PLA Test Requirements

No: 44047144

Date(g): 27/12/2022 | Date(h): 4/6/1444

Status: In-Force

12.20	The PLA test compares daily risk-theoretical P&L (RTPL) with the daily HPL for each trading desk. It intends to:
	(1)	measure the materiality of simplifications in a banks’ internal models used for determining market risk capital requirements driven by missing risk factors and differences in the way positions are valued compared with their front office systems; and
	(2)	prevent banks from using their internal models for the purposes of capital requirements when such simplifications are considered material.
12.21	The PLA test must be performed on a standalone basis for each trading desk in scope for use of the IMA.
Definition of profits and losses used for the PLA test and backtesting
12.22	The RTPL is the daily trading desk-level P&L that is produced by the valuation engine of the trading desk’s risk management model.
	(1)	The trading desk’s risk management model must include all risk factors that are included in the bank’s expected shortfall (ES) model with SAMA parameters and any risk factors deemed not modellable by SAMA, and which are therefore not included in the ES model for calculating the respective regulatory capital requirement, but are included in non-modellable risk factors.
	(2)	The RTPL must not take into account any risk factors that the bank does not include in its trading desk’s risk management model.
12.23	Movements in all risk factors contained in the trading desk’s risk management model should be included, even if the forecasting component of the internal model uses data that incorporates additional residual risk. For example, a bank using a multifactor beta-based index model to capture event risk might include alternative data in the calibration of the residual component to reflect potential events not observed in the name-specific historical time series. The fact that the name is a risk factor in the model, albeit modelled in a multifactor model environment, means that, for the purposes of the PLA test, the bank would include the actual return of the name in the RTPL (and in the HPL) and receive recognition for the risk factor coverage of the model.
12.24	The PLA test compares a trading desk’s RTPL with its HPL. The HPL used for the PLA test should be identical to the HPL used for backtesting purposes. This comparison is performed to determine whether the risk factors included and the valuation engines used in the trading desk’s risk management model capture the material drivers of the bank’s P&L by determining if there is a significant degree of association between the two P&L measures observed over a suitable time period. The RTPL can differ from the HPL for a number of reasons. However, a trading desk risk management model should provide a reasonably accurate assessment of the risks of a trading desk to be deemed eligible for the internal models-based approach.
12.25	The HPL must be calculated by revaluing the positions held at the end of the previous day using the market data of the present day (ie using static positions). As HPL measures changes in portfolio value that would occur when end-of-day positions remain unchanged, it must not take into account intraday trading nor new or modified deals, in contrast to the APL. Both APL and HPL include foreign denominated positions and commodities included in the banking book.
12.26	Fees and commissions must be excluded from both APL and HPL as well as valuation adjustments for which separate regulatory capital approaches have been otherwise specified as part of the rules (eg credit valuation adjustment and its associated eligible hedges) and valuation adjustments that are deducted from Common Equity Tier 1 (eg the impact on the debt valuation adjustment component of the fair value of financial instruments must be excluded from these P&Ls).
12.27	Any other market risk-related valuation adjustments, irrespective of the frequency by which they are updated, must be included in the APL while only valuation adjustments updated daily must be included in the HPL, unless the bank has received specific agreement to exclude them from SAMA. Smoothing of valuation adjustments that are not calculated daily is not allowed. P&L due to the passage of time should be included in the APL and should be treated consistently in both HPL and RTPL.⁴⁸
12.28	Valuation adjustments that the bank is unable to calculate at the trading desk level (eg because they are assessed in terms of the bank’s overall positions/risks or because of other constraints around the assessment process) are not required to be included in the HPL and APL for backtesting at the trading desk level, but should be included for bank-wide backtesting. To the satisfaction of SAMA, the bank must provide support for valuation adjustments that are not computed at a trading desk level.
12.29	Both APL and HPL must be computed based on the same pricing models (eg same pricing functions, pricing configurations, model parametrisation, market data and systems) as the ones used to produce the reported daily P&L.

PLA test data input alignment

12.30

For the sole purpose of the PLA assessment, banks are allowed to align RTPL input data for its risk factors with the data used in HPL if these alignments are documented, justified to SAMA and the requirements set out below are fulfilled:

(1)

Banks must demonstrate that HPL input data can be appropriately used for RTPL purposes, and that no risk factor differences or valuation engine differences are omitted when transforming HPL input data into a format which can be applied to the risk factors used in RTPL calculation.

(2)

Any adjustment of RTPL input data must be properly documented, validated and justified to SAMA.

(3)

Banks must have procedures in place to identify changes with regard to the adjustments of RTPL input data. Banks must notify SAMA of any such changes.

(4)

Banks must provide assessments on the effect these input data alignments would have on the RTPL and the PLA test. To do so, banks must compare RTPL based on HPL-aligned market data with the RTPL based on market data without alignment. This comparison must be performed when designing or changing the input data alignment process and upon the request of SAMA.

