Stress Testing

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  • Stress Testing

    1. 1. Stress Testing
    2. 2. VAR - what does it mean(value-at-risk) - the worst expected loss over a given horizon under normal market conditions at a given confidence level
    3. 3. MAIN PROBLEM VAR m easure s can fai l to i de ntify extrem e u n u sual situations losses
    4. 4. STRESS TESTING a process to identify and manage situations that could cause extraordinary losses
    5. 5. STRESS TESTING toolsscenario analysisstressing modelspolicy responses
    6. 6. Why stress testing? Simulating: SHOCKS THAT HAVE NEVER OCCURRED SHOCKS THAT REFLECT PERMANENT STRUCTURAL BREAK
    7. 7. Imprementing scenario analysis Rp,s =∑Wi,t • Ri,s s - selected scenario i - number of scenarios R - portfolio return ❖
    8. 8. generating unidimensional scenarios Guidelines for scenarios by DPG✓Parallel yield curve shifting by ±100 basis points✓ Yield curve twisting by ±25 basis points✓ Each of the four combinations or yield curves shift andtwist✓ Equity index values changing by ±10 percent✓ Currencies moving by ±6 percent for marjor currencies✓ Swap spreads changing by ±20 basis points
    9. 9. The OTS* requiersto estimate what would happen toyour economic value under parallelshifts in the yield curve varyingfrom -400 to +400 basis points*The office of Thrift Supervision
    10. 10. The SPAN system* The objective:to identify movements in portfolio values under a series of scenarios➙ SPAN searches for the largest loss that aportfolio may suffer and sets the margin at that level *1998, Chicago Mercantile Exchange
    11. 11. The SPAN system ✔ it considers only two risk factors ✘ places the same probability on most of the scenarios ✘ ignores correlations between risk factors
    12. 12. Multidimensional scenario analysis Unidimensional scenarios Prospective Scenarios Factor Push Method Conditional Scenario Method Historical Scenatios Systematic Scenarios
    13. 13. «Bottom-up approach»◈ posting a state of the world◈ inferring movements in market as in a top-down approach
    14. 14. Prospective ScenariosAn earthquake or war? Examine the effect*not well suited to large, complex pertfolios
    15. 15. Factor Push Method➙ push up and down ➙ compute the changes to theportfolio➙ evaluate a worst-case scenario, pushing allparametres in the «worst loss» position*completely ignores correlation*looking at extreme movements may not be appropriate
    16. 16. Conditional scenario Method ≈conditional normal VAR modeling▸ at the core is the covariance matrix▸ «KEY» variables R* + other variables R ASL = ∑ w *R *+ ∑ w R i i i j j j ✘ results are much closer to the actual stress loss ✘ only in case where correlation plays the main role
    17. 17. Historical Scenarios✓ helps to identifyscenarios that may beoutside the VAR window✓ are useful to measurejoint movements in financialvariables
    18. 18. Systematic ScenariosThis analysis provides insight into the vulnerabilities of a particular portfolio Maximum-loss criterion To identify the wors loss through an optimization that respects the correlations between the risk-factor movements ∆⨍ ML = min loss (∆⨍ ) subject to ⨍ˈ∑⁻¹ ∆⨍ ≤ C
    19. 19. Stress testing model parametersSensitivity We need details! analysis Model Use the same period!parameters
    20. 20. Managing Stress Tests Relevant scenarios require careful planning(1) Purchase protection or insurance for theevents in quiestion(2) Modify the portfolio to decrease the impact ofthe event(3) Diversify(4) Develop a plan to correct course of action(5) Prepare sources of alternative funding
    21. 21. Conclusions People may be very bad at pre!cting extreme situations✓stress test can be viewed as an extension of the historicalsimulation method at increasingly higher confidence levels✓«blind spots» or complement to standard VARmth✓a complement to VARmth rather than a replacement✗ can lead to a large amount of unfiltered information✗ the risk to produce large numbers of scenarios✗ difficult to interpret
    22. 22. Stress testing reminds:VAR is no guarantee of worst case loss

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