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\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auto;padding:0 16px;font-family:ui-sans-serif,system-ui,-apple-system,\"Segoe UI\",sans-serif;line-height:1.55;overflow-wrap:break-word}#nxe-n2j2vddr.nxe :where(*,*::before,*::after){box-sizing:inherit}#nxe-n2j2vddr.nxe :where(section,header,footer,nav,aside){display:block;margin:0 0 32px}#nxe-n2j2vddr.nxe :where(h1,h2,h3,h4){line-height:1.2;margin:24px 0 12px;font-weight:600}#nxe-n2j2vddr.nxe :where(p,ul,ol,dl,table,figure,details){margin:0 0 16px}#nxe-n2j2vddr.nxe :where(ul,ol){padding-left:20px}#nxe-n2j2vddr.nxe a{color:inherit;text-decoration:underline;text-underline-offset:2px}#nxe-n2j2vddr.nxe table{border-collapse:collapse;width:100%;display:block;overflow-x:auto}#nxe-n2j2vddr.nxe :where(th,td){padding:6px 8px;text-align:left;vertical-align:top;border-bottom:1px solid;border-color:inherit}#nxe-n2j2vddr.nxe svg{display:none}#nxe-n2j2vddr.nxe svg.nx-i{display:inline-block;width:18px;height:18px;vertical-align:-3px}#nxe-n2j2vddr.nxe :where([role=\"tablist\"],[role=\"toolbar\"],[hidden],button,.nx-theme-toggle,.nx-live-slot){display:none}#nxe-n2j2vddr.nxe img{max-width:100%;height:auto}<\/style><svg class=\"nx-defs\" aria-hidden=\"true\" focusable=\"false\" width=\"0\" height=\"0\"><defs><linearGradient id=\"nx-gi\" x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\"><stop offset=\"0\" class=\"nx-gi-a\"\/><stop offset=\"0.55\" class=\"nx-gi-b\"\/><stop offset=\"1\" class=\"nx-gi-c\"\/><\/linearGradient><linearGradient id=\"nx-giu\" gradientUnits=\"userSpaceOnUse\" x1=\"0\" y1=\"0\" x2=\"800\" y2=\"0\"><stop offset=\"0\" class=\"nx-gi-a\"\/><stop offset=\"0.55\" class=\"nx-gi-b\"\/><stop offset=\"1\" class=\"nx-gi-c\"\/><\/linearGradient><linearGradient id=\"nx-gp\" x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\"><stop offset=\"0\" class=\"nx-gp-a\"\/><stop offset=\"1\" class=\"nx-gp-b\"\/><\/linearGradient><\/defs><\/svg><section class=\"nx-hero\" data-layout=\"console\" aria-labelledby=\"nx-title-1\"><div class=\"nx-container\"><div class=\"nx-theme-toggle\" role=\"group\" aria-label=\"Appearance of this page\" hidden><button type=\"button\" data-mode=\"light\" aria-pressed=\"false\">Light<\/button><button type=\"button\" data-mode=\"dark\" aria-pressed=\"false\">Dark<\/button><button type=\"button\" data-mode=\"auto\" aria-pressed=\"true\">Auto<\/button><\/div><div class=\"nx-folio\" aria-label=\"Document reference\"><strong>A-P01 \u00b7 TOPIC \u00b7 stress-testing-methods<\/strong>GRA dossier \u00b7 service level R0<\/div><div class=\"nx-hero-grid\"><div class=\"nx-hero-text\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">GRA<\/span><span class=\"nx-eyebrow\" aria-hidden=\"true\">\u00b7<\/span><span class=\"nx-eyebrow\">Financial Stability<\/span><span class=\"nx-eyebrow\" aria-hidden=\"true\">\u00b7<\/span><span class=\"nx-eyebrow\">In development<\/span><\/div><div class=\"nx-accent-row\"><span class=\"nx-accent-rule\" aria-hidden=\"true\"><\/span><span>Topic dossier \u00b7 Financial Stability<\/span><\/div><h1 id=\"nx-title-1\" class=\"nx-hero-title\">Stress testing methods<\/h1><p class=\"nx-tagline\">Stress tests ask how institutions and the system would fare under severe but plausible scenarios. Supervisors use them to set capital, central banks to study system dynamics, and boards to test their plans. Methods range from bank-run models to system-wide exercises that include nonbanks. This page sets out how stress tests are built and where they mislead, the records they produce, and who decides how they are used.