This chapter sets out the calculation of the sensitivities-based method under the standardised approach for market risk.
The sensitivities of financial instruments to a prescribed list of risk factors are used to calculate the delta, vega and curvature risk capital requirements. These sensitivities are risk-weighted and then aggregated, first within risk buckets (risk factors with common characteristics) and then across buckets within the same risk class as set out in MAR21.8 to MAR21.14. The following terminology is used in the sensitivities-based method:
In applying the sensitivities-based method, all instruments held in trading desks as set out in MAR12 and subject to the sensitivities-based method (ie excluding instruments where the value at any point in time is purely driven by an exotic underlying as set out in MAR23.3), are subject to delta risk capital requirements. Additionally, the instruments specified in (1) to (4) are subject to vega and curvature risk capital requirements:
| 1 | For example, each instrument that is an option or that includes an option (eg an embedded option such as convertibility or rate dependent prepayment and that is subject to the capital requirements for market risk). A non-exhaustive list of example instruments with optionality includes: calls, puts, caps, floors, swaptions, barrier options and exotic options. |
| 2 | An instrument with a prepayment option is a debt instrument which grants the debtor the right to repay part of or the entire principal amount before the contractual maturity without having to compensate for any foregone interest. The debtor can exercise this option with a financial gain to obtain funding over the remaining maturity of the instrument at a lower rate in other ways in the market. |
As set out in MAR21.1, the capital requirement under the sensitivities-based method is calculated by aggregating delta, vega and curvature capital requirements. The relevant paragraphs that describe this process are as follows:
For each risk class, a bank must determine its instruments’ sensitivity to a set of prescribed risk factors, risk weight those sensitivities, and aggregate the resulting risk-weighted sensitivities separately for delta and vega risk using the following step-by-step approach:
for all risk factors in bucket b; and
for all risk factors in bucket c.
For each risk class, to calculate curvature risk capital requirements a bank must apply an upward shock and a downward shock to each prescribed risk factor and calculate the incremental loss for instruments sensitive to that risk factor above that already captured by the delta risk capital requirement using the following step-by-step approach:
for the FX and equity risk classes, is the delta sensitivity of instrument i; and
for the GIRR, CSR and commodity risk classes, is the sum of delta sensitivities to all tenors of the relevant curve of instrument i with respect to curvature risk factor k.
Where , this shall be termed "selecting the upward scenario".
Where , this shall be termed "selecting the downward scenario".
In the specific case where if
, it is deemed that the upward scenario is selected; otherwise the downward scenario is selected.
| FAQ1 | When the delta effect is removed in the calculation of the curvature risk capital requirement, should the delta used in that calculation be the same as the delta used in the delta risk capital requirement? Should the same assumptions that go into the calculation of the delta (ie sticky delta for normal or log-normal volatilities) go into the calculation of the shifted or shocked price of the instrument? The delta used for the calculation of the curvature risk capital requirement should be the same as that used for calculating the delta risk capital requirement. The assumptions that are used for the calculation of the delta (ie sticky delta for normal or log-normal volatilities) should also be used for calculating the shifted or shocked price of the instrument. |
| FAQ2 | Are banks permitted to choose between zero rate and market rate sensitivities for GIRR delta and curvature capital requirements? MAR21.17 states that banks must determine each delta sensitivity, vega sensitivity and curvature scenario based on instrument prices or pricing models that an independent risk control unit within a bank uses to report market risks or actual profits and losses to senior management. Banks should use zero rate or market rate sensitivities consistent with the pricing models referenced in that paragraph. |
In order to address the risk that correlations increase or decrease in periods of financial stress, the aggregation of bucket level capital requirements and risk class level capital requirements per each risk class for delta, vega, and curvature risks as specified in MAR21.4 to MAR21.5 must be repeated, corresponding to three different scenarios on the specified values for the correlation parameter (correlation between risk factors within a bucket) and
(correlation across buckets within a risk class).
The total capital requirement under the sensitivities-based method is aggregated as follows:
GIRR factors
| 3 | The assignment of risk factors to the specified tenors should be performed by linear interpolation or a method that is most consistent with the pricing functions used by the independent risk control function of a bank to report market risks or P&L to senior management. |
| 4 | Cross-currency basis are basis added to a yield curve in order to evaluate a swap for which the two legs are paid in two different currencies. They are in particular used by market participants to price cross-currency interest rate swaps paying a fixed or a floating leg in one currency, receiving a fixed or a floating leg in a second currency, and including an exchange of the notional in the two currencies at the start date and at the end date of the swap. |
| 5 | For example, an option with a forward starting cap, lasting 12 months, consists of four consecutive caplets on USD three-month Libor. There are four (independent) options, with option expiry dates in 12, 15, 18 and 21 months. These options are all on underlying USD three-month Libor; the underlying always matures three months after the option expiry date (its residual maturity being three months). Therefore, the implied volatilities for a regular forward starting cap, which would start in one year and last for 12 months should be defined along the following two dimensions: (i) the maturity of the option’s individual components (caplets) – 12, 15, 18 and 21 months; and (ii) the residual maturity of the underlying of the option – three months. |
| FAQ1 | Different results can be produced depending on the bank’s curve methodology as diversification will be different for different methodologies. For example, if three-month Euribor is constructed as a “spread to EONIA”, this curve will be a spread curve and can be considered a different yield curve for the purpose of computing risk-weighted PV01 and subsequent diversification. In this example, should three-month Euribor and EONIA be considered two distinct yield curves for the purpose of computing the risk capital requirement? MAR21.8(1)(c)states that for the purpose of constructing the risk-free yield curve per currency, an overnight index swap curve (such as EONIA) and an interbank offered rate curve (such as three-month Euribor) must be considered two different curves, with distinct risk factors in each tenor bucket, for the purpose of computing the risk capital requirement. |
| FAQ2 | For GIRR, CSR, equity risk, commodity risk or FX risk, risk factors need to be assigned to prescribed tenors. How should this assignment be performed if the internally used tenors do not match the prescribed ones? Banks are not permitted to perform capital computations based on internally used tenors. Risk factors and sensitivities must be assigned to the prescribed tenors. As stated in footnote 3 to MAR21.8 and footnote 8 to MAR21.25, the assignment of risk factors and sensitivities to the specified tenors should be performed by linear interpolation or a method that is most consistent with the pricing functions used by the independent risk control function of the bank to report market risks or profits and losses to senior management. |
| FAQ3 | When calculating the cross-currency basis spread (CCBS) capital requirement: since pricing models use a term structure-based CCBS curve, is it acceptable to use sensitivities to individual tenors aggregated by simple sum rather than explicitly modelling the CCBS curve as flat in the pricing model? Yes. Banks may use a term structure-based CCBS curve and aggregate sensitivities to individual tenors by simple sum. |
| FAQ4 | Should inflation and cross-currency bases be included as a risk factor in the vega GIRR capital requirement? Yes. Inflation and cross-currency bases are included in the GIRR vega risk capital requirement. As no maturity dimension is specified for the delta capital requirement for inflation or cross-currency bases (ie the possible underlying of the option), the vega risk for inflation and cross-currency bases should be considered only along the single dimension of the maturity of the option. |
| FAQ5 | Should a bank compute delta, vega and curvature risk for callable bonds, options on sovereign bond futures and bond options? For the specified instruments, delta, vega and curvature capital requirements must be computed for both GIRR and CSR. |
