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Current Scope

The Open Source Risk Project aims at providing a transparent platform for pricing and risk analysis that serves as

  • a benchmarking, validation, training, and teaching reference,
  • an extensible foundation for tailored risk solutions.

On that journey, ORE currently provides portfolio pricing, cash flow generation, and a range of contemporary derivative portfolio analytics. The latter are based on a Monte Carlo simulation framework which yields the evolution of various credit exposure and market risk measures:

  • EE aka EPE (Expected Exposure or Expected Positive Exposure)
  • ENE (Expected Negative Exposure, i.e. the counterparty’s perspective)
  • ’Basel’ exposure measures relevant for regulatory capital charges under internal model methods
  • PFE (Potential Future Exposure at some user defined quantile)
  • Value at Risk and Expected Shortfall

and derivative value adjustments

  • CVA (Credit Value Adjustment)
  • DVA (Debit Value Adjustment)