<\/p><div class=\"nx-actions\"><a class=\"nx-btn\" data-variant=\"primary\" href=\"https:\/\/globalriskalliance.com\/financial-stability\/contact\/\">Make an enquiry <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a class=\"nx-btn\" data-variant=\"secondary\" href=\"https:\/\/globalriskalliance.com\/financial-stability\/topics\/\">Back to Topics<\/a><\/div><\/div><div class=\"nx-hero-panel\"><div class=\"nx-register\"><div class=\"nx-register-head\"><span class=\"nx-eyebrow\"><strong>Dossier<\/strong><\/span><span class=\"nx-eyebrow\">A-P01 \u00b7 topic<\/span><\/div><ol class=\"nx-register-rows\"><li><a href=\"#nx-sec-brief-answer\"><span class=\"nx-register-n\">01<\/span><span class=\"nx-register-k\">In brief<\/span><span class=\"nx-register-v\">Definition and scope<\/span><\/a><\/li><li><a href=\"#nx-sec-question\"><span class=\"nx-register-n\">02<\/span><span class=\"nx-register-k\">The question<\/span><span class=\"nx-register-v\">4 mechanisms<\/span><\/a><\/li><li><a href=\"#nx-sec-terms\"><span class=\"nx-register-n\">03<\/span><span class=\"nx-register-k\">Key terms<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">3<\/span><\/span><\/a><\/li><li><a href=\"#nx-sec-field\"><span class=\"nx-register-n\">04<\/span><span class=\"nx-register-k\">Field<\/span><span class=\"nx-register-v\">H3 field plate<\/span><\/a><\/li><li><a href=\"#nx-sec-indicators\"><span class=\"nx-register-n\">05<\/span><span class=\"nx-register-k\">Indicators<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">6<\/span><\/span><\/a><\/li><li><a href=\"#nx-sec-pipeline\"><span class=\"nx-register-n\">06<\/span><span class=\"nx-register-k\">Pipeline<\/span><span class=\"nx-register-v\">Run graph<\/span><\/a><\/li><li><a href=\"#nx-sec-sources\"><span class=\"nx-register-n\">07<\/span><span class=\"nx-register-k\">Sources<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">5<\/span><\/span><\/a><\/li><li><a href=\"#nx-sec-decisions\"><span class=\"nx-register-n\">08<\/span><span class=\"nx-register-k\">Decision holders<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">4<\/span><\/span><\/a><\/li><li><a href=\"#nx-sec-methods\"><span class=\"nx-register-n\">09<\/span><span class=\"nx-register-k\">Methods<\/span><span class=\"nx-register-v\"><span class=\"nx-register-num\">4<\/span><\/span><\/a><\/li><\/ol><p class=\"nx-register-foot\">GRA \u00b7 In development \u00b7 service level R0<\/p><\/div><\/div><\/div><\/div><\/section> <nav class=\"nx-index-strip\" data-nx-spy=\"true\" aria-label=\"On this page\"><div class=\"nx-container\"><a href=\"#nx-sec-brief-answer\"><span>01<\/span>The short answer<\/a><a href=\"#nx-sec-field\"><span>02<\/span>A loan book under scenario families<\/a><a href=\"#nx-sec-question\"><span>03<\/span>Stress testing methods: how the risk\u2026<\/a><a href=\"#nx-sec-terms\"><span>04<\/span>Terms used on this page<\/a><a href=\"#nx-sec-indicators\"><span>05<\/span>What is measured, and how well<\/a><a href=\"#nx-sec-pipeline\"><span>06<\/span>From sources to decisions<\/a><a href=\"#nx-sec-sources\"><span>07<\/span>Where the evidence comes from<\/a><a href=\"#nx-sec-decisions\"><span>08<\/span>Who decides, and what the evidence\u2026<\/a><\/div><\/nav> <section id=\"nx-sec-brief-answer\" class=\"nx-section\" data-hue=\"finance\" aria-labelledby=\"nx-s-2\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">01<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">In brief<\/span><\/div><h2 id=\"nx-s-2\" class=\"nx-section-title\">The short answer.<\/h2><p class=\"nx-lede\">Stress testing methods are the ways supervisors, central banks and firms estimate how institutions would fare under severe but plausible scenarios. They range from bank-level tests with static balance sheets to system-wide exercises with second-round effects. Results are conditional, not forecasts. Supervisors and boards decide how they are used.<\/p><\/div><\/div><\/section><section id=\"nx-sec-field\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" aria-labelledby=\"nx-s-3\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">02<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Spatial finance<\/span><\/div><h2 id=\"nx-s-3\" class=\"nx-section-title\">A loan book under scenario families.<\/h2><p class=\"nx-lede\">How physical and transition risk could reach a loan book under different scenarios. Illustrative design values.