12.31

Adjustments to RTPL input data will be allowed when the input data for a given risk factor that is included in both the RTPL and the HPL differs due to different providers of market data sources or time fixing of market data sources, or transformations of market data into input data suitable for the risk factors of the underlying pricing models. These adjustments can be done either:

(1)

by direct replacement of the RTPL input data (eg par rate tenor x, provider a) with the HPL input data (eg par rate tenor x, provider b); or

(2)

by using the HPL input data (eg par rate tenor x, provider b) as a basis to calculate the risk factor data needed in the RTPL/ES model (eg zero rate tenor x).

In the event trading desks of a bank operate in different time zones compared to the location of the bank’s risk control department, data for risk modelling could be retrieved at different snapshot times compared to the data on which the desks’ front office P&L is based. Banks are permitted to align the snapshot time used for the calculation of the RTPL of a desk to the snapshot time used for the derivation of its HPL.

12.32

If the HPL uses market data in a different manner to RTPL to calculate risk parameters that are essential to the valuation engine, these differences must be reflected in the PLA test and as a result in the calculation of HPL and RTPL. In this regard, HPL and RTPL are allowed to use the same market data only as a basis, but must use their respective methods (which can differ) to calculate the respective valuation engine parameters. This would be the case, for example, where market data are transformed as part of the valuation process used to calculate RTPL. In that instance, banks may align market data between RTPL and HPL pre-transformation but not post- transformation.

12.33

Banks are not permitted to align HPL input data for risk factors with input data used in RTPL. Adjustments to RTPL or HPL to address residual operational noise are not permitted. Residual operational noise arises from computing HPL and RTPL in two different systems at two different points in time. It may originate from transitioning large portions of data across systems, and potential data aggregations may result in minor reconciliation gaps below tolerance levels for intervention; or from small differences in static/reference data and configuration.

PLA test metrics

12.34

The PLA requirements are based on two test metrics:

(1)

the Spearman correlation metric to assess the correlation between RTPL and HPL; and

(2)

the Kolmogorov-Smirnov (KS) test metric to assess similarity of the distributions of RTPL and HPL.

12.35

To calculate each test metric for a trading desk, the bank must use the time series of the most recent 250 trading days of observations of RTPL and HPL.

Process for determining the Spearman correlation metric

12.36

For a time series of HPL, banks must produce a corresponding time series of ranks based on the size of the P&L (R_HPL). That is, the lowest value in the HPL time series receives a rank of 1, the next lowest value receives a rank of 2 and so on.

12.37

Similarly, for a time series of RTPL, banks m0ust produce a corresponding time series of ranks based on size (R_RTPL).

12.38

Banks must calculate the Spearman correlation coefficient of the two time series of rank values of R_RTPL and R_HPL based on size using the following formula, where σ_RHPL and σ_RRTPL are the standard deviations of R_RTPL and R_HPL.

Process for determining Kolmogorov-Smirnov test metrics

12.39

The bank must calculate the empirical cumulative distribution function of RTPL. For any value of RTPL, the empirical cumulative distribution is the product of 0.004 and the number of RTPL observations that are less than or equal to the specified RTPL.

12.40

The bank must calculate the empirical cumulative distribution function of HPL. For any value of HPL, the empirical cumulative distribution is the product of 0.004 and number of HPL observations that are less than or equal to the specified HPL.

12.41

The KS test metric is the largest absolute difference observed between these two empirical cumulative distribution functions at any P&L value.

PLA test metrics evaluation

12.42

Based on the outcome of the metrics, a trading desk is allocated to a PLA test red zone, an amber zone or a green zone as set out in Table 2.

(1)

A trading desk is in the PLA test green zone if both

(a)

the correlation metric is above 0.80; and

(b)

the KS distributional test metric is below 0.09 (p-value = 0.264).

(2)

A trading desk is in the PLA test red zone if the correlation metric is less than 0.7 or if the KS distributional test metric is above 0.12 (p-value = 0.055).

(3)

A trading desk is in the PLA amber zone if it is allocated neither to the green zone nor to the red zone.

PLA test thresholds		Table 2
Zone	Spearman correlation	KS test
Amber zone thresholds	0.80	0.09 (p-value = 0.264)
Red zone thresholds	0.70	0.12 (p-value = 0.055)

12.43

If a trading desk is in the PLA test red zone, it is ineligible to use the IMA to determine market risk capital requirements and must be use the standardised approach.

(1)

Risk exposures held by these ineligible trading desks must be included with the out-of- scope trading desks for purposes of determining capital requirement per the standardised approach.

(2)

A trading desk deemed ineligible to use the IMA must remain out-of-scope to use the IMA until:

(a)

the trading desk produces outcomes in the PLA test green zone; and

(b)

the trading desk has satisfied the backtesting exceptions requirements over the past 12 months.

12.44

If a trading desk is in the PLA test amber zone, it is not considered an out-of-scope trading desk for use of the IMA.

(1)

If a trading desk is in the PLA test amber zone, it cannot return to the PLA test green zone until:

(a)

the trading desk produces outcomes in the PLA test green zone; and

(b)

the trading desk has satisfied its backtesting exceptions requirements over the prior 12 months.

(2)

Trading desks in the PLA test amber zone are subject to a capital surcharge as specified in [13.43]

⁴⁸ Time effects can include various elements such as: the sensitivity to time, or theta effect (ie using mathematical terminology, the first-order derivative of the price relative to the time) and carry or costs of funding.

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