Vector Risk Ten thousand futures.
One number that matters.

A fully featured Historical or Monte Carlo VaR calculation. Specify attributions for VaR (breakdown by market segment), proxying of rates, confidence interval, and any risk roll-ups up to global VaR.

Run historical scenarios on groups of curves: together or separately, parallel or non-parallel shifts, absolute or relative, by industry sector or liquidity ranking. The same stresses are reused for market, credit and collateral calculations.

Ready for FRTB SA? Curve definitions carry the categorisations (credit quality, industry sector, market cap, economy and commodity bucket), and trades contribute automatically based on the risk factors they price against. Complete coverage is assured with a minimal set of sensitivity definitions.

For PFE we use real-world Monte Carlo parameterised from your historical data. See the effect of netting and collateral, track path-dependent events such as option knock-outs, and apply correlations and stochastic processes appropriate to the evolution of different market rates.

Vector Risk calculates xVA and sensitivities using full Monte Carlo simulation with risk-neutral curve evolution. Sensitivities are produced inside the Monte Carlo by running extra scenarios that shift each risk factor up and down. It’s an intensive calculation, made possible by our vectorised code.

CVA, DVA, bilateral CVA, FVA, FCA and FBA are all supported.

The Internal Model requires a large number of historic or Monte Carlo simulations: the stress period, the current period with full and constrained factors, all at five liquidity horizons. Vector Risk bundles all of these into a single task and applies the Basel formula across the expected-shortfall results to give regulatory capital.

Link your business-unit hierarchy to the internal method and the system runs the calculation at desk level and for the enterprise as a whole. Supporting analytics (VaR, backtesting and theoretical P&L) are supplied, as is a calibration calculation to identify the stress period in the history set.

ISDA developed the standardised margin methodology to reduce the potential for disputes and create efficiency through netting exposures. The model applies a sensitivity-based calculation across four product groups: interest rates and foreign exchange, credit, equity and commodities.

Vector Risk is a licensed ISDA SIMM provider, so the margin you compute is the margin your counterparties agree to.

The Standardised Approach for Counterparty Credit Risk (SA-CCR) is the capital-requirement framework under Basel III addressing counterparty risk for derivative trades.

SA-CCR calculates the exposure at default of derivatives and long-settlement transactions exposed to counterparty credit risk, feeding directly into your regulatory capital.

Examine the sources of change in your mark-to-market from one day to the next. Show P&L due to maturing trades, new trades, market movements (broken down further by risk type) and theta.

The same attribution engine feeds the FRTB PLA test, so your desk sign-off and your regulatory reporting draw on one consistent number.

IFRS 9 qualifies a hedging relationship on three criteria: an economic relationship between the hedged item and the hedging instrument, credit risk that does not dominate the resulting value changes, and a hedge ratio matching the quantities actually designated. All three are assessed prospectively — at inception and on an ongoing basis. Vector Risk evidences the economic relationship with regression analysis over a historical simulation of changes in both legs.

The standard prescribes no method and sets no threshold; IAS 39’s 80–125% bright line went with it. Ineffectiveness still has to be measured and taken to profit or loss, so the dollar-offset ratio is reported alongside the regression as the entity’s own measure — and stands as the retrospective test for books that have elected to carry on applying IAS 39 hedge accounting. Either way treasury and accounting get a defensible, auditable result.