| FAQ6 | The sensitivities-based approach defines the repo risk factor only in the context of equities and not for fixed income funding instruments (to the extent that these instruments fall within the trading book definition as trading-related repo-style transactions). Is it the intention that fixed income funding instruments be excluded from the equity repo treatment? If so, should such funding instruments be subject to the GIRR capital requirement – for example, by considering the repo curve for a given currency as a yield curve subject to interest rate shocks? Repo rate risk factors for fixed income funding instruments are subject to the GIRR capital requirement. A relevant repo curve should be considered by currency. |
| FAQ7 | May risk weights be floored for interest rate and credit instruments when applying the risk weights for GIRR or for CSR, given that there is a possibility of the interest rates being negative (eg for JPY and EUR curves)? No such floor is permitted in the market risk standard. |
CSR non-securitisation risk factors
| FAQ1 | The second FAQ under MAR21.8 is also relevant to this paragraph. |
| FAQ2 | Should a bank compute delta, vega and curvature risk for callable bonds, options on sovereign bond futures and bond options? For the specified instruments, delta, vega and curvature capital requirements must be computed for both GIRR and CSR. |
| FAQ3 | MAR21.9(3) explicitly states that, for CSR curvature, the bond-CDS basis is ignored. Is it correct that, under MAR21.9(1), bond and CDS curves are considered distinct risk factors and the only “basis” taken into account in in MAR21.54 and MAR21.55 is the bond-CDS basis? Yes. Bond and CDS credit spreads are considered distinct risk factors under MAR21.9(1), and referenced in MAR21.54 and MAR21.55 is meant to capture only the bond-CDS basis. |
| FAQ4 | May risk weights be floored for interest rate and credit instruments when applying the risk weights for GIRR or for CSR, given that there is a possibility of the interest rates being negative (eg for JPY and EUR curves)? No such floor is permitted in the market risk standard. |
CSR securitisation: non-CTP risk factors
| FAQ1 | The second FAQ under MAR21.8 is also relevant to this paragraph. |
| FAQ2 | May risk weights be floored for interest rate and credit instruments when applying the risk weights for GIRR or for CSR, given that there is a possibility of the interest rates being negative (eg for JPY and EUR curves)? No such floor is permitted in the market risk standard. |
CSR securitisation: CTP risk factors
| FAQ1 | The second FAQ under MAR21.8 is also relevant to this paragraph. |
| FAQ2 | May risk weights be floored for interest rate and credit instruments when applying the risk weights for GIRR or for CSR, given that there is a possibility of the interest rates being negative (eg for JPY and EUR curves)? No such floor is permitted in the market risk standard. |
Equity risk factors
| FAQ1 | The second FAQ under MAR21.8 is also relevant to this paragraph. |
| FAQ2 | The sensitivities-based approach defines the repo risk factor only in the context of equities and not for fixed income funding instruments (to the extent that these instruments fall within the trading book definition as trading-related repo-style transactions). Is it the intention that fixed income funding instruments be excluded from the equity repo treatment? If so, should such funding instruments be subject to the GIRR capital requirement – for example, by considering the repo curve for a given currency as a yield curve subject to interest rate shocks? Repo rate risk factors for fixed income funding instruments are subject to the GIRR capital requirement. A relevant repo curve should be considered by currency. |
Commodity risk factors
| 6 | For example, a contract that can be delivered in five ports can be considered having the same delivery location as another contract if and only if it can be delivered in the same five ports. However, it cannot be considered having the same delivery location as another contract that can be delivered in only four (or less) of those five ports. |
| FAQ1 | The second FAQ under MAR21.8 is also relevant to this paragraph. |
| FAQ2 | How are commodity delta risk factors computed for futures and forward contracts? The current prices for futures and forward contracts should be used to compute the commodity delta risk factors. Commodity delta should be allocated to the relevant tenor based on the tenor of the futures and forward contract and given that spot commodity price positions should be slotted into the first tenor (0 years). |
FX risk factors
the reporting currency; and
both the currency in which an instrument is denominated and any other currencies referenced by the instrument.7
the FX risk against the base currency; but also
the FX risk between the reporting currency and the base currency (ie translation risk).
To use this alternative, a bank may only consider a single currency as its base currency; and
The bank shall demonstrate to the relevant supervisor that calculating FX risk relative to their proposed base currency provides an appropriate risk representation for their portfolio (for example, by demonstrating that it does not inappropriately reduce capital requirements relative to those that would be calculated without the base currency approach) and that the translation risk between the base currency and the reporting currency is taken into account.
the reporting currency; and
both the currency in which an instrument is denominated and any other currencies referenced by the instrument.
| 7 | For example, for an FX forward referencing USD/JPY, the relevant risk factors for a CAD-reporting bank to consider are the exchange rates USD/CAD and JPY/CAD. If that CAD-reporting bank calculates FX risk relative to a USD base currency, it would consider separate deltas for the exchange rate JPY/USD risk and CAD/USD FX translation risk and then translate the resulting capital requirement to CAD at the USD/CAD spot exchange rate. |
| FAQ1 | The second FAQ under MAR21.8 is also relevant to this paragraph. |
| FAQ2 | MAR21.14(4) states: “No distinction is required between onshore and offshore variants of a currency for all FX delta, vega and curvature risk factors.” Does this also apply for deliverable/non-deliverable variants (eg KRO vs KRW, BRO vs BRL, INO vs INR)? Yes. No distinction is required between deliverable and non-deliverable variants of a currency. |
Sensitivities for each risk class must be expressed in the reporting currency of the bank.
For each risk factor defined in MAR21.8 to MAR21.14, sensitivities are calculated as the change in the market value of the instrument as a result of applying a specified shift to each risk factor, assuming all the other relevant risk factors are held at the current level as defined in MAR21.17 to MAR21.38.
FAQ1| FAQ1 | In the context of delta sensitivity calculations, is it acceptable to use alternative formulations of sensitivities calculations that yield results very close to the prescribed formulation of sensitivities calculations? Yes, as per MAR21.17, a bank may make use of alternative formulations of sensitivities based on pricing models that the bank’s independent risk control unit uses to report market risks or actual profits and losses to senior management. In doing so, the bank is to demonstrate to its supervisor that the alternative formulations of sensitivities yield results very close to the prescribed formulations. |
In calculating the risk capital requirement under the sensitivities-based method in MAR21, the bank must determine each delta and vega sensitivity and curvature scenario based on instrument prices or pricing models that an independent risk control unit within a bank uses to report market risks or actual profits and losses to senior management.
FAQ1, FAQ2| FAQ1 | In the context of delta sensitivity calculations, is it acceptable to use alternative formulations of sensitivities calculations that yield results very close to the prescribed formulation of sensitivities calculations? Yes, as per MAR21.17, a bank may make use of alternative formulations of sensitivities based on pricing models that the bank’s independent risk control unit uses to report market risks or actual profits and losses to senior management. In doing so, the bank is to demonstrate to its supervisor that the alternative formulations of sensitivities yield results very close to the prescribed formulations. |
| FAQ2 | Are banks permitted to choose between zero rate and market rate sensitivities for GIRR delta and curvature capital requirements? MAR21.17 states that banks must determine each delta sensitivity, vega sensitivity and curvature scenario based on instrument prices or pricing models that an independent risk control unit within a bank uses to report market risks or actual profits and losses to senior management. Banks should use zero rate or market rate sensitivities consistent with the pricing models referenced in that paragraph. |
A key assumption of the standardised approach for market risk is that a bank’s pricing models used in actual profit and loss reporting provide an appropriate basis for the determination of regulatory capital requirements for all market risks. To ensure such adequacy, banks must at a minimum establish a framework for prudent valuation practices that include the requirements of CAP50.
