Group-wide Stress Testing: A Case Study. Enrico Piotto

Transcription

1 Group-wide Stress esting: A Case Study Enrico Piotto

2 Background Severe Losses Beyond scope of risk models Reluctance to statistical models Emphasis on stress testing as risk control and risk management tool Inflated Balance Sheets High leverage Geographical diversification Group view missing Interest in combined view of finance / risk / capital on divisional and group level Financial instability Fear of repeated impacts on financial stability Regulators under scrutiny Request for more insight, information and involvement Sharper regulations and demand regarding stress testing 1

3 Stress esting Landscape Portfolio specific stress tests Group-wide / Combined stress testing Reverse stress testing Portfolio specific worst case scenarios Portfolio specific assumptions Used for tracking against limits Directly business relevant Cannot be aggregated across portfolio (inconsistencies in terms of loss measure, methodology and scenario Common scenario reflecting current outlook Common assumptions across portfolios Group view RWA stress All risk categories Used for business, capital planning Consistent interpretation of results across portfolios Common scenario Extreme break the bank New breakdowns of portfolios New "risk parameters" More expert judgment, less statistical measures 2

4 Combined Stress esting -- Overview Captures the group-wide portfolio based on a forward-looking scenario Computed with one overarching model where all major risks are integrated to provide a fully scenario consistent stress loss. NO an inconsistent sum of "worse of worse" losses Captures the group-wide comprehensive impact of a scenario on the overall bank, from a P&L, RWA, ier1 capital perspective Input Overarching approach Output Stress scenario: Interest Rate up 200 bp Scenario consistent impact on: Probability of Default (the Probability of Default is linked to IR, FX, GDP, Exposure at Default (exposure is recomputed following a change in IR, FX, EQ, Loss Given Default (LGD is linked to IR, GDP, Market P&L (the MtM of each transaction is recomputed following a change in IR, FX EQ, Stressed level for PD, LGD, EAD and MtM: Bottom up calculation at transaction/counterparty level of credit losses and market P&L 3 3

5 UBS Approach for Group-wide Stress esting Macroeconomic Scenario Risk Factor Sensitivities Credit Risk Market Risk Country Risk Funding Risk PD time profile LGD time profile EAD time profile Market Risk Factors Country specific shocks Funding costs Default Rate Original PD Exposure oday's exposure LGD oday's LGD ( 0 3m ( 3m 6m ( 6m 9m ( 9m 1y ( 1y 1.5y ( 1.5 y 2y 10d 10d 3m 3m 6m 6m Stressed default rate (annualized 9m 1y 1.5y ( 0 3m ( 3m 6m ( 6m 9m ( 9m 1y ( 1y 1.5y ( 1.5 y 2y Exposure Profile raded Products Exposure Profile Mortgage 9m 1y 1.5y ( 0 3m ( 3m 6m ( 6m 9m ( 9m 1y ( 1y 1.5y ( 1.5y 2y LGD Profile 2y 2y time time Calculation and Aggregation ime profile of losses ime profile of capital adequacy Business Risk Interest income 10d 3m 6m 9m 1y 1.5y 2y time 4

6 Critical Input: Macroeconomic Scenarios Set of scenarios Discussion in hink ank (Research, Business, Risk Control E.g. Recession, Deflation/Depression, Stagflation, Forward-looking risk assessment Possibly different severity levels Update of scenarios (see next slides Reflection of current state of the economy and current outlook Changing environment vs. changing inputs Stress forecast for all major economic and financial variables in major economies 5

7 Scenario Landscape Update frequency Risk factor shocks Lifespan Purpose "Constant severity" version he initial version of the scenario is used. Corresponding risk factor shocks or risk factor levels (e.g. default rates are "frozen" at their initial values and applied in the same way every quarter. For example, default rates estimated based on macro variables in the initial scenario version are kept constant. Lagged impacts of the recent macroeconomic developments are not taken into account. For market risk factors (interest rates, spreads, equity returns, FX relative movements are kept constant. he initial version of the scenario is used until discontinued or replaced. Keeping all risk factors constant, a track record of scenario impacts over time can be established. his can be used for assessing the portfolio risk profile over time. "Current" / "Economic Logic" version he scenario is updated to reflect the latest macro-/financial developments and the current conditions. Risk factor shocks are re-calculated based on the updated scenario. For example, default rates are re-estimated using updated historical and scenario specific macroeconomic variables, therefore also accounting for lagged impacts of recent developments. he updated version is only used for one quarter. It will be replaced by the next update. Risk factors change and therefore are not directly comparable over time. his version is more suitable for forwardlooking risk and capital assessment. 6

8 ranslation into Risk Factors he methodology aims at assessing the impact on the various portfolios in a scenario consistent way. he same shocks specified in the scenario are applied to assess the losses in: Credit risk Market risk Issuer risk Country risk Private equity We have established methodologies for stressing all major risk drivers in a scenario consistent way based on given macroeconomic scenario specifications 7

9 Example: Approach for Credit Risk PDs (1 SEP 1 Sensitivities SEP 2 Application to Stress Scenario SEP 3 Bottom up stress loss calculation lnpd Statistical analysis of default indicators it = 0 + β1x1, it β K xk, it β + u + η + ε i t it Aggregate stress forecasts for default indicators for stress scenario Link to UBS portfolio: Link to UBS portfolio ranslation into default rate and PDs Break down to single names Define stressed PDs/Default rates for each individual counterparty Default indicator: observed, fitted, inclusive bandwidths Default Rate Original PD ( 0 3m ( 3m 6m ( 6m 9m ( 9m 1y ( 1y 1.5y ( 1.5y 2y Stressed default rate (annualized 1996q1 1997q1 1998q1 1999q1 2000q1 2001q1 2002q1 2003q1 2004q1 2005q1 2006q1 2007q1 2008q1 2009q1 2010q1 2011q1 10d 3m 6m 9m 1y 1.5y 2y time time 8

