Stress Scenario

From Open Risk Manual


Stress Scenario, in the context of Market Risk or Credit Risk management, is a collection of assumptions about potential future economic conditions that are not the expected outcome over an assessment horizon but do have a meaningful (material) probability to incur and would tend to induce high market or credit losses if they did occur[1]

Stress Scenarios are a key element of Stress Testing

Narrative Scenarios

This type of stress scenario is typically expressed as a narrative, a verbal description of a (shorter or longer) sequence of events.

  • This narrative is not, in general, a complete description of future states of the world
  • The probability of a stress scenario is in general not specified and it may be exceedingly difficult to quantify objectively
  • The impact of a stress scenario is also in general not specified. It will in general be highly depended on the entity under consideration

Simulated Scenarios

In various quantitative risk management contexts stress scenarios are generated programmatically using an Economic Scenario Generator. Such scenarios

  • Form a complete description of future states of the world (in a probabilistic sense - they may be exceeding simplified versions)
  • Are typically estimated using quantitative (historical) data and may ignore any substantial regime shifts


A scenario narrative will typically involve:

  • Potentially one or more Actors (agents deciding independently). For some scenarios the "actors" may be the aggregate behaviors of individuals in an economy
  • Always at least one directional change in a key metric or observable that is either subject to policy decision or is an aggregate of financial / economic conditions
  • Always at least one or more Jurisdictions (economic regions under similar legal, political conditions)
  • Always at least one or more Financial Markets (those will typically express / bear the ultimate impact of the scenario)
  • Potentially connections, correlations, contagion, knock-on effects between Actors, Jurisdictions and Financial Markets

Example: 2019 Risk Scenarios

This list is a worked out example motivated by a recent publication[2]

Actor(s) Metric / Observable Jurisdiction(s) Financial Market(s) Connections
Algorithmic Traders Market Gap (Discontinuous Jump) Global Equities, Credit
Chinese, Europe Population GDP Slowdown / Reduction China, Europe Impact on US Economy
Chinese, Europe Population GDP Slowdown / Reduction China, Europe US Dollar Appreciation
Fixed Income Investors US Debt Volumes / Bid-Ask spreads US US Interest Rates
US Treasury Increase in US T-Bill Volumes US Libor-OIS spread
US Treasury Increase in US Bond Volumes US Demand for Investment Grade Credit
European, Japanese Investors FX Hedging Costs US US Credit
ECB Ending Quantitative Easing Eurozone Global Fixed Income
BoJ Slowing Quantitative Easing Japan Global Fixed Income
Fixed Income Investors 2yr-10yr Yield Curve Spread US Credit, Equity Markets
US Corp Management Use of Corporate Tax Cuts US Equities
US Governement Governement Shutdown US Global Markets
UK Governement No-deal Brexit UK Global Markets
US, China Tariffs US, China
US, EU Tariffs US, EU
Fed Interest Rate Increase US Profit Margins from Wages Growth
Fed Interest Rate Increase US Inflation Expectations Unanchored
French Population Public Unrest France
European Population European Parlament Elections EU
DE Real Estate Investors House Price Increases Germany Real Estate
Italian Government Fiscal Policy Italy
Australian, Canadian Real Estate Investors House Price Increases Australia, Canada Real Estate
Chinese Population Response to economic stimulus China
Chinese Government Current Account Deficit Surprise China
Chinese Population Chinese GDP China Japanese GDP
Emerging Market Populations Political Change India, Argentina, South Africa, Indonesia
Global Economies Inequality Index Global
Fed, ECB QE Re-enactement US, EU Broken correlation with GDP
Global Goverments and CB's Monetary and Fiscal Easing Global Broken correlation with GDP


  1. BCBS, Studies on the Validation of Internal Rating Systems, 2005
  2. 30 Risks to Markets in 2019, Deutsche Bank Research (Torsten Slock)

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