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-canvas-wrap\"><figure class=\"nx-fk nx-sf\" data-fk=\"climate-stress\" data-gl=\"sf:climate-stress\" data-sf=\"climate-stress\" data-sx-credit=\"Natural Earth (public domain) | relief: Mapzen Terrain Tiles | design values; NGFS names as labels only\" data-sx-src=\"Natural Earth ~ public domain ~ https:\/\/www.naturalearthdata.com\/ | Mapzen Terrain Tiles relief (SRTM, GMTED2010, ETOPO1) ~ attribution as published by Mapzen ~ https:\/\/github.com\/tilezen\/joerd\/blob\/master\/docs\/attribution.md | Design scenario values by the Global Risks Alliance ~ illustrative, not data\" data-sf-learn-views=\"waterfall\" aria-label=\"Interactive map: a design loan book over Europe, coloured by a design loss-sensitivity score. The panel chooses layers, a scenario family and a horizon.\" 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\"><figcaption class=\"nx-fk-cap\"><span>A loan book across Europe under physical and transition risk.<\/span><span data-honesty=\"true\">Design values; NGFS scenario names are labels only, not stress test results.<\/span><\/figcaption><\/figure><\/div><div class=\"nx-live-slot\" data-nxf-slot=\"map\" data-nxf-kind=\"map\" data-nxf-resource=\"nexus:\/\/gra\/A-P01\/topics\/stress-testing-methods\/#map\" data-nxf-title=\"Financial Stability live map\" data-nxf-height=\"560\" hidden><\/div><\/div><\/div><\/section><section id=\"nx-sec-question\" class=\"nx-section\" data-hue=\"finance\" data-variant=\"split\" aria-labelledby=\"nx-s-4\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">03<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">The question<\/span><\/div><h2 id=\"nx-s-4\" class=\"nx-section-title\">Stress testing methods: how the risk develops.<\/h2><p class=\"nx-lede\">Scenario, sensitivity and model limits. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-cells\" data-cols=\"2\"><div><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 3v18h18\"\/><path d=\"m19 9-5 5-4-4-3 3\"\/><\/svg><\/span><span class=\"nx-eyebrow\">Mechanism<\/span><\/div><h3 class=\"nx-h4 nx-mt-2\">Scenarios set the answer<\/h3><p class=\"nx-p nx-mt-1\">A stress test shows losses under the scenario chosen. Scenarios that are too mild, or that miss the next shock's shape, give false comfort.<\/p><\/div><div><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"m12.83 2.18a2 2 0 0 0-1.66 0L2.6 6.08a1 1 0 0 0 0 1.83l8.58 3.91a2 2 0 0 0 1.66 0l8.58-3.9a1 1 0 0 0 0-1.83Z\"\/><path d=\"m22 17.65-9.17 4.16a2 2 0 0 1-1.66 0L2 17.65\"\/><path d=\"m22 12.65-9.17 4.16a2 2 0 0 1-1.66 0L2 12.65\"\/><\/svg><\/span><span class=\"nx-eyebrow\">Mechanism<\/span><\/div><h3 class=\"nx-h4 nx-mt-2\">Static balance sheets miss reactions<\/h3><p class=\"nx-p nx-mt-1\">Many tests hold balance sheets fixed. Real firms deleverage, sell assets and cut lending, which can amplify stress across the system.<\/p><\/div><div><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><rect x=\"16\" y=\"16\" width=\"6\" height=\"6\" rx=\"1\"\/><rect x=\"2\" y=\"16\" width=\"6\" height=\"6\" rx=\"1\"\/><rect x=\"9\" y=\"2\" width=\"6\" height=\"6\" rx=\"1\"\/><path d=\"M5 16v-3a1 1 0 0 1 1-1h12a1 1 0 0 1 1 1v3\"\/><path d=\"M12 12V8\"\/><\/svg><\/span><span class=\"nx-eyebrow\">Mechanism<\/span><\/div><h3 class=\"nx-h4 nx-mt-2\">System-wide exercises add feedback<\/h3><p class=\"nx-p nx-mt-1\">Exercises that model banks, nonbanks and central counterparties together capture second-round effects that firm-level tests miss.<\/p><\/div><div><div class=\"nx-glyph-row\"><span class=\"nx-glyph\" data-tone=\"accent\"><svg class=\"nx-i\" viewBox=\"0 0 24 24\" aria-hidden=\"true\" focusable=\"false\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><circle cx=\"12\" cy=\"12\" r=\"10\"\/><circle cx=\"12\" cy=\"12\" r=\"6\"\/><circle cx=\"12\" cy=\"12\" r=\"2\"\/><\/svg><\/span><span class=\"nx-eyebrow\">Mechanism<\/span><\/div><h3 class=\"nx-h4 nx-mt-2\">Results drive capital and conduct<\/h3><p class=\"nx-p nx-mt-1\">When results set capital buffers, firms have incentives to optimise models to the test. Varying scenarios and transparency limit gaming.<\/p><\/div><\/div><\/div><\/div><\/section><section id=\"nx-sec-terms\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" aria-labelledby=\"nx-s-5\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">04<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Key terms<\/span><\/div><h2 id=\"nx-s-5\" class=\"nx-section-title\">Terms used on this page.