Delta GIRR: the sensitivity is defined as the PV01. PV01 is measured by changing the interest rate r at tenor t (rt) of the risk-free yield curve in a given currency by 1 basis point (ie 0.0001 in absolute terms) and dividing the resulting change in the market value of the instrument (Vi) by 0.0001 (ie 0.01%) as follows, where:
| FAQ1 | Are banks permitted to choose between zero rate and market rate sensitivities for GIRR delta and curvature capital requirements? MAR21.17 states that banks must determine each delta sensitivity, vega sensitivity and curvature scenario based on instrument prices or pricing models that an independent risk control unit within a bank uses to report market risks or actual profits and losses to senior management. Banks should use zero rate or market rate sensitivities consistent with the pricing models referenced in that paragraph. |
Delta CSR non-securitisation, securitisation (non-CTP) and securitisation (CTP): the sensitivity is defined as CS01. The CS01 (sensitivity) of an instrument i is measured by changing a credit spread cs at tenor t (cst) by 1 basis point (ie 0.0001 in absolute terms) and dividing the resulting change in the market value of the instrument (Vi) by 0.0001 (ie 0.01%) as follows:
| FAQ1 | In cases where the bank does not have counterparty-specific money market curves, can the bank proxy PV01 to CS01? Yes. Proxying PV01 to CS01 is permitted for such money market instruments. |
Delta equity spot: the sensitivity is measured by changing the equity spot price by 1 percentage point (ie 0.01 in relative terms) and dividing the resulting change in the market value of the instrument (Vi) by 0.01 (ie 1%) as follows, where:
Delta equity repo rates: the sensitivity is measured by applying a parallel shift to the equity repo rate term structure by 1 basis point (ie 0.0001 in absolute terms) and dividing the resulting change in the market value of the instrument Vi by 0.0001 (ie 0.01%) as follows, where:
Delta commodity: the sensitivity is measured by changing the commodity spot price by 1 percentage point (ie 0.01 in relative terms) and dividing the resulting change in the market value of the instrument Vi by 0.01 (ie 1%) as follows, where:
| FAQ1 | In relation to the curvature risk capital requirement for the commodity risk class, MAR21.99 requires that the curvature risk weight is the parallel shift of all the tenors for each curve based on the highest prescribed delta risk weight for each bucket. A parallel shift in MAR21.99 implies that an additive shock (in absolute terms) is applied along the curve. However, MAR21.23 states that the shock applied to delta commodity is a relative shock. How should the shock be applied to commodity curvature? The sizes of upward and downward shocks applied to assess the net curvature risk capital requirement for a specific commodity´s curvature risk factor should be based on the risk weight connected to the curvature bucket where that commodity is classified, in accordance with MAR21.97 and MAR21.82. The same relative shocks should be applied to all curvature risk factors classified under the same bucket, defined along the dimension of the constructed curve (ie no term structure decomposition) per each commodity spot price, as described in MAR21.13(3). For example, the constructed curve for gold (with a risk weight of 20%) would be shifted up by multiplying each tenor price by 1.2 and down by multiplying each tenor price by 0.8. |
Delta FX: the sensitivity is measured by changing the exchange rate by 1 percentage point (ie 0.01 in relative terms) and dividing the resulting change in the market value of the instrument Vi by 0.01 (ie 1%), where:
The option-level vega risk sensitivity to a given risk factor8 is measured by multiplying vega by the implied volatility of the option as follows, where:
The following sets out how to derive vega risk sensitivities in specific cases:
| FAQ1 | Under the sensitivities-based method, would a bank need to compute vega risk over the longest maturity for a cancellable swap? Would a bank also be required to compute residual risk for cancellable swaps? In the case where options do not have a specified maturity (eg cancellable swaps), the bank must assign those options to the longest prescribed maturity tenor for vega risk sensitivities and also assign such options to the RRAO. In the case of the bank viewing the optionality of the cancellable swap as a swaption, the bank must assign the swaption to the longest prescribed maturity tenor for vega risk sensitivities (as it does not have a specified maturity) and derive the residual maturity of the underlying of the option accordingly. |
When computing a first-order sensitivity for instruments subject to optionality, banks should assume that the implied volatility either:
For the calculation of vega sensitivities, the distribution assumptions (ie log-normal assumptions or normal assumptions) for pricing models are applied as follows:
| 9 | Since vega ( of an instrument is multiplied by its implied volatility ( ), the vega risk sensitivity for that instrument will be the same under the log-normal assumption and the normal assumption. As a consequence, banks may use a log-normal or normal assumption for GIRR and CSR (in recognition of the trade-offs between constrained specification and computational burden for a standardised approach). For the other risk classes, banks must only use a log-normal assumption (in recognition that this is aligned with common practices across jurisdictions). |
| FAQ1 | If banks may use either a log-normal or normal assumption for vega GIRR, does this mean that the same log-normal or normal assumption should be applied to all currencies, or can the application be different for different currencies? For example, is a bank permitted to adopt a normal assumption for EUR and a log-normal assumption for USD? To compute vega GIRR, banks may choose a mix of log-normal and normal assumptions for different currencies. |
If, for internal risk management, a bank computes vega sensitivities using different definitions than the definitions set out in this standard, the bank may transform the sensitivities computed for internal risk management purposes to deduce the sensitivities to be used for the calculation of the vega risk measure.
All vega sensitivities must be computed ignoring the impact of credit valuation adjustments (CVA).
In the delta and curvature risk context: for index instruments and multi-underlying options, a look-through approach should be used. However, a bank may opt not to apply the look-through approach for instruments referencing any listed and widely recognised and accepted equity or credit index, where:
| FAQ1 | When certain conditions set out in MAR21.31 are satisfied for instruments referencing any listed and widely recognised equity or credit index, a bank may opt not to apply the look-through approach. It is common for funds with diversified constituents to satisfy the conditions set out in MAR21.31. Are positions in funds and instruments that reference them permitted to apply the no look-through approach using index buckets? No. Capital requirements for equity investments in funds generally must be calculated in accordance with one of the three ways set out in MAR21.36 – the no look-through approach for equity and credit indices cannot be applied to funds that do not track a listed and widely recognised index even if their holdings meet the criteria set out in MAR21.31 (1) to (5). Subject to the criteria in MAR21.35, however, equity investment funds that invest purely in either equity or debt instruments to replicate a listed and widely-recognised index may be treated as if they were investments in the those equity or credit indices and apply the no look-through approach available for credit and equity indices on those funds if those investments in funds meet the requirements set out in MAR21.31 to MAR21.34. |
For a given instrument, irrespective of whether a look-through approach is adopted or not, the sensitivity inputs used for the delta and curvature risk calculation must be consistent.
Where a bank opts not to apply the look-through approach in accordance with MAR21.31, a single sensitivity shall be calculated to each widely recognised and accepted index that an instrument references. The sensitivity to the index should be assigned to the relevant delta risk bucket defined in MAR21.53 and MAR21.72 as follows:
A look-through approach must always be used for indices that do not meet the criteria set out in MAR21.31(2) to MAR21.31(5), and for any multi-underlying instruments that reference a bespoke set of equities or credit positions.
