ARMS Market Risk extends support for IMA-FRTB, SA-FRTB, and DRC
To finalize a production version of ARMS for the new FRTB capital requirements calculation, a number of core technology components have been developed at the heart of the ARMS platform. Using the new infrastructure, high-performance risk calculations can be done using the standard ARMS risk platform without large upgrade and configuration projects.
A new portfolio-tree controller with multiple selection capabilities down to position-level including search and filtering will be launched. For effective day-to-day operations an advanced portfolio pre-selection filter can be applied. Users can select and de-select positions and portfolios for viewing risk on ad-hoc groups of positions such as trading strategies or single position analysis.
Multiple market data contexts attached to a single set-up of positions. Example use; highly granular risk factor representation for pricing accuracy for IMA-FRTB PnL attribution, stylized risk factor representation for fast intra-day risk calculations, and coarse regulatory risk factor representation for EBA and SA-FRTB scenario use. Switching between risk factor contexts can be done at run time without reloading or remapping positions. Results using multiple contexts can be run in parallel, server side, for maximum performance of large position sets as usual.
Inclusion of basket calculation support, as index positions individually or as a group, can be broken down into basket constituents when looking at stress tests, value-at-risk, expected shortfall, greeks and sensitivities. In particular, FRTB requirements requiring look-through down to issuer level for all index related positions can now easily be handled even though the constituents do not have risk factor time-series.
Proxy risk factors, curves, and surfaces are a novel way of mapping positions to risk factor names that have no usable risk series. This gives control in risk factor break-downs in combination with missing market data. The proxy feature can also be used together with the basket definition to proxy missing constituent market data.
In relation to proxy risk factors, ghost maturity nodes and ghost moneyness nodes can be used to programmatically control which maturities on a curve that should generate sensitivities, regardless of the actual curve composition. Example use could be to comply with SA-FRTB and EBA sensitivity measures requiring a pre-defined set of maturity nodes for all interest rate curves and corporate spread curves without the hassle of physically defining such a grid structure in the database.