<\/h2><p class=\"nx-lede\">Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Term<\/th><th scope=\"col\">Definition<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Term\">Adverse scenario<\/td><td data-label=\"Definition\">A hypothetical path of economic and financial variables designed to be severe but plausible.<\/td><\/tr><tr><td data-label=\"Term\">Second-round effects<\/td><td data-label=\"Definition\">Losses caused by institutions' reactions to an initial shock, such as asset sales, rather than the shock itself.<\/td><\/tr><tr><td data-label=\"Term\">Stress capital buffer<\/td><td data-label=\"Definition\">A capital requirement set from the results of a supervisory stress test.<\/td><\/tr><\/tbody><\/table><\/div><\/div><\/div><\/section><section id=\"nx-sec-indicators\" class=\"nx-section\" data-hue=\"finance\" aria-labelledby=\"nx-s-6\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">05<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Indicators<\/span><\/div><h2 id=\"nx-s-6\" class=\"nx-section-title\">What is measured, and how well.<\/h2><p class=\"nx-lede\">Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.<\/p><\/div><div class=\"nx-section-body\" data-lv=\"register\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Indicator<\/th><th scope=\"col\">Unit<\/th><th scope=\"col\">Cadence<\/th><th scope=\"col\">Source type<\/th><th scope=\"col\">Label<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Indicator\">Capital depletion under the adverse scenario<\/td><td data-label=\"Unit\">percentage points of CET1 ratio<\/td><td data-label=\"Cadence\">annual<\/td><td data-label=\"Source type\">Supervisory stress test results<\/td><td data-label=\"Label\"><span class=\"nx-chip\">MODELLED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Stress capital buffer<\/td><td data-label=\"Unit\">percent of risk-weighted assets<\/td><td data-label=\"Cadence\">annual<\/td><td data-label=\"Source type\">Supervisory determinations<\/td><td data-label=\"Label\"><span class=\"nx-chip\">OFFICIAL<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Liquidity survival horizon under stress<\/td><td data-label=\"Unit\">days<\/td><td data-label=\"Cadence\">periodic<\/td><td data-label=\"Source type\">Liquidity stress tests<\/td><td data-label=\"Label\"><span class=\"nx-chip\">MODELLED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Second-round losses in system-wide exercises<\/td><td data-label=\"Unit\">currency<\/td><td data-label=\"Cadence\">per exercise<\/td><td data-label=\"Source type\">System-wide exercise reports<\/td><td data-label=\"Label\"><span class=\"nx-chip\">MODELLED<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Scenario severity<\/td><td data-label=\"Unit\">peak-to-trough change in key variables<\/td><td data-label=\"Cadence\">per exercise<\/td><td data-label=\"Source type\">Scenario documents<\/td><td data-label=\"Label\"><span class=\"nx-chip\">OFFICIAL<\/span><\/td><\/tr><tr><td data-label=\"Indicator\">Climate scenario losses in exploratory exercises<\/td><td data-label=\"Unit\">currency or percent<\/td><td data-label=\"Cadence\">per exercise<\/td><td data-label=\"Source type\">Climate exercise reports<\/td><td data-label=\"Label\"><span class=\"nx-chip\">MODELLED<\/span><\/td><\/tr><\/tbody><\/table><\/div><div class=\"nx-live-slot\" data-nxf-slot=\"indicators\" data-nxf-kind=\"indicator\" data-nxf-resource=\"nexus:\/\/gra\/A-P01\/topics\/stress-testing-methods\/#indicators\" data-nxf-title=\"Indicators\" data-nxf-height=\"520\" hidden><\/div><\/div><\/div><\/section><section id=\"nx-sec-pipeline\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" aria-labelledby=\"nx-s-7\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">06<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Canvas<\/span><\/div><h2 id=\"nx-s-7\" class=\"nx-section-title\">From sources to decisions.