| 10 | In other words, a bank can initially not apply a look-through approach, and later decide to apply it. However once applied (for a certain type of instrument referencing a particular index), the bank will require supervisory approval to revert to a “no look-through” approach. |
| FAQ1 | In accordance with MAR21.58(1), sensitivities to credit spread risk (CSR) arising from the correlation trading portfolio (CTP) should be classified according to the same bucket structure as the one for CSR non-securitisation, as set out in MAR21.51, except for index buckets (bucket 17 and bucket 18). Since an index CTP should be considered a risk factor as a whole and cannot be broken down into its constituents, as stated in MAR21.34(2), how should a bank determine which bucket to assign the delta sensitivity of an index CTP instrument, given the aforementioned bucket structure? The delta CSR sensitivity of an index CTP instrument should be assigned to a single specific delta sector bucket consistent with the characteristics of, at least, 75% of the index constituents (taking into account the weightings of that index), in accordance with MAR21.33(1). If this is not possible, then the index should be assigned to bucket 16, “Other sector”. The sensitivity to that index CTP instrument should be considered and treated like any other single-name sensitivity assigned to that same sector bucket. |
For equity investments in funds that can be looked through as set out in RBC25.8(5)(a), banks must apply a look-through approach and treat the underlying positions of the fund as if the positions were held directly by the bank (taking into account the bank’s share of the equity of the fund, and any leverage in the fund structure), except for the funds that meet the following conditions:
For equity investments in funds that cannot be looked through (ie do not meet the criterion set out in RBC25.8(5)(a)), but that the bank has access to daily price quotes and knowledge of the mandate of the fund (ie meet both the criteria set out in RBC25.8(5)(b)), banks may calculate capital requirements for the fund in one of three ways:
As per the requirement in RBC25.8(5), net long equity investments in a given fund in which the bank cannot look through or does not meet the requirements of RBC25.8(5) for the fund must be assigned to the banking book. Net short positions in funds, where the bank cannot look through or does not meet the requirements of RBC25.8(5), must be excluded from any trading book capital requirements under the market risk framework, with the net position instead subjected to a 100% capital requirement.
In the vega risk context:
Each currency is a separate delta GIRR bucket, so all risk factors in risk-free yield curves for the same currency in which interest rate-sensitive instruments are denominated are grouped into the same bucket.
For calculating weighted sensitivities, the risk weights for each tenor in risk-free yield curves are set in Table 1 as follows:
|
Delta GIRR buckets and risk weights |
Table 1 |
|||||
|
Tenor |
0.25 year |
0.5 year |
1 year |
2 year |
3 year |
|
|
Risk weight |
1.7% |
1.7% |
1.6% |
1.3% |
1.2% |
|
|
Tenor |
5 year |
10 year |
15 year |
20 year |
30 year |
|
|
Risk weight (percentage points) |
1.1% |
1.1% |
1.1% |
1.1% |
1.1% |
|
The risk weight for the inflation risk factor and the cross-currency basis risk factors, respectively, is set at 1.6%.
For aggregating GIRR risk positions within a bucket, the correlation parameter between weighted sensitivities
and
within the same bucket (ie same currency), same assigned tenor, but different curves is set at 99.90%. In aggregating delta risk positions for cross-currency basis risk for onshore and offshore curves, which must be considered two different curves as set out in MAR21.8, a bank may choose to aggregate all cross-currency basis risk for a currency (ie “Curr/USD” or “Curr/EUR”) for both onshore and offshore curves by a simple sum of weighted sensitivities.
The delta risk correlation between weighted sensitivities
and
within the same bucket with different tenor and same curve is set in the following Table 213 :
| Delta GIRR correlations ( | Table 2
| ||||||||||
|
| 0.25 year | 0.5 year | 1 year | 2 year | 3 year | 5 year | 10 year | 15 year | 20 year | 30 year | |
| 0.25 year | 100.0% | 97.0% | 91.4% | 81.1% | 71.9% | 56.6% | 40.0% | 40.0% | 40.0% | 40.0% | |
| 0.5 year | 97.0% | 100.0% | 97.0% | 91.4% | 86.1% | 76.3% | 56.6% | 41.9% | 40.0% | 40.0% | |
| 1 year | 91.4% | 97.0% | 100.0% | 97.0% | 94.2% | 88.7% | 76.3% | 65.7% | 56.6% | 41.9% | |
| 2 year | 81.1% | 91.4% | 97.0% | 100.0% | 98.5% | 95.6% | 88.7% | 82.3% | 76.3% | 65.7% | |
| 3 year | 71.9% | 86.1% | 94.2% | 98.5% | 100.0% | 98.0% | 93.2% | 88.7% | 84.4% | 76.3% | |
| 5 year | 56.6% | 76.3% | 88.7% | 95.6% | 98.0% | 100.0% | 97.0% | 94.2% | 91.4% | 86.1% | |
| 10 year | 40.0% | 56.6% | 76.3% | 88.7% | 93.2% | 97.0% | 100.0% | 98.5% | 97.0% | 94.2% | |
| 15 year | 40.0% | 41.9% | 65.7% | 82.3% | 88.7% | 94.2% | 98.5% | 100.0% | 99.0% | 97.0% | |
| 20 year | 40.0% | 40.0% | 56.6% | 76.3% | 84.4% | 91.4% | 97.0% | 99.0% | 100.0% | 98.5% | |
| 30 year | 40.0% | 40.0% | 41.9% | 65.7% | 76.3% | 86.1% | 94.2% | 97.0% | 98.5% | 100.0% | |
| 13 | The delta GIRR correlation parameters ( ) set out in Table 2 is determined by , where Tk (respectively Tl) is the tenor that relates to (respectively ); and is set at 3%. For example, the correlation between a sensitivity to the one-year tenor of the Eonia swap curve and the a sensitivity to the five-year tenor of the Eonia swap curve in the same currency is . |
Between two weighted sensitivities and
within the same bucket with different tenor and different curves, the correlation
is equal to the correlation parameter specified in MAR21.46 multiplied by 99.90%.14
| 14 | For example, the correlation between a sensitivity to the one-year tenor of the Eonia swap curve and a sensitivity to the five-year tenor of the three-month Euribor swap curve in the same currency is . |
| FAQ1 | What should the correlation between two inflation curves in the same currency (eg German vs French, in Euro) be for GIRR? Per MAR21.47, a 99.90% correlation should apply to different inflation curves in the same currency. |
The delta risk correlation between a weighted sensitivity
to the inflation curve and a weighted sensitivity
to a given tenor of the relevant yield curve is 40%.
The delta risk correlation between a weighted sensitivity
to a cross-currency basis curve and a weighted sensitivity
to each of the following curves is 0%:
For aggregating GIRR risk positions across different buckets (ie different currencies), the parameter is set at 50%.
For delta CSR non-securitisations, buckets are set along two dimensions - credit quality and sector - as set out in Table 3. The CSR non-securitisation sensitivities or risk exposures should first be assigned to a bucket defined before calculating weighted sensitivities by applying a risk weight.
