4.2 | 0.2 | 1.011 | 6.7 | 0.2 | 107.3 | 4.5 | -0.6 | 126.6 | 3.5 | -0.3 | 1.141 |
Q1 2025 | 5.3 | 0.7 | 1.019 | 7.1 | 0.6 | 106.4 | 5.5 | 0.1 | 127.1 | 4.4 | -0.2 | 1.151 |
Q2 2025 | 6.3 | 1.2 | 1.036 | 7.6 | 1.4 | 104.7 | 6.5 | 0.9 | 127.3 | 5.3 | 0.1 | 1.169 |
Q3 2025 | 7.4 | 1.9 | 1.044 | 8.0 | 2.5 | 103.9 | 7.0 | 1.6 | 127.6 | 6.2 | 0.6 | 1.179 |
Q4 2025 | 8.4 | 2.5 | 1.053 | 8.5 | 3.6 | 103.1 | 7.5 | 2.2 | 127.7 | 7.0 | 1.2 | 1.188 |
Q1 2026 | 9.5 | 3.0 | 1.061 | 8.4 | 4.5 | 102.2 | 8.5 | 2.7 | 128.0 | 7.9 | 1.8 | 1.198 |
Note: Refer to Notes Regarding Scenario Variables for more information on the definitions and sources of historical observations of the variables in the table.
1. F/USD denotes foreign currency index, relative to the U.S. dollar, obtained as a weighted average of the exchange rates of the countries in the developing Asia bloc. Return to table
Notes Regarding Scenario Variables
The following are descriptions of data through 2022:Q4 (as released through January 12, 2023). The 2022:Q4 values of variables marked with an asterisk (*) are estimates.
*U.S. real GDP growth: Quarterly percent change in real gross domestic product (chained 2012 dollars), expressed at an annualized rate, Bureau of Economic Analysis (NIPA table 1.1.6, line 1).
*U.S. nominal GDP growth: Quarterly percent change in gross domestic product (current dollars), expressed at an annualized rate, Bureau of Economic Analysis (NIPA table 1.1.5, line 1).
*U.S. real disposable income growth: Quarterly percent change in real disposable personal income (current-dollar values divided by the price index for personal consumption expenditures), expressed at an annualized rate, Bureau of Economic Analysis (NIPA table 2.1, line 27, and NIPA table 1.1.4, line 2).
*U.S. nominal disposable income growth: Quarterly percent change in disposable personal income (current dollars), expressed at an annualized rate, Bureau of Economic Analysis (NIPA table 2.1, line 27).
U.S. unemployment rate: Quarterly average of seasonally adjusted monthly unemployment rates for the civilian, non-institutional population aged 16 years and older, Bureau of Labor Statistics (series LNS14000000).
U.S. CPI inflation: Percent change in the quarterly average of seasonally adjusted monthly levels of the all-items CPI for all urban consumers (CPI-U), expressed at an annualized rate, Bureau of Labor Statistics (series CUSR0000SA0).
U.S. 3-month Treasury rate: Quarterly average of 3-month Treasury bill secondary market rate on a discount basis, H.15 Release, Selected Interest Rates, Federal Reserve Board (series RIFSGFSM03_N.B).
U.S. 5-year Treasury yield: Quarterly average of the yield on 5-year U.S. Treasury notes, constructed for the FRB/US model by Federal Reserve staff based on the Svensson smoothed term structure model (see Lars E. O. Svensson, 1995, "Estimating Forward Interest Rates with the Extended Nelson–Siegel Method," Quarterly Review, no. 3, Sveriges Riksbank, pp. 13–26).
U.S. 10-year Treasury yield: Quarterly average of the yield on 10-year U.S. Treasury notes, constructed for the FRB/US model by Federal Reserve staff based on the Svensson smoothed term structure model; (see Svensson, "Estimating Forward Interest Rates").
U.S. BBB corporate yield: Quarterly average of ICE BofAML U.S. Corporate 7-10 Year Yield-to-Maturity Index, ICE Data Indices, LLC, used with permission. (C4A4 series.)
U.S. mortgage rate: Quarterly average of weekly series for the interest rate of a conventional, conforming, 30-year fixed-rate mortgage, obtained from the Primary Mortgage Market Survey of the Federal Home Loan Mortgage Corporation.
U.S. prime rate: Quarterly average of monthly series, H.15 Release (Selected Interest Rates), Federal Reserve Board (series RIFSPBLP_N.M).
U.S. Dow Jones Total Stock Market (Float Cap) Index: End-of-quarter value via Bloomberg Finance LP
*U.S. House Price Index: Price Index for Owner-Occupied Real Estate, Z.1 Release (Financial Accounts of the United States), Federal Reserve Board (series FL075035243.Q divided by 1000).
*U.S. Commercial Real Estate Price Index: Commercial Real Estate Price Index, Z.1 Release (Financial Accounts of the United States), Federal Reserve Board (series FL075035503.Q divided by 1000).
U.S. Market Volatility Index (VIX): VIX converted to quarterly frequency using the maximum close-of-day value in any quarter, Chicago Board Options Exchange via Bloomberg Finance LP.
*Euro area real GDP growth: Quarterly percent change in real gross domestic product at an annualized rate, staff calculations based on Statistical Office of the European Communities via Haver, extended back using ECB Area Wide Model dataset (ECB Working Paper series no. 42).
Euro area inflation: Percent change in the quarterly average of the harmonized index of consumer prices at an annualized rate, staff calculations based on Statistical Office of the European Communities via Haver.