<\/h2><p class=\"nx-lede\">The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-plate\" data-wide=\"true\"><div class=\"nx-plate-label\"><span class=\"nx-eyebrow\"><strong>Pipeline canvas<\/strong> \u00b7 Stress testing methods as a run graph<\/span><span class=\"nx-eyebrow\">Design, not a record<\/span><\/div><div class=\"nx-figure-frame\" data-scene=\"true\"><svg class=\"nx-figure nx-ui nx-dag\" viewBox=\"0 0 1200 564\" data-nx-dag=\"true\" data-w=\"1200\" data-h=\"564\" role=\"img\" aria-labelledby=\"nx-dag-a-p01-topics-stress-testing-methods-syste-t nx-dag-a-p01-topics-stress-testing-methods-syste-d\" data-nx-z=\"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\"><title id=\"nx-dag-a-p01-topics-stress-testing-methods-syste-t\">Stress testing methods: a cascade across interdependent systems<\/title><desc id=\"nx-dag-a-p01-topics-stress-testing-methods-syste-d\">A hazard hits one system; dependencies carry the failure into others; impact grows until buffers, redundancy or restoration priorities stop it; the analysis ranks the links to strengthen. Design of the process, not a record of a run.<\/desc><\/svg><\/div><\/div><p class=\"nx-caption\"><strong>Fig. 02<\/strong><span>Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.<\/span><\/p><\/div><\/div><\/section><section id=\"nx-sec-sources\" class=\"nx-section\" data-hue=\"finance\" aria-labelledby=\"nx-s-8\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">07<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Sources<\/span><\/div><h2 id=\"nx-s-8\" class=\"nx-section-title\">Where the evidence comes from.<\/h2><p class=\"nx-lede\">Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.<\/p><\/div><div class=\"nx-section-body\" data-lv=\"register\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Source<\/th><th scope=\"col\">What it gives<\/th><th scope=\"col\">Licence class<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Source\">Federal Reserve stress test scenarios and results<\/td><td data-label=\"What it gives\">Supervisory scenarios and bank results<\/td><td data-label=\"Licence class\">Public domain<\/td><\/tr><tr><td data-label=\"Source\">EBA EU-wide stress test results<\/td><td data-label=\"What it gives\">Scenarios and bank-level results<\/td><td data-label=\"Licence class\">Free, EU reuse terms<\/td><\/tr><tr><td data-label=\"Source\">Bank of England system-wide exploratory scenario report<\/td><td data-label=\"What it gives\">System-wide exercise covering banks and nonbanks<\/td><td data-label=\"Licence class\">Free, Bank of England terms<\/td><\/tr><tr><td data-label=\"Source\">NGFS climate scenarios<\/td><td data-label=\"What it gives\">Reference climate scenarios for exploratory exercises<\/td><td data-label=\"Licence class\">Free, NGFS terms<\/td><\/tr><tr><td data-label=\"Source\">IMF FSAP stress test technical notes<\/td><td data-label=\"What it gives\">Stress test methods and results by country<\/td><td data-label=\"Licence class\">Free, IMF terms<\/td><\/tr><\/tbody><\/table><\/div><div class=\"nx-live-slot\" data-nxf-slot=\"evidence\" data-nxf-kind=\"evidence\" data-nxf-resource=\"nexus:\/\/gra\/A-P01\/topics\/stress-testing-methods\/#evidence\" data-nxf-title=\"Sources\" data-nxf-height=\"520\" hidden><\/div><\/div><\/div><\/section><section id=\"nx-sec-decisions\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" aria-labelledby=\"nx-s-9\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">08<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Decisions<\/span><\/div><h2 id=\"nx-s-9\" class=\"nx-section-title\">Who decides, and what the evidence serves.