|
Buckets for delta CSR non-securitisations |
Table 3 |
||
|
Bucket number |
Credit quality |
Sector |
|
|
1 |
Investment grade (IG) |
Sovereigns including central banks, multilateral development banks |
|
|
2 |
Local government, government-backed non-financials, education, public administration |
||
|
3 |
Financials including government-backed financials |
||
|
4 |
Basic materials, energy, industrials, agriculture, manufacturing, mining and quarrying |
||
|
5 |
Consumer goods and services, transportation and storage, administrative and support service activities |
||
|
6 |
Technology, telecommunications |
||
|
7 |
Health care, utilities, professional and technical activities |
||
|
8 |
Covered bonds15 |
||
|
9 |
High yield (HY) & non-rated (NR) |
Sovereigns including central banks, multilateral development banks |
|
|
10 |
Local government, government-backed non-financials, education, public administration |
||
|
11 |
Financials including government-backed financials |
||
|
12 |
Basic materials, energy, industrials, agriculture, manufacturing, mining and quarrying |
||
|
13 |
Consumer goods and services, transportation and storage, administrative and support service activities |
||
|
14 |
Technology, telecommunications |
||
|
15 |
Health care, utilities, professional and technical activities |
||
|
16 |
Other sector16 |
||
|
17 |
IG indices |
||
|
18 |
HY indices |
||
| 15 | Covered bonds must meet the definition provided in LEX30.37, LEX30.39 and LEX30.40. |
| 16 | Credit quality is not a differentiating consideration for this bucket. |
| FAQ1 | How are risk weights to be determined when external ratings assigned by credit rating agencies differ and when there are no external ratings available? Consistent with the treatment of external ratings under the standardised approach to credit risk (see CRE21.10 and CRE21.11), if there are two ratings which map into different risk weights, the higher risk weight should be applied. If there are three or more ratings with different risk weights, the ratings corresponding to the two lowest risk weights should be referred to and the higher of those two risk weights will be applied. Consistent with the treatment where there are no external ratings under the CVA risk chapter (see MAR50.16), where there are no external ratings or where external ratings are not recognised within a jurisdiction, banks may, subject to supervisory approval: for the purpose of assigning delta CSR non-securitisation risk weights, map the internal rating to an external rating, and assign a risk weight corresponding to either “investment grade” or “high yield” in MAR21.51; for the purpose of assigning default risk weights under the DRC requirement, map the internal rating to an external rating, and assign a risk weight corresponding to one of the seven external ratings in the table included MAR22.24; or apply the risk weights specified in MAR21.51 and MAR22.24 for unrated/non-rated categories. |
| FAQ2 | For the purpose of market risk capital requirements, what are the CSR capital requirements for Fannie Mae and Freddie Mac mortgage-backed security (MBS) bonds? What is the loss-given-default (LGD) for Fannie and Freddie MBS? Non-tranched MBS issued by government sponsored-entities (GSEs), such as Fannie and Freddie, are assigned to bucket 2 (local government, government-backed non-financials, education, public administration) for CSR with a risk weight of 1.0%. In accordance with MAR22.12, the LGD for non-tranched MBS issued by GSEs is 75% (ie the LGD assigned to senior debt instruments) unless the GSE security satisfies the requirements of footnote 15 to MAR21.51 for treatment of the security as a covered bond. |
To assign a risk exposure to a sector, banks must rely on a classification that is commonly used in the market for grouping issuers by industry sector.
For calculating weighted sensitivities, the risk weights for buckets 1 to 18 are set out in Table 4. Risk weights are the same for all tenors (ie 0.5 years, 1 year, 3 years, 5 years, 10 years) within each bucket:
|
Risk weights for buckets for delta CSR non-securitisations |
Table 4 |
|
|
Bucket number |
Risk weight |
|
|
1 |
0.5% |
|
|
2 |
1.0% |
|
|
3 |
5.0% |
|
|
4 |
3.0% |
|
|
5 |
3.0% |
|
|
6 |
2.0% |
|
|
7 |
1.5% |
|
|
8 |
2.5%17 |
|
|
9 |
2.0% |
|
|
10 |
4.0% |
|
|
11 |
12.0% |
|
|
12 |
7.0% |
|
|
13 |
8.5% |
|
|
14 |
5.5% |
|
|
15 |
5.0% |
|
|
16 |
12.0% |
|
|
17 |
1.5% |
|
|
18 |
5.0% |
|
| 17 | For covered bonds that are rated AA- or higher, the applicable risk weight may at the discretion of the bank be 1.5%. |
For buckets 1 to 15, for aggregating delta CSR non-securitisations risk positions within a bucket, the correlation parameter between two weighted sensitivities
and
within the same bucket, is set as follows, where:18
| 18 | For example, a sensitivity to the five-year Apple bond curve and a sensitivity to the 10-year Google CDS curve would be: . |
| FAQ1 | MAR21.9(3) explicitly states that, for CSR curvature, the bond-CDS basis is ignored. Is it correct that, under MAR21.9(1), bond and CDS curves are considered distinct risk factors and the only “basis” taken into account in in MAR21.54 and MAR21.55 is the bond-CDS basis? Yes. Bond and CDS credit spreads are considered distinct risk factors under MAR21.9(1), and referenced in MAR21.54 and MAR21.55 is meant to capture only the bond-CDS basis. |
For buckets 17 and 18, for aggregating delta CSR non-securitisations risk positions within a bucket, the correlation parameter between two weighted sensitivities
and
within the same bucket is set as follows, where:
The correlations above do not apply to the other sector bucket (ie bucket 16).
For aggregating delta CSR non-securitisation risk positions across buckets 1 to 18, the correlation parameter is set as follows, where:
|
Values of |
Table 5 |
||||||||||
|
Bucket |
1 / 9 |
2 / 10 |
3 / 11 |
4 / 12 |
5 / 13 |
6 / 14 |
7 / 15 |
8 |
16 |
17 |
18 |
|
1 / 9 |
75% |
10% |
20% |
25% |
20% |
15% |
10% |
0% |
45% |
45% |
|
|
2 / 10 |
5% |
15% |
20% |
15% |
10% |
10% |
0% |
45% |
45% |
||
|
3 / 11 |
5% |
15% |
20% |
5% |
20% |
0% |
45% |
45% |
|||
|
4 / 12 |
20% |
25% |
5% |
5% |
0% |
45% |
45% |
||||
|
5 / 13 |
25% |
5% |
15% |
0% |
45% |
45% |
|||||
|
6 / 14 |
5% |
20% |
0% |
45% |
45% |
||||||
|
7 / 15 |
5% |
0% |
45% |
45% |
|||||||
|
8 |
0% |
45% |
45% |
||||||||
|
16 |
0% |
0% |
|||||||||
|
17 |
75% |
||||||||||
|
18 |
|||||||||||
Sensitivities to CSR arising from the CTP and its hedges are treated as a separate risk class as set out in MAR21.1. The buckets, risk weights and correlations for the CSR securitisations (CTP) apply as follows:
| FAQ1 | In accordance with MAR21.58(1), sensitivities to credit spread risk (CSR) arising from the correlation trading portfolio (CTP) should be classified according to the same bucket structure as the one for CSR non-securitisation, as set out in MAR21.51, except for index buckets (bucket 17 and bucket 18). Since an index CTP should be considered a risk factor as a whole and cannot be broken down into its constituents, as stated in MAR21.34(2), how should a bank determine which bucket to assign the delta sensitivity of an index CTP instrument, given the aforementioned bucket structure? The delta CSR sensitivity of an index CTP instrument should be assigned to a single specific delta sector bucket consistent with the characteristics of, at least, 75% of the index constituents (taking into account the weightings of that index), in accordance with MAR21.33(1). If this is not possible, then the index should be assigned to bucket 16, “Other sector”. The sensitivity to that index CTP instrument should be considered and treated like any other single-name sensitivity assigned to that same sector bucket. |
For calculating weighted sensitivities, the risk weights for buckets 1 to 16 are set out in Table 6. Risk weights are the same for all tenors (ie 0.5 years, 1 year, 3 years, 5 years, 10 years) within each bucket:
| Risk weights for sensitivities to CSR arising from the CTP | Table 6 | |
| Bucket number | Risk weight | |
| 1 | 4.0% | |
| 2 | 4.0% | |
| 3 | 8.0% | |
| 4 | 5.0% | |
| 5 | 4.0% | |
| 6 | 3.0% | |
| 7 | 2.0% | |
| 8 | 6.0% | |
| 9 | 13.0% | |
| 10 | 13.0% | |
| 11 | 16.0% | |
| 12 | 10.0% | |
| 13 | 12.0% | |
| 14 | 12.0% | |
| 15 | 12.0% | |
| 16 | 13.0% | |
For aggregating delta CSR securitisations (CTP) risk positions across buckets, the correlation parameters for are identical to CSR non-securitisation as set out in MAR21.57.
