Calculation of Expected Shortfall

The ES measure must be calibrated to a period of stress. (1) Specifically, the ES measure must replicate an ES outcome that would be generated on the bank’s current portfolio if the relevant risk factors were experiencing a period of stress. This is a joint assessment across all relevant risk factors, which will capture stressed correlation measures. (2) This calibration is to be based on an indirect approach using a reduced set of risk factors. Banks must specify a reduced set of risk factors that are relevant for their portfolio and for which there is a sufficiently long history of observations. (a) This reduced set of risk factors is subject to SAMA approval and must meet the data quality requirements for a modellable risk factor as outlined in [11.12] to [11.24] . (b) The identified reduced set of risk factors must be able to explain a minimum of 75% of the variation of the full ES model (ie the ES of the reduced set of risk factors should be at least equal to 75% of the fully specified ES model on average measured over the preceding 12- week period). The indicator that must be maximised for the identification of the stressed period is the aggregate capital requirement for modellable risk factors (IMCC) as per [13.15] , it has to be maximised for the modellable risk factors, which implies that ESr,s is maximised, as noted in [13.7]. The reduced set of risk factors must be able to explain a minimum of 75% of the variation of the full ES model at the group level for the aggregate of all desks with IMA model approval. 13.6 The ES for market risk capital purposes is therefore expressed as follows, where: (1) The ES for the portfolio using the above reduced set of risk factors (ES R,S ), is calculated based on the most severe 12-month period of stress available over the observation horizon. (2) ES R,S is then scaled up by the ratio of (i) the current ES using the full set of risk factors to (ii) the current ES measure using the reduced set of factors. For the purpose of this calculation, this ratio is floored at 1. (a) ES F,C is the ES measure based on the current (most recent) 12-month observation period with the full set of risk factors; and (b) ES R,C is the ES measure based on the current period with a reduced set of risk factors. 13.7 For measures based on stressed observations (ES R,S ), banks must identify the 12-month period of stress over the observation horizon in which the portfolio experiences the largest loss. The observation horizon for determining the most stressful 12 months must, at a minimum, span back to and include 2007. Observations within this period must be equally weighted. Banks must update their 12- month stressed periods at least quarterly, or whenever there are material changes in the risk factors in the portfolio. Whenever a bank updates its 12-month stressed periods it must also update the reduced set of risk factors (as the basis for the calculations of E R,C and E R,S ) accordingly. 13.8 For measures based on current observations (ES F,C ), banks must update their data sets no less frequently than once every three months and must also reassess data sets whenever market prices are subject to material changes. (1) This updating process must be flexible enough to allow for more frequent updates. (2) SAMA may also require a bank to calculate its ES using a shorter observation period if, in SAMA’s judgement; this is justified by a significant upsurge in price volatility. In this case, however, the period should be no shorter than six months. 13.9 No particular type of ES model is prescribed. Provided that each model used captures all the material risks run by the bank, as confirmed through profit and loss (P&L) attribution (PLA) tests and backtesting, and conforms to each of the requirements set out above and below, SAMA may permit banks to use models based on either historical simulation, Monte Carlo simulation, or other appropriate analytical methods.