<\/h2><p class=\"nx-lede\">Financial Stability prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Who decides<\/th><th scope=\"col\">The question<\/th><th scope=\"col\">Evidence this page serves<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Who decides\">Prudential supervisors<\/td><td data-label=\"The question\">How stress test results set capital buffers<\/td><td data-label=\"Evidence this page serves\">Scenario design, model review and results<\/td><\/tr><tr><td data-label=\"Who decides\">Central banks and macroprudential authorities<\/td><td data-label=\"The question\">Whether system-wide dynamics need policy response<\/td><td data-label=\"Evidence this page serves\">System-wide exercise findings<\/td><\/tr><tr><td data-label=\"Who decides\">Bank and insurer boards<\/td><td data-label=\"The question\">Whether capital and liquidity plans survive severe scenarios<\/td><td data-label=\"Evidence this page serves\">Internal and supervisory test results<\/td><\/tr><tr><td data-label=\"Who decides\">Scenario design teams<\/td><td data-label=\"The question\">Which risks and severity to include<\/td><td data-label=\"Evidence this page serves\">Historical episodes and emerging risk evidence<\/td><\/tr><\/tbody><\/table><\/div><h3 class=\"nx-h4 nx-mt-4\">Outputs this topic produces<\/h3><ul class=\"nx-list\"><li>Guide to stress test types and what each answers<\/li><li>Method note on scenario design and severity<\/li><li>Brief on second-round effects in system-wide exercises<\/li><li>Questions for boards on reverse stress testing<\/li><\/ul><\/div><\/div><\/section><section id=\"nx-sec-core-questions\" class=\"nx-section\" data-hue=\"finance\" data-variant=\"split\" aria-labelledby=\"nx-s-10\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">09<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Core questions<\/span><\/div><h2 id=\"nx-s-10\" class=\"nx-section-title\">Shared questions the industry asks.<\/h2><\/div><div class=\"nx-section-body\"><ol class=\"nx-rows\"><li><span class=\"nx-eyebrow nx-index\">01<\/span><div><h3 class=\"nx-h4\">What scenario is severe but plausible?<\/h3><p class=\"nx-p nx-mt-1\">How to design scenarios that challenge institutions without being arbitrary.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">02<\/span><div><h3 class=\"nx-h4\">What do tests capture?<\/h3><p class=\"nx-p nx-mt-1\">Which channels, such as credit losses, market moves and funding outflows, are modelled and which are left out.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">03<\/span><div><h3 class=\"nx-h4\">Do tests include feedback?<\/h3><p class=\"nx-p nx-mt-1\">Whether institutions' reactions and system-wide effects are represented.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">04<\/span><div><h3 class=\"nx-h4\">How should results be read?<\/h3><p class=\"nx-p nx-mt-1\">What a stress test shows and what it cannot show.<\/p><\/div><\/li><\/ol><\/div><\/div><\/section><section id=\"nx-sec-mechanisms\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" aria-labelledby=\"nx-s-11\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">10<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Mechanisms<\/span><\/div><h2 id=\"nx-s-11\" class=\"nx-section-title\">How the risk arises and transmits.<\/h2><\/div><div class=\"nx-section-body\"><p class=\"nx-p\">Sensitivity analysis changes one factor at a time; scenario analysis changes many together in a coherent narrative. Reverse stress testing starts from failure and asks what would cause it.<\/p><p class=\"nx-p\">Most traditional tests are static and firm-by-firm: they apply a shock and measure losses at each institution separately. They miss how institutions' responses, such as selling assets or cutting lending, affect each other and the economy.<\/p><p class=\"nx-p\">System-wide and macroprudential tests add feedback, contagion and nonbank sectors. They are more realistic in structure but rely on more uncertain behavioural assumptions.<\/p><p class=\"nx-p\">New risks challenge methods. Climate, cyber and pandemic scenarios involve long horizons, deep uncertainty and non-financial transmission paths that models were not built for.<\/p><p class=\"nx-p\">Model risk is inherent. Results depend on data, assumptions and model choices; communicating uncertainty is as important as the headline results.<\/p><\/div><\/div><\/section><section id=\"nx-sec-methods-and-limits\" class=\"nx-section\" data-hue=\"finance\" aria-labelledby=\"nx-s-12\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">11<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Methods and limits<\/span><\/div><h2 id=\"nx-s-12\" class=\"nx-section-title\">How evidence is gathered, and where it stops.