For delta CSR securitisations not in the CTP, buckets are set along two dimensions – credit quality and sector – as set out in Table 7. The delta CSR securitisation (non-CTP) sensitivities or risk exposures must first be assigned to a bucket before calculating weighted sensitivities by applying a risk weight.
| Buckets for delta CSR securitisations (non-CTP) | Table 7 | ||
| Bucket number | Credit quality | Sector | |
| 1 | Senior investment grade (IG) | RMBS – Prime | |
| 2 | RMBS – Mid-prime | ||
| 3 | RMBS – Sub-prime | ||
| 4 | CMBS | ||
| 5 | Asset-backed securities (ABS) – Student loans | ||
| 6 | ABS – Credit cards | ||
| 7 | ABS – Auto | ||
| 8 | Collateralised loan obligation (CLO) non-CTP | ||
| 9 | Non-senior IG | RMBS – Prime | |
| 10 | RMBS – Mid-prime | ||
| 11 | RMBS – Sub-prime | ||
| 12 | Commercial mortgage-backed securities (CMBS) | ||
| 13 | ABS – Student loans | ||
| 14 | ABS – Credit cards | ||
| 15 | ABS – Auto | ||
| 16 | CLO non-CTP | ||
| 17 | High yield & non-rated | RMBS – Prime | |
| 18 | RMBS – Mid-prime | ||
| 19 | RMBS – Sub-prime | ||
| 20 | CMBS | ||
| 21 | ABS – Student loans | ||
| 22 | ABS – Credit cards | ||
| 23 | ABS – Auto | ||
| 24 | CLO non-CTP | ||
| 25 | Other sector19 | ||
| 19 | Credit quality is not a differentiating consideration for this bucket. |
To assign a risk exposure to a sector, banks must rely on a classification that is commonly used in the market for grouping tranches by type.
For calculating weighted sensitivities, the risk weights for buckets 1 to 8 (senior IG) are set out in Table 8:
| Risk weights for buckets 1 to 8 for delta CSR securitisations (non-CTP) | Table 8 | |
| Bucket number | Risk weight (in percentage points) | |
| 1 | 0.9% | |
| 2 | 1.5% | |
| 3 | 2.0% | |
| 4 | 2.0% | |
| 5 | 0.8% | |
| 6 | 1.2% | |
| 7 | 1.2% | |
| 8 | 1.4% | |
The risk weights for buckets 9 to 16 (non-senior investment grade) are then equal to the corresponding risk weights for buckets 1 to 8 scaled up by a multiplication by 1.25. For instance, the risk weight for bucket 9 is equal to .
The risk weights for buckets 17 to 24 (high yield and non-rated) are then equal to the corresponding risk weights for buckets 1 to 8 scaled up by a multiplication by 1.75. For instance, the risk weight for bucket 17 is equal to .
The risk weight for bucket 25 is set at 3.5%.
For aggregating delta CSR securitisations (non-CTP) risk positions within a bucket, the correlation parameter between two sensitivities
and
within the same bucket, is set as follows, where:
| FAQ1 | MAR21.68 includes , which equals 1 where the two sensitivities within the same bucket are related to the same securitisation tranche, or 40% otherwise. There is no issuer factor. Does this mean that two sensitivities relating to the same issuer but different tranches require 40% correlation? Yes. There is no granularity for issuers in the delta CSR securitisation part as set out in MAR21.10. Where two tranches have exactly the same issuer, same tenor and same basis, but different tranches (ie different credit quality), the correlation must be 40%. |
The correlations above do not apply to the other sector bucket (ie bucket 25).
For aggregating delta CSR securitisations (non-CTP) risk positions across buckets 1 to 24, the correlation parameter is set as 0%.
For aggregating delta CSR securitisations (non-CTP) risk positions between the other sector bucket (ie bucket 25) and buckets 1 to 24, (i) the capital requirements for bucket 25 and (ii) the aggregated capital requirements for buckets 1 to 24 will be simply summed up to the overall risk class level capital requirements. There should be no diversification or hedging effects recognised in aggregating the capital requirements for the other sector bucket (ie bucket 25) with those for buckets 1 to 24.
For delta equity risk, buckets are set along three dimensions – market capitalisation, economy and sector – as set out in Table 9. The equity risk sensitivities or exposures must first be assigned to a bucket before calculating weighted sensitivities by applying a risk weight.
| Buckets for delta sensitivities to equity risk | Table 9 | |||
| Bucket number | Market cap | Economy | Sector | |
| 1 | Large | Emerging market economy | Consumer goods and services, transportation and storage, administrative and support service activities, healthcare, utilities | |
| 2 | Telecommunications, industrials | |||
| 3 | Basic materials, energy, agriculture, manufacturing, mining and quarrying | |||
| 4 | Financials including government-backed financials, real estate activities, technology | |||
| 5 | Advanced economy | Consumer goods and services, transportation and storage, administrative and support service activities, healthcare, utilities | ||
| 6 | Telecommunications, industrials | |||
| 7 | Basic materials, energy, agriculture, manufacturing, mining and quarrying | |||
| 8 | Financials including government-backed financials, real estate activities, technology | |||
| 9 | Small | Emerging market economy | All sectors described under bucket numbers 1, 2, 3 and 4 | |
| 10 | Advanced economy | All sectors described under bucket numbers 5, 6, 7 and 8 | ||
| 11 | Other sector20 | |||
| 12 | Large market cap, advanced economy equity indices (non-sector specific) | |||
| 13 | Other equity indices (non-sector specific) | |||
| 20 | Market capitalisation or economy (ie advanced or emerging market) is not a differentiating consideration for this bucket. |
Market capitalisation (market cap) is defined as the sum of the market capitalisations based on the market value of the total outstanding shares issued by the same listed legal entity or a group of legal entities across all stock markets globally, where the total outstanding shares issued by the group of legal entities refer to cases where the listed entity is a parent company of a group of legal entities. Under no circumstances should the sum of the market capitalisations of multiple related listed entities be used to determine whether a listed entity is “large market cap” or “small market cap”.
Large market cap is defined as a market capitalisation equal to or greater than USD 2 billion and small market cap is defined as a market capitalisation of less than USD 2 billion.
The advanced economies are Canada, the United States, Mexico, the euro area, the non-euro area western European countries (the United Kingdom, Norway, Sweden, Denmark and Switzerland), Japan, Oceania (Australia and New Zealand), Singapore and Hong Kong SAR.
FAQ1| FAQ1 | Are the countries referenced in MAR21.75 to be understood as country of incorporation? An equity issuer must be allocated to a particular bucket according to the most material country or region in which the issuer operates. As stated in MAR21.76: “For multinational multi-sector equity issuers, the allocation to a particular bucket must be done according to the most material region and sector in which the issuer operates. |
To assign a risk exposure to a sector, banks must rely on a classification that is commonly used in the market for grouping issuers by industry sector.
For calculating weighted sensitivities, the risk weights for the sensitivities to each of equity spot price and equity repo rates for buckets 1 to 13 are set out in Table 10:
| Risk weights for buckets 1 to 13 for sensitivities to equity risk | Table 10 | ||
| Bucket number | Risk weight for equity spot price | Risk weight for equity repo rate
| |
| 1 | 55% | 0.55% | |
| 2 | 60% | 0.60% | |
| 3 | 45% | 0.45% | |
| 4 | 55% | 0.55% | |
| 5 | 30% | 0.30% | |
| 6 | 35% | 0.35% | |
| 7 | 40% | 0.40% | |
| 8 | 50% | 0.50% | |
| 9 | 70% | 0.70% | |
| 10 | 50% | 0.50% | |
| 11 | 70% | 0.70% | |
| 12 | 15% | 0.15% | |
| 13 | 25% | 0.25% | |
For aggregating delta equity risk positions within a bucket, the correlation parameter between two sensitivities
and
within the same bucket is set at as follows
The correlations set out above do not apply to the other sector bucket (ie bucket 11).
