Response to consultation Paper on draft RTS on criteria for assessing risk factors modellability under the IMA
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Since it can be assumed that a significant amount of information would be required of them,
it must be ensured that the requirements can be fulfilled with reasonable efforts by them.
Otherwise the information needed for the model would not be available or be very expensive.
surfaces (Interest rates, Equity and FX volatilities) as e.g. SABR model, SVI model.
However although pricing is based on the parametric representation, these parameters are
not risk factors. The risk factors are still the volatility quotations themselves (which are shifted
in each scenario and afterwards new SABR parameters are derived in the scenario
calculation).
both options have significant practical limitations.
view.
Option 2 can be based on all input factors – including non-modellable – a parametric model
is to deliver calibration parameters as well as output risk factors. On this output level the
exclusion of risk factors from non modellable buckets would take place. In case where pricing
functions are setup on model parameters it would require to establish new pricing functions
(e.g. SVI). In cases where the pricing functions is setup to use the output risk factors we see
open questions with respect to use of a non modellable basis in contrast to a full exclusion of
the bucket.
own tracking routines of original maturities vs. actual maturities. Notwithstanding, we are in
favor of any possibility which helps to improve the diminishing demand for bonds with
remaining short term maturities 0-1,5years (which were often highly liquid when issued at
e.g. 5Y original maturity).
problems.
available shortly following the close of trading. Vendor service data will most likely not be
available during this time but only later with a considerable time delay.
Q5. Do you see any problems with requiring that institutions are allowed to use data from external data providers as input to the modellability assessment only where the external data providers are regularly subject to an independent audit (independent of whether the price is shared with the institution or not)? If so, please describe them thoroughly (i.e. for which data providers and the reasons for it).
Yes, potentially. The question must therefore also be discussed with the data providers.Since it can be assumed that a significant amount of information would be required of them,
it must be ensured that the requirements can be fulfilled with reasonable efforts by them.
Otherwise the information needed for the model would not be available or be very expensive.
Q6. Do you have any proposals on additional specifications that could be included in the legal text in order to ensure that verifiable prices provided by third-party vendors meet the requirements of this Regulation?
We have no additional proposals.Q7. How relevant are the provisions outlined above for your institution? How many and which curves, surfaces or cubes are (planned to be) represented by a mathematical function with function parameters chosen as risk factors in your (future) internal model?
This topic is of high relevance. We use parametric functions for all important volatilitysurfaces (Interest rates, Equity and FX volatilities) as e.g. SABR model, SVI model.
However although pricing is based on the parametric representation, these parameters are
not risk factors. The risk factors are still the volatility quotations themselves (which are shifted
in each scenario and afterwards new SABR parameters are derived in the scenario
calculation).
Q8. Do you have a preference for any of the options outlined above? For which reasons? Please motivate your response.
No do not have a strong preference for either. In fact, we share the opinion of ISDA/IIF thatboth options have significant practical limitations.
Q9. Do you consider any of the options outlined above as impossible or impractical? For which reasons? Please motivate your response.
If option 1 requires a historic recalibration it would not be possible from an operation point ofview.
Option 2 can be based on all input factors – including non-modellable – a parametric model
is to deliver calibration parameters as well as output risk factors. On this output level the
exclusion of risk factors from non modellable buckets would take place. In case where pricing
functions are setup on model parameters it would require to establish new pricing functions
(e.g. SVI). In cases where the pricing functions is setup to use the output risk factors we see
open questions with respect to use of a non modellable basis in contrast to a full exclusion of
the bucket.
Q10. Do you have alternative proposals to define the consequence on the modellability of the parameters where some buckets of a curve, surface or cube are modellable whilst others are nonmodellable?
We support the ISDA/IIF proposal.Q11. Do you intend to apply paragraph 4? If so, for which risk factors will it be relevant? Do you expect any implementation issues related to it? Please explain expected issues thoroughly.
We intend to rely on the services of data providers to be established and avoid building upown tracking routines of original maturities vs. actual maturities. Notwithstanding, we are in
favor of any possibility which helps to improve the diminishing demand for bonds with
remaining short term maturities 0-1,5years (which were often highly liquid when issued at
e.g. 5Y original maturity).
Q12. Do you agree with the outlined methodology for the assessment of modellability of risk factors? If not, please explain why.
Since we will not have sufficient own trades, we will need to rely on data service provider.Q13. Do you expect any problems for the modellability assessment arising from the upcoming benchmark rate transition that could be addressed via this regulation? If so, please provide a thorough description and potential solutions if any
As soon as a liquid markets new reference rate is established, we do not expect additionalproblems.
Q14. How do you intend to integrate the risk factor modellability assessment (i.e. RFET) into the processes of your institution? Do you expect those data to be used for the purpose of the RFET only or do you think those data would increase the data availability used e.g. for the calibration of your internal model (under para 31.26 of 2019 Basel rules)? What percentage of data used for the RFET do you think will be used also for the calibration of your internal model?
We believe that the RFET is primarily a stand-alone test. Daily marked-to-market prices areavailable shortly following the close of trading. Vendor service data will most likely not be
available during this time but only later with a considerable time delay.