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Method or data<\/th><th scope=\"col\">What it shows<\/th><th scope=\"col\">Its limit<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Method or data\">Sensitivity analysis<\/td><td data-label=\"What it shows\">Exposure to single factors<\/td><td data-label=\"Its limit\">Ignores interactions<\/td><\/tr><tr><td data-label=\"Method or data\">Macro scenarios<\/td><td data-label=\"What it shows\">Coherent multi-factor stress<\/td><td data-label=\"Its limit\">Scenario design is judgemental<\/td><\/tr><tr><td data-label=\"Method or data\">System-wide models<\/td><td data-label=\"What it shows\">Feedback and contagion<\/td><td data-label=\"Its limit\">Behavioural assumptions uncertain<\/td><\/tr><tr><td data-label=\"Method or data\">Reverse stress tests<\/td><td data-label=\"What it shows\">Paths to failure<\/td><td data-label=\"Its limit\">Can identify implausible paths<\/td><\/tr><\/tbody><\/table><\/div><\/div><\/div><\/section><section id=\"nx-sec-methods\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" aria-labelledby=\"nx-s-13\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">12<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Methods<\/span><\/div><h2 id=\"nx-s-13\" class=\"nx-section-title\">How it is studied, and what the methods cannot say.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-methods\" data-limits=\"true\"><ol class=\"nx-mledger\" aria-label=\"Methods\"><li><a class=\"nx-mledger-main\" href=\"https:\/\/globalriskalliance.com\/financial-stability\/stem\/scenario-stress\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">01<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Scenario design and stress testing<\/span><span class=\"nx-mledger-role\">Macro-financial scenario design \u00b7 System-wide exercises \u00b7 Reverse stress tests<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/mathematics\/scenario-stress\/\" aria-label=\"Scenario design and stress testing: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/globalriskalliance.com\/financial-stability\/stem\/econometrics\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">02<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Econometrics<\/span><span class=\"nx-mledger-role\">Early warning indicators \u00b7 Quantile regression for growth-at-risk \u00b7 Spillover estimation<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/mathematics\/econometrics\/\" aria-label=\"Econometrics: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/globalriskalliance.com\/financial-stability\/stem\/complex-systems\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">03<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Complex systems and agent-based modelling<\/span><span class=\"nx-mledger-role\">Agent-based market models \u00b7 Early warning of regime shifts \u00b7 Feedback loop mapping<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/mathematics\/complex-systems\/\" aria-label=\"Complex systems and agent-based modelling: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/globalriskalliance.com\/financial-stability\/stem\/network-science\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">04<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Network science and contagion<\/span><span class=\"nx-mledger-role\">Interbank contagion simulation \u00b7 Common exposure networks \u00b7 Multilayer networks<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/mathematics\/network-science\/\" aria-label=\"Network science and contagion: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><\/ol><aside class=\"nx-limits\" aria-label=\"What the methods cannot say\"><span class=\"nx-eyebrow\">What the methods cannot say<\/span><p class=\"nx-limits-text\">Stress tests depend on scenarios, models and behavioural assumptions, and they cannot cover every risk. Results are conditional, not forecasts. System-wide exercises rely on participant inputs. Climate scenarios carry deep uncertainty over long horizons. Financial Stability explains methods; it does not run stress tests, interpret any firm's results or give investment advice.