The backbone of all UnRisk products are the UnRisk Engines, all programmed in C++.
Covers the calibration of models and the valuation of financial instruments. Highly advanced numerical schemes are used to provide fast and robust solutions. A critical step in the valuation process is the parameter identification for the models used for the simulation of the underlying risk factors, as the inverse problem may be ill-posed. Our algorithms targeting and solving these inverse problems have been developed together with some of the leading mathematicians in this fields. For the solution of the forward problem (valuation) UnRisk chooses among different methods including the solution of PDEs with Finite Difference/Finite Element schemes, the solution of SDEs with (Quasi-) Monte-Carlo methods as well as direct integration methods like Adaptive Integration and Fourier based techniques. The UnRisk Valuation Engine covers many models and a vast variety of deal types.
Covers parametric, historic and Monte Carlo Value at Risk calculations for a variety of risk factors. For a deeper understanding of the sources of risk, the VaR Engine allows the calculation of incremental, marginal and contribution VaR from single instruments up to the portfolio level. Besides the VaR other important key ratios, like the expected shortfall, are calculated. Routines for backtesting the results are included. Also scenario analysis and stress testing are part of the engine.
Utilizing our most advanced numerical schemes, UnRisk xVA engine is capable of simulating expsoures and calculating derived quantities like CVA and DVA. All risk factors of a portfolio are simulated together to create market scenarios - all instruments of a portfolio are evaluated under these scenarios to obtain the exposures. In the aggregation process, netting can be applied and the xVA management ratios are calculated taken into account probabilities of default for the counterparty and the institution.