For aggregating delta equity risk positions across buckets 1 to 13, the correlation parameter is set at:
For delta commodity risk, 11 buckets that group commodities by common characteristics are set out in Table 11.
For calculating weighted sensitivities, the risk weights for each bucket are set out in Table 11:
| Delta commodity buckets and risk weights | Table 11 | |||
| Bucket number | Commodity bucket | Examples of commodities allocated to each commodity bucket (non-exhaustive) | Risk weight | |
| 1 | Energy - solid combustibles | Coal, charcoal, wood pellets , uranium | 30% | |
| 2 | Energy - liquid combustibles | Light-sweet crude oil; heavy crude oil; West Texas Intermediate (WTI) crude; Brent crude; etc (ie various types of crude oil) Bioethanol; biodiesel ; etc (ie various biofuels) Propane; ethane; gasoline; methanol; butane; etc (ie various petrochemicals) Jet fuel; kerosene; gasoil; fuel oil; naphtha; heating oil; diesel etc (ie various refined fuels) | 35% | |
| 3 | Energy - electricity and carbon trading | Spot electricity; day-ahead electricity; peak electricity; off-peak electricity (ie various electricity types) Certified emissions reductions; in-delivery month EU allowance; Regional Greenhouse Gas Initiative CO2 allowance; renewable energy certificates; etc (ie various carbon trading emissions) | 60% | |
| 4 | Freight | Capesize; Panamax; Handysize; Supramax (ie various types of dry-bulk route) Suezmax; Aframax; very large crude carriers (ie various liquid-bulk/gas shipping route) | 80% | |
| 5 | Metals – non-precious | Aluminium; copper; lead; nickel; tin; zinc (ie various base metals) Steel billet ; steel wire; steel coil ; steel scrap; steel rebar; iron ore; tungsten; vanadium; titanium; tantalum (ie steel raw materials) Cobalt; manganese; molybdenum (ie various minor metals) | 40% | |
| 6 | Gaseous combustibles | Natural gas; liquefied natural gas | 45% | |
| 7 | Precious metals (including gold) | Gold; silver; platinum; palladium | 20% | |
| 8 | Grains and oilseed | Corn; wheat; soybean seed; soybean oil; soybean meal; oats; palm oil; canola; barley; rapeseed seed; rapeseed oil; rapeseed meal; red bean; sorghum; coconut oil; olive oil; peanut oil; sunflower oil; rice | 35% | |
| 9 | Livestock and dairy | Live cattle; feeder cattle; hog; poultry; lamb; fish; shrimp; milk; whey; eggs; butter; cheese | 25% | |
| 10 | Softs and other agriculturals | Cocoa; arabica coffee; robusta coffee; tea; citrus juice; orange juice; potatoes; sugar; cotton; wool; lumber; pulp; rubber | 35% | |
| 11 | Other commodity | Potash; fertilizer; phosphate rocks (ie various industrial materials) Rare earths; terephthalic acid; flat glass | 50% | |
For the purpose of aggregating commodity risk positions within a bucket using a correlation parameter, the correlation parameter between two sensitivities
and
within the same bucket, is set as follows, where:21
|
Values of |
Table 12 |
||
|
Bucket number |
Commodity bucket |
Correlation ( |
|
|
1 |
Energy - Solid combustibles |
55% |
|
|
2 |
Energy - Liquid combustibles |
95% |
|
|
3 |
Energy - Electricity and carbon trading |
40% |
|
|
4 |
Freight |
80% |
|
|
5 |
Metals - non-precious |
60% |
|
|
6 |
Gaseous combustibles |
65% |
|
|
7 |
Precious metals (including gold) |
55% |
|
|
8 |
Grains and oilseed |
45% |
|
|
9 |
Livestock and dairy |
15% |
|
|
10 |
Softs and other agriculturals |
40% |
|
|
11 |
Other commodity |
15% |
|
| 21 | For example, the correlation between the sensitivity to Brent, one-year tenor, for delivery in Le Havre and the sensitivity to WTI, five-year tenor, for delivery in Oklahoma is . |
| FAQ1 | For instruments with commodity spreads as underlying, are the spreads considered a risk factor, or does the instrument have to be decomposed? For example, if there is a swap on the spread between WTI and Brent, will delta on the spread be reported, or will delta of WTI and delta of Brent be reported individually? Instruments with a spread as their underlying are considered sensitive to different risk factors. In the example cited, the swap will be sensitive to both WTI and Brent, each of which require a capital charge at the risk factor level (ie delta of WTI and delta of Brent). The correlation to aggregate capital charges is specified in MAR21.83. |
For determining whether the commodity correlation parameter ( ) as set out in Table 12 in MAR21.83(1)(a) should apply, this paragraph provides non-exhaustive examples of further definitions of distinct commodities as follows:
| FAQ1 | For instruments with commodity spreads as underlying, are the spreads considered a risk factor, or does the instrument have to be decomposed? For example, if there is a swap on the spread between WTI and Brent, will delta on the spread be reported, or will delta of WTI and delta of Brent be reported individually? Instruments with a spread as their underlying are considered sensitive to different risk factors. In the example cited, the swap will be sensitive to both WTI and Brent, each of which require a capital charge at the risk factor level (ie delta of WTI and delta of Brent). The correlation to aggregate capital charges is specified in MAR21.83. |
For aggregating delta commodity risk positions across buckets, the correlation parameter is set as follows:
An FX risk bucket is set for each exchange rate between the currency in which an instrument is denominated and the reporting currency.
A unique relative risk weight equal to 15% applies to all the FX sensitivities.
For the specified currency pairs by the Basel Committee,22 and for currency pairs forming first-order crosses across these specified currency pairs,23 the above risk weight may at the discretion of the bank be divided by the square root of 2.
| 22 | Specified currency pairs by the Basel Committee are: USD/EUR, USD/JPY, USD/GBP, USD/AUD, USD/CAD, USD/CHF, USD/MXN, USD/CNY, USD/NZD, USD/RUB, USD/HKD, USD/SGD, USD/TRY, USD/KRW, USD/SEK, USD/ZAR, USD/INR, USD/NOK, USD/BRL. |
| 23 | For example, EUR/AUD is not among the selected currency pairs specified by the Basel Committee, but is a first-order cross of USD/EUR and USD/AUD. |
For aggregating delta FX risk positions across buckets, the correlation parameter is uniformly set to 60%.
The same bucket definitions for each risk class are used for vega risk as for delta risk.