<\/p><\/aside><\/div><\/div><\/div><\/section><section id=\"nx-s-14-sec\" class=\"nx-section\" data-hue=\"finance\" aria-labelledby=\"nx-s-14\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">13<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Questions<\/span><\/div><h2 id=\"nx-s-14\" class=\"nx-section-title\">Questions and answers.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-faq\"><details><summary>Is a stress test a forecast?<\/summary><div class=\"nx-answer\">No. It shows the effect of a hypothetical scenario. The scenario is chosen to be severe and plausible, not likely.<\/div><\/details><details><summary>What is reverse stress testing?<\/summary><div class=\"nx-answer\">Starting from an outcome that would make a firm's business model fail, and working back to the scenarios that could cause it.<\/div><\/details><details><summary>What is a system-wide stress exercise?<\/summary><div class=\"nx-answer\">An exercise that models how banks, nonbanks and market infrastructure respond together, capturing interactions that firm-level tests miss.<\/div><\/details><details><summary>Are GRA scenarios supervisory stress tests?<\/summary><div class=\"nx-answer\">No. They are research scenarios. They set no requirement and have no supervisory consequence.<\/div><\/details><details><summary>Can a stress test prove an institution is safe?<\/summary><div class=\"nx-answer\">No. It shows outcomes under specific assumptions. Unmodelled shocks and behaviour can produce different results.<\/div><\/details><details><summary>Where are scenarios published?<\/summary><div class=\"nx-answer\">On <a class=\"nx-link\" href=\"https:\/\/globalriskalliance.com\/financial-stability\/tools\/scenarios\/\">published scenarios<\/a>, once reviewed, with their assumptions and limits.<\/div><\/details><\/div><\/div><\/div><\/section><section class=\"nx-section\" data-tone=\"alt\" aria-labelledby=\"nx-rel-15\"><div class=\"nx-container\"><span class=\"nx-eyebrow\">Related<\/span><h2 id=\"nx-rel-15\" class=\"nx-h3 nx-mt-2\">Around Financial Stability.<\/h2><nav class=\"nx-related nx-mt-3\" aria-label=\"Related\"><a href=\"https:\/\/globalriskalliance.com\/financial-stability\/topics\/systemic-interconnectedness\/\">Systemic interconnectedness <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/globalriskalliance.com\/financial-stability\/topics\/nonbank-financial-intermediation\/\">Nonbank financial intermediation <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/globalriskalliance.com\/financial-stability\/topics\/liquidity-and-market-stress\/\">Liquidity and market stress <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/globalriskalliance.com\/financial-stability\/topics\/contagion-and-fire-sales\/\">Contagion and fire sales <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/globalriskalliance.com\/financial-stability\/topics\/cross-border-financial-risk\/\">Cross border financial risk <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/globalriskalliance.com\/financial-stability\/topics\/crisis-management-and-resolution\/\">Crisis management and resolution <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/globalriskalliance.com\/financial-stability\/\">Financial Stability home <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/globalriskalliance.com\/financial-stability\/counterparts\/\">Counterparts across the Consortium <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/globalriskalliance.com\/\">The Global Risks Alliance home <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/globalriskalliance.com\/trust\/\">GRA governance and trust <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/nav><\/div><\/section><section class=\"nx-closing\" aria-labelledby=\"nx-close-16\"><div class=\"nx-container\"><span class=\"nx-eyebrow\">Financial Stability<\/span><h2 id=\"nx-close-16\" class=\"nx-section-title\">Bring your expertise to this field.<\/h2><p class=\"nx-lede\">The current service level is R0: information and enquiries. 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