Minimum Capital Requirements for Market Risk

In the event an outlier can be shown by the bank to relate to a non-modellable risk factor, and the capital requirement for that non-modellable risk factor exceeds the actual or hypothetical loss for that day, it may be disregarded for the purpose of the overall backtesting process if SAMA is notified accordingly and does not object to this treatment. In these cases, a bank must document the history of the movement of the value of the relevant non-modellable risk factor and have supporting evidence that the non-modellable risk factor has caused the relevant loss. If the backtesting exception at a desk-level test is being driven by a non-modellable risk factor that receives an SES capital requirement that is in excess of the maximum of the APL loss or HPL loss for that day, it is permitted to be disregarded for the purposes of the desk-level backtesting. The bank must be able to calculate a non-modellable risk factor capital requirement for the specific desk and not only for the respective risk factor across all desks. For example, if the P&L for a desk is SAR –1.5 million and VaR is SAR 1 million, a non-modellable risk factor capital requirement (at desk level) of EUR 0.8 million would not be sufficient to disregard an exception for the purpose of desk-level backtesting. The non-modellable risk factor capital requirement attributed to the standalone desk level (without VaR) must be greater than the loss of SAR 1.5 million in order to disregard an exception for the purpose of desk-level backtesting. 12.7 The scope of the portfolio subject to bank-wide backtesting should be updated quarterly based on the results of the latest trading desk-level backtesting, risk factor eligibility test and PLA tests. 12.8 The framework for SAMA interpretation of backtesting results for the bank-wide capital model encompasses a range of possible responses, depending on the strength of the signal generated from the backtesting. These responses are classified into three backtesting zones, distinguished by colours into a hierarchy of responses. (1) Green zone. This corresponds to results that do not themselves suggest a problem with the quality or accuracy of a bank’s model. (2) Amber zone. This encompasses results that do raise questions in this regard, for which such a conclusion is not definitive. (3) Red zone. This indicates a result that almost certainly indicates a problem with a bank’s risk model. 12.9 These zones are defined according to the number of exceptions generated in the backtesting programme considering statistical errors as explained in [16.9] to [16.21] . Table 1 sets out boundaries for these zones and the presumptive SAMA response for each backtesting outcome, based on a sample of 250 observations. Backtesting zones Table 1 Backtesting zone Number of exceptions Backtesting dependent multiplier (to be added to any qualitative add-on per [MAR33.44]) Green 0 1.50 1 1.50 2 1.50 3 1.50 4 1.50 Amber 5 1.70 6 1.76 7 1.83 8 1.88 9 1.92 Red 10 or more 2.00 12.10 The backtesting green zone generally would not initiate a SAMA increase in capital requirements for backtesting (ie no backtesting add-on would apply). 12.11 Outcomes in the backtesting amber zone could result from either accurate or inaccurate models. However, they are generally deemed more likely for inaccurate models than for accurate models. Within the backtesting amber zone, SAMA will impose a higher capital requirement in the form of a backtesting add-on. The number of exceptions should generally inform the size of any backtesting add-on, as set out in Table 1 of [12.9]. 12.12 A bank must also document all of the exceptions generated from its ongoing backtesting programme, including an explanation for each exception. 12.13 A bank may also implement backtesting for confidence intervals other than the 99th percentile, or may perform other statistical tests not set out in this standard.