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test ../ test user-ref.html
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test ../ test getting-started.html
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test ../ test getting-started/using-this-guide.html
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test ../ test getting-started/whats-new.html
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test ../ test getting-started/frtb-data-model.html
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test ../ test getting-started/directquery.html
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test ../ test configuration.html
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test ../ test tutorials/data-sanity-check.html
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test ../ test tutorials/tips-for-validating-the-calculations.html
- Tips for Validating the Calculations
test ../ test tutorials/viewing-qis-numbers.html
- Viewing QIS Numbers
test ../ test interpret-impl.html
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test ../ test cube.html
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test ../ test cube/measures.html
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Measures
test ../ test cube/measures/measure-variations.html
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Measure variations
test ../ test cube/measures/standardisedapproach.html
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StandardisedApproach
test ../ test cube/measures/stresscalibration.html
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StressCalibration
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test ../ test dev/dev-tools.html
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test ../ test dev/dev-sign-off.html
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test ../ test what-if.html
What-If Analysis
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test ../ test glossary.html
Glossary
ES (Model Variation)
Description
For each risk class and allin risk class, this is the ratio of the liquidity adjusted ES for reduced current set and ES for full current set
Hierarchies required in the view
Reference
[MAR33.5]
Formula
$$\frac{ES_{R,C}}{ES_{F,C}}$$
To evaluate how much variation of the full ES model is explained by the reduced set of risk-factors (MAR 33.5 (2) (b)), the ES (Model Variation) avg measure should be evaluated for the allin risk-class.
The ES (Model Variation) measure is the ratio of the ES (Liquidity Adj.) measures for the reduced and full sets of risk factors (over the current data set). i.e. ES_{R,C} / ES_{F,C}. As per MAR33.5 (2) (b), this ratio should average over 75% for the last 12 weeks.
See also