*Developing Asia real GDP growth: Quarterly percent change in real gross domestic product at an annualized rate, staff calculations based on data from Bank of Korea via Haver; National Bureau of Statistics of China via Haver; Indian Central Statistics Office via Haver; Census and Statistics Department of Hong Kong via Haver; and Taiwan Directorate-General of Budget, Accounting and Statistics via Haver.
*Developing Asia inflation: Percent change in the quarterly average of the consumer price index, or local equivalent, at an annualized rate, staff calculations based on data from National Bureau of Statistics of China via Haver; Indian Ministry of Statistics and Programme Implementation via Haver; Labour Bureau of India via Haver; Statistics Korea (KOSTAT) via Haver; Census and Statistics Department of Hong Kong via Haver; and Taiwan Directorate-General of Budget, Accounting and Statistics via Haver.
*Japan real GDP growth: Quarterly percent change in gross domestic product at an annualized rate from 1980 to present and percent change in gross domestic expenditure at an annualized rate prior to 1980, Cabinet Office of Japan via Haver.
*Japan inflation: Percent change in the quarterly average of the consumer price index at an annualized rate, based on data from the Ministry of Internal Affairs and Communications via Haver.
*U.K. real GDP growth: Quarterly percent change in gross domestic product at an annualized rate, U.K. Office for National Statistics via Haver.
*U.K. inflation: Percent change in the quarterly average of the consumer price index at an annualized rate from 1988 to present and percent change in the quarterly average of the retail prices index prior to 1988, staff calculations based on data from the U.K. Office for National Statistics via Haver.
Exchange rates: End-of-quarter exchange rates, H.10 Release (Foreign Exchange Rates), Federal Reserve Board.
Footnotes
1. See 12 C.F.R. pt. 238, subpart O; 12 C.F.R. pt. 252, subpart E.
U.S. intermediate holding companies with $100 billion or more in total consolidated assets are also subject to the stress test. Return to text
2. U.S. bank holding companies (BHCs), savings and loan holding companies (SLHCs), and intermediate holding companies of foreign banking organizations (IHCs) with $100 billion or more in assets are subject to the Board's supervisory stress test rule (12 C.F.R. pt. 238, subpart O; 12 C.F.R. pt. 252, subpart E) and capital planning requirements (12 C.F.R. § 225.8; 12 C.F.R. § 238.170). In addition, certain BHCs, SLHCs, U.S. IHCs, and state member banks must comply with the Board's company-run stress test rules (12 C.F.R. pt. 238, subpart P; and 12 C.F.R. pt. 252, subparts B and F). Return to text
3. The U.S. G-SIBs are Bank of America Corporation, The Bank of New York Mellon Corporation, Citigroup Inc., The Goldman Sachs Group, Inc., JPMorgan Chase & Co., Morgan Stanley, State Street Corporation, and Wells Fargo & Company. Return to text
4. For more information about the Federal Reserve's framework for designing stress test scenarios, see "Policy Statement on the Scenario Design Framework for Stress Testing" (12 C.F.R. pt. 252, appendix A). Return to text
5. The scenarios can also be downloaded (together with the historical time series of the variables) from the Board's website, at https://www.federalreserve.gov/supervisionreg/dfa-stress-tests.htm. Return to text
6. See Wolters Kluwer Legal and Regulatory Solutions, Blue Chip Economic Indicators and Blue Chip Financial Forecasts. Return to text
7. See International Monetary Fund, World Economic Outlook (October 2022), https://www.imf.org/en/Publications/WEO/Issues/2022/10/11/world-economic-outlook-october-2022. The January 2023 update to the World Economic Outlook was released after the finalization of the scenarios. Return to text
8. 12 C.F.R. pt. 252, appendix A. Return to text
9. The global market shock component for the severely adverse scenario applies to a firm that is subject to the stress test and that has aggregate trading assets and liabilities of $50 billion or more, or aggregate trading assets and liabilities equal to 10 percent or more of total consolidated assets, and that is not a Category IV firm under the Board's tailoring framework. See 12 C.F.R. § 252.54(b)(2)(i). Return to text
10. A firm may use data as of the date that corresponds to its weekly internal risk reporting cycle as long as it falls during the business week of the as-of date for the global market shock (i.e., October 10–14, 2022). Return to text
11. For example, credit spread changes in the municipal credit markets during March and April of 2020 would have been considered unprecedented had they been used in earlier global market shock scenarios. Return to text
12. The liquidity of previously well-functioning financial markets can undergo abrupt changes in times of financial stress. For example, prior to the Global Financial Crisis, AAA-rated private-label RMBS would likely have been considered highly liquid, but their liquidity deteriorated drastically during the crisis period. Return to text
13. The Board may require a company to include one or more additional components in its severely adverse scenario in the annual stress test based on the company's financial condition, size, complexity, risk profile, scope of operations, or activities, or based on risks to the U.S. economy. See 12 C.F.R. § 252.54(b)(2)(ii). Return to text
14. In selecting its largest counterparty, a firm subject to the counterparty default component will not consider certain sovereign entities (Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States) or qualifying central counterparties (QCCPs). See definition of a QCCP at 12 C.F.R. § 217.2.
U.S. IHCs are not required to include any affiliate as a counterparty. As in the U.S. final rule pursuant to the Dodd-Frank Act for Single Counterparty Credit Limits, an affiliate of the company includes a parent of the company, as well as any other firm that is consolidated with the company under applicable accounting standards, including U.S. generally accepted accounting principles or International Financial Reporting Standards. Return to text
15. As with the global market shock, a firm subject to the counterparty default component may use data as of the date that corresponds to its weekly internal risk reporting cycle as long as it falls during the business week of the as-of date for the counterparty default scenario component (i.e., October 10–14, 2022). Return to text