Liquidity Risk

To measure Liquidity risks, Risksvr™ incorporates price slippage either as a number of days until the trade will be unwounded or a bid-ask spread that evolves stochastically throughout time: 

To measure Credit risks, Risksvr™ applies a random counterparty default model based on stochastic recovery rates, default probabilities and generalized expected default frequencies. 

Credit Curves
Risksvr uses default probabilities from a credit curve when simulating default mode. 
Expected default frequencies are computed from the marginal default probabilities extracted from the credit curve.
The credit curve can be built from:

• Expected default probabilities

• Marginal default probabilities or Hazard rates.

• Survival Probabilities.

• Transition matrices that evolve throughout time. If one single matrix is provided then Risksvr will assume it will be used to build the entire curve
  
  Risksvr™ extends beyond the fixed 1 year horizon and provides a model that can incorporate the full term structure of default probabilities, default correlations, hazard rates and / or transition matrices.

Transition and Migration
Risksvr can also use Transition Matrices to migrate counterparty ratings over simulation horizons.
Migration opens the door to two types of migration Migration up-to-default and Migration with Full cost of carry:

Correlated and uncorrelated default methodology:

Risksvr™ incorporates tow different default simulation technologies:

1. Direct Default Non-Default Observations
   
   Univariate / Independant Default: If no weightings are provided, the engine falls back to the default mode, which applies no correlation between the counterparty's probabilities of default. Instead Risksvr computes the likely-hood of default from a random uniform draw. If default is observed then recovery is simulated stochastically and then applied to the agent's exposure in order to compute LGDLoss-Given-Default)

   Correlated: As with standard obligor correlation, Risksvr expects a weighting scheme for each risk factor associated to a counterparty.
   This weighting is usually assumed to follow a country index approach, but any weighting scheme can apply. The simulation is then weighted and mapped to the Normal distribution's cumulative density. In its most simplistic form, this model falls back to the CreditMetric(tm) model.
   In it's fully fledged form, this allows for migration between simulation horizons with different transition matrices. This model expected a rating assigned to each spread curve in order to compute the full impact of upgrades and downgrades as they take place over the simulation horizons.
   
   

2. Time-to-Default Copula based methodology:
   If this is not enough you can actually switch the defaults engines to uses copula based Time-to-Default or Time-To-Survival methodologies instead of the more direct edf approach.
   
   This can apply for both Counterparty Risk (Counterparty Credit Exposure and Country Based Exposure) and Obligor Based Risk (i.e. Credit Sensitive Assets).

Risksvr™ offers the mechanisms to measure bilateral and multi-lateral netting across account  hierarchies. Every counterparty can hold nettable and non-nettable accounts with their own specific collateral and currency.

Risksvr™ can simulate country risk devaluation, contraction or growth (Sovereign political risk, Inflationary pressure, Devaluation policies, etc.) by computing both Country Exposures and Country Losses. 

Risksvr™ can measure funding gaps and long term profitability scenarios of positions. 
Each position can associate cash-accounts to individual exposures (i.e. legs). Each exposure   can then credit/debit the cash-account according to the proceeds or costs associated with the positions (coupons, dividends (if paid in cash), payments, option exercise, etc. 
Cash-accounts can thus mimic very closely what happens in practice. 

You can therefore take into account movements of collateral posted to fund these positions as well as estimate the impact of reinvestment policies and this either from a non-guaranteed or guaranteed counterparty relationship

^Risksvr™  is designed as a generic modular engine.

Each component is connected to the other via generic streams. 
Reports can thus be produced for every piece of information processed by ^Risksvr(Tm).

Better yet, every process can be overridden by user defined input data, This means you have complete control over each calculation step in the engine. Each step can be captured and replayed, which greatly facilitates replication, validation and benchmarking.

For example, you can decide to override the internal engine and inject your own Random data, your own forward rates, your own Zero Coupon Rates, your own  Factored Matrix, your own unitized returns, your own  Pricing Routines, your own Marginal / Conditional Default Probabilities, your own Counterparty factorized weights and mappings, etc. You can also switch between unlimited sources of market data (file, sockets, db)  (see Template Data / Benchmarking)  which greatly facilitates checking of results.

Risksvr™ accumulates results according to tags and dimensions In Risksvr™ parlance, a tag is a token in a URL like hierarchy associated to one or a group of trades.
Tags support the same syntax as conventional URLs. (e.g.: /portfolio/fx/usd could be a valid tag). Tags are always associated to a dimension. If no tag is defined, the engine assumes the tags belong to the same default dimension.

Tags can be sliced and diced as well as "custom operated".
Tags come in many flavors and types (market, credit, factor, time-band, benchmark, limits, hedge-accounting, etc)

By design Risksvr™ accumulates marginal sensitivities of the trade's contribution with regards to other holdings that form a position and portfolio on the fly. This means incremental VaR or Losses  as well as any marginal statistics are always available for any report. This has important consequences in terms of stress test "hot-spots" identification, hedge analysis, real-time value-at-risk, default loss or credit enhancement and portfolio diversification benefits.

Risksvr^™ comes pre-configured with industry standard settings and assumptions.
However, every underlying assumption that drives each Methodology can be changed by the user or administrator, if need be.
This approach is based on the idea that if you don't ask, then you probably don't need to know....

This obviously makes your life a lot easier, since you don't need to deal with complex setup values which only Risk Management professionals are accustomed to. On the other hand you can always change these values if you want to tweak results according to your own assumptions.

The engine is based upon generic financial concepts that can be relaxed or constrained in order to create entire sets of assumptions that steer each methodology.

This makes the engine very easy to use for beginners and yet amazingly sophisticated for leading edge users or researchers that want to investigate new approaches.