10 Example: Approach for Credit Risk PDs (2 Estimations of dependencies of default indicators on macroeconomic variables per region/industry cluster lnpd it = 0 + β1x1, it β K x K, it β + u + η + ε i t it E.g. GDP growth decrease by 1% default rate increase by..% E.g. Interest rate increase by 1% default rate increase by..% Use estimated betas to forecast future default rates Scale to UBS portfolio 1996q1 1997q1 1998q1 1999q1 2000q1 2001q1 2002q1 2003q1 2004q1 2005q1 2006q1 2007q1 2008q1 2009q1 2010q1 2011q1 Default indicator: observed, fitted, inclusive bandwidths time 9

11 Example: Approach for Credit Risk EAD Banking products (loans, credit line Assume full utilization of committed credit lines Stressed according to the FX shocks specified in the scenario raded products (OCs and SFs Stressed by shocking all risk factors as specified in the scenario (IR; FX; EQ Corresponding netting rules applied Re-margining assumptions Exposure ( 0 3m ( 3m 6m ( 6m 9m ( 9m 1y ( 1y 1.5y ( 1.5y 2y Exposure Profile raded Products oday's exposure Exposure Profile Mortgage 10d 3m 6m 9m 1y 1.5y 2y time 10

12 Exposure sensitivities Exposure sensitivities at portfolio level: how much exposure change if EUR/CHF goes up by 10%? OC - FX SENSIIVIY - OAL EAD - SEPEMBER 2009 USD JPY AUD change in EAD, CHFbn -15% -10% -5% 0% +5% +10% +15% rel change in FX 11

13 Example: Scenario consistent calculation of credit and market losses IR swap with counterparty Xample Swap Value Notional 100 mio CHF UBS pays fix rate 1% Counterparty pays floating rate (last reset rate 2% Maturity 2 Y oday price: 1.7 mio CHF oday credit Exposure: CHF 1.7m Counterparty Credit View ABC Rating PD: 0.35% LGD: 0.45 Sector/Region: Material/US oday PD: 0.35% oday LGD: 0.45 oday EL = 0.35%*0.45*1.7 mio = CHF 2,677 12

14 Example: Scenario consistent calculation of credit and market losses IR swap with counterparty ABC today Q1'09 Q2'09 Q3'09 Q4'09 Q1'10 Q2'10 Q3'10 Q4'10 Real GDP growth (% yoy United States Corp credit spreads (US HY (B in bps, eop Fixed Income: 3-mth Libor rate (%, eop CHF Fixed Income: 10-yr Gov't bonds (%, eop CHF Swap Value Interest rate decreases he swap price is recomputed, resulting in lower MtM, therefore in a market loss and lower exposure to the counterparty Stress price: CHF 0.4m Stress credit Exposure: CHF 0.4m Stress market P&L = = CHF -1.3m Counterparty Credit View GDP growth down by 3% in Q109 increase PD by 3*20% = 60% (purely illustrative Interest rates down by 0.5% in Q109 (compared to 3% today IR results in decrease PD by -0.5*20% = 10% Stress PD: 0.35%*(1+0.6*(1-0.1=0.504% LGD assumed constant: 0.45 Stress EL = 0.504%*0.45*0.4 mio = CHF 907 Scenario Consistent otal Stress loss = Stress P&L + Stress EL = 1.3m 907= 1.301m 13

15 Stressing the Capital Ratio Earnings Scenarios Reduce retained earnings Reduced Commissions and Fees Income Reduced rading Income Provisions and Basel II EL he deterioration of the credit quality of the portfolio induces an increase in the provisions and Basel II EL. 50% of the difference between the two (if positive must be subtracted from the available capital. ier1 Capital Ratio ier1 Capital before Stress Earnings Losses 0.5 BaselII EL Provisions RWA RWA Scenario Stress depends on Basel II treatment Higher credit RWA due to lower quality assets Higher Market Risk charges as market volatility feeds into VaR calculations Actual defaults and other losses Market Losses Credit Losses (defaults Increased Funding Costs Operational Losses 14

16 Stressing the Earnings How much the Wealth Management fees decrease conditional to a equity crash? - Statistically estimate sensitivities of income to macro-economic and financial indicators specified in Group stress scenarios Sensitivities account for changes in both business volumes and profit margins Example: Sensitivity of changes in WM Fee Income to returns of S&P500 index is 0.5 Example: If stress scenario specifies a 20% decline of S&P500 Index, then WM Fee Income is expected to decline by 10% (= 0.5*20% 15

17 Stressing Risk Weighted Assets Capital Ratio = Available Capital Risk Weighted Assets Loss Losses impact available capital Risk Weighted Assets are second part of the stress test Sensitive to all risk factors Impact is in many cases not direct Stress methodology for RWA parameters for credit risk PD: reaction of rating tools migrations, Recalibrations, planned changes in rating tools, hrough-the-cycle vs. point-in-time LGD: reaction of LGD tools reaction to changed macroeconomic parameters, Recalibrations EAD Reaction of exposure measurement tools under the scenario 16

18 Use of Stress esting Results Regular reporting Business Planning Capital Planning Risk Appetite definition Statistical Aggregation model 17

19 Challenges going forward Definition of scenarios Scenario severity perception (what is a stress test under stress Pro-cyclicality of stress scenarios and impact Methodology "Backtesting" of stress testing methodologies Concentration under stress Implement forward-looking assumptions about portfolio development Processes and Governance Integration in Business Decisions 18