MoCaX expands the capabilities of IMM Counterparty Credit Risk engines

The Monte Carlo simulation framework increases its product coverage and helps optimise Capital
See how to Increase IMM Coverage

Typical problem with Capital calculation: we have an IMM-approved diffusion model for interest rates. We want to calculate IMM-CCR capital on a Bermuda Swaption. The official pricer in our organisation for Bermudan Swaptions is a Monte Carlo pricer based in a 1-factor Hull-White (HW), which is different from the IMM-approved interest rate model.

In order to compute IMM capital on this trade we have to

  1. Diffuse the yield curves using the IMM-approved model for interest rates in our Monte Carlo engine
  2. In each scenario and time step (i) Calibrate the HW model to the diffused yield curve and (ii) price the Bermudan Swaption with the Monte Carlo pricer

… we have to run a yield curve calibration + Monte Carlo pricing in each node of the IMM Monte Carlo engine.

To our knowledge, nobody can do in a useful time frame due to its outstanding computational demand.



The APA method inside MoCaX compresses the Yield Curve calibration + the Monte Carlo pricing into one ultra-fast and ultra-accurate process.


Find more examples here.

See how you can Further Optimise Capital

Existing IMM Monte Carlo engines can calculate capital for vanilla trades; typically fairly standard IR swaps, European options, simple FX products, some times standard CDSs, etc.

What if you could run the current IMM calculations of those trades, say, 100 times faster?

MoCaX processed IR swaps can be 1,000x faster, European Swaptions 100x faster, simple FX products 1,000x faster, CDSs 1000x faster.

In that case you could do things that you cannot think of as present:

  • Stress-test and re-run the IMM calculation frequently
  • Increase the pre-trade analysis response time
  • Perform scenario analysis


MoCaX helps you optimise Capital.



Do you want to see examples?