For calculating weighted sensitivities for vega risk, the risk of market illiquidity is incorporated into the determination of vega risk, by assigning different liquidity horizons for each risk class as set out in Table 13. The risk weight for each risk class24 is also set out in Table 13.
|
Regulatory liquidity horizon, |
Table 13 |
||
|
Risk class |
|
Risk weights |
|
|
GIRR |
60 |
100% |
|
|
CSR non-securitisations |
120 |
100% |
|
|
CSR securitisations (CTP) |
120 |
100% |
|
|
CSR securitisations (non-CTP) |
120 |
100% |
|
|
Equity (large cap and indices) |
20 |
77.78% |
|
|
Equity (small cap and other sector) |
60 |
100% |
|
|
Commodity |
120 |
100% |
|
|
FX |
40 |
100% |
|
| 24 | The risk weight for a given vega risk factor k is determined by ,where is set at 55%; and is specified per risk class in Table 13. |
| FAQ1 | When applying risk weights for equity vega risk factors, does the 20 days liquidity horizon apply to equities that are both large market cap and indices, or does it apply to equities that are either large market cap or indices? Similarly, does the 60 days liquidity horizon apply to equities that are both small market cap and other sector, or does it apply to equities that are either small market cap or other sector? The 20-day liquidity horizon applies to vega risk factors that would be allocated to large market cap buckets (ie buckets 1 to 8) or to index buckets (ie buckets 12 and 13) as set out in MAR21.72. The 60-day liquidity horizon applies to vega risk factors that would be allocated to small market cap buckets (ie buckets 9 and 10) or to the other sector bucket (ie bucket 11) as set out in MAR21.72. |
For aggregating vega GIRR risk positions within a bucket, the correlation parameter is set as follows, where:
For aggregating vega risk positions within a bucket of the other risk classes (ie non-GIRR), the correlation parameter is set as follows, where:
| FAQ1 | MAR21.94 defines the vega correlation between risk factors k and l as the product of the option maturity correlation ( ) and the delta correlation ( ) that applies between the delta risk factors that correspond to vega risk factors k and l. Please clarify the meaning of “delta risk factors that correspond to vega risk factors k and l”. In particular, besides the option maturity, should banks consider for CSR and commodity risk (i) the correlation across vega risk factors for the dimensions defined for vega for a given risk class only, or (ii) all dimensions of delta risk factors? For CSR and commodity risks in MAR21.9 to MAR21.11 and MAR21.13, if the vega risk factors are defined for a smaller number of dimensions than are defined for delta risk factors, only the dimensions that are defined both as a vega risk factor dimension and as a delta risk factor dimension for the relevant risk class need to be considered as a correlation based on delta risk factors ( ) in the calculation of vega risk per MAR21.94. This means that the following dimensions are considered: for CSR non-securitisation risk: option maturity ( ) and underlying name ( ); for CSR securitisations (CTP) risk: option maturity ( ) and underlying name ( ); for CSR securitisation (non-CTP): option maturity ( ) and securitisation tranche ( ); and for commodity risk: option maturity ( ) and commodity ( ). |
For aggregating vega risk positions across different buckets within a risk class (GIRR and non-GIRR), the same correlation parameters for , as specified for delta correlations for each risk class in MAR21.39 to MAR21.89 are to be used for the aggregation of vega risk (eg
= 50% is to be used for the aggregation of vega risk sensitivities across different GIRR buckets).
For calculating the net curvature risk capital requirement for risk factor k for FX and equity risk classes, the curvature risk weight, which is the size of a shock to the given risk factor, is a relative shift equal to the respective delta risk weight. For FX curvature, for options that do not reference a bank’s reporting currency (or base currency as set out in MAR21.14(b)) as an underlying, net curvature risk charges (
and
) may be divided by a scalar of 1.5. Alternatively, and subject to supervisory approval, a bank may apply the scalar of 1.5 consistently to all FX instruments provided curvature sensitivities are calculated for all currencies, including sensitivities determined by shocking the reporting currency (or base currency where used) relative to all other currencies.
For calculating the net curvature risk capital requirement for curvature risk factor k for GIRR, CSR and commodity risk classes, the curvature risk weight is the parallel shift of all the tenors for each curve based on the highest prescribed delta risk weight for each bucket. For example, in the case of GIRR for a given currency (ie bucket), the risk weight assigned to 0.25-year tenor (ie the most punitive tenor risk weight) is applied to all the tenors simultaneously for each risk-free yield curve (consistent with a "translation", or "parallel shift" risk calculation).
| FAQ1 | In relation to the curvature risk capital requirement for the commodity risk class, MAR21.99 requires that the curvature risk weight is the parallel shift of all the tenors for each curve based on the highest prescribed delta risk weight for each bucket. A parallel shift in MAR21.99 implies that an additive shock (in absolute terms) is applied along the curve. However, MAR21.23 states that the shock applied to delta commodity is a relative shock. How should the shock be applied to commodity curvature? The sizes of upward and downward shocks applied to assess the net curvature risk capital requirement for a specific commodity´s curvature risk factor should be based on the risk weight connected to the curvature bucket where that commodity is classified, in accordance with MAR21.97 and MAR21.82. The same relative shocks should be applied to all curvature risk factors classified under the same bucket, defined along the dimension of the constructed curve (ie no term structure decomposition) per each commodity spot price, as described in MAR21.13(3). For example, the constructed curve for gold (with a risk weight of 20%) would be shifted up by multiplying each tenor price by 1.2 and down by multiplying each tenor price by 0.8. |
For aggregating curvature risk positions within a bucket, the curvature risk correlations are determined by squaring the corresponding delta correlation parameters
. In a case where a curvature risk factor is defined differently than the corresponding delta risk factor for a given risk class (ie for CSR non-securitisations, CSR securitisations (CTP), CSR securitisations (non-CTP) and commodities as defined in MAR21.9 to MAR21.13), banks do not need to consider this delta risk factor dimension. For example, for CSR non-securitisations and CSR securitisations (CTP), consistent with MAR21.9 which defines a bucket along one dimension (ie the relevant credit spread curve), the correlation parameter
as defined in MAR21.54 and MAR21.55 is not applicable to the curvature risk capital requirement calculation. Thus, the correlation parameter is determined by whether the two names of weighted sensitivities are the same. In the formula in MAR21.54 and MAR21.55, the correlation parameters
and
need not apply and only correlation parameter
applies between two weighted sensitivities within the same bucket. This correlation parameter should be squared. In applying the high and low correlations scenario set out in MAR21.6, the curvature risk capital requirements are calculated by applying the curvature correlation parameters
determined in this paragraph.
For aggregating curvature risk positions across buckets, the curvature risk correlations are determined by squaring the corresponding delta correlation parameters
. For instance, when aggregating
and
for the GIRR, the correlation should be
. In applying the high and low correlations scenario set out in MAR21.6, the curvature risk capital requirements are calculated by applying the curvature correlation parameters
, (ie the square of the corresponding delta correlation parameter).
This standard describes the scope of application of the Basel Framework.
This standard describes the criteria that bank capital instruments must meet to be eligible to satisfy the Basel capital requirements, as well as necessary regulatory adjustments and transitional arrangements.
This standard describes the framework for risk-based capital requirements.
This standard describes how to calculate capital requirements for credit risk.
This standard describes how to calculate capital requirements for market risk and credit valuation adjustment risk.
This standard describes how to calculate capital requirements for operational risk.
This standard describes the simple, transparent, non-risk-based leverage ratio. This measure intends to restrict the build-up of leverage in the banking sector and reinforce the risk-based requirements with a simple, non-risk-based "backstop" measure.
This standard describes the Liquidity Coverage Ratio, a measure which promotes the short-term resilience of a bank's liquidity risk profile.
The net stable funding ratio requires banks to maintain a stable funding profile in relation to the composition of their assets and off-balance-sheet activities.
Large exposures regulation limits the maximum loss that a bank could face in the event of a sudden counterparty failure to a level that does not endanger the bank's solvency. This standard requires banks to measure their exposures to a single counterparty or a group of connected counterparties and limit the size of large exposures in relation to their capital.
This standard establishes minimum standards for margin requirements for non-centrally cleared derivatives. Such requirements reduce systemic risk with respect to non-standardised derivatives by reducing contagion and spillover risks and promoting central clearing.
The Pillar 2 supervisory review process ensures that banks have adequate capital and liquidity to support all the risks in their business, especially with respect to risks not fully captured by the Pillar 1 process, and encourages good risk management.
This standard sets out disclosure requirements, which aim to encourage market discipline.
The Basel Core Principles provide a comprehensive standard for establishing a sound foundation for the regulation, supervision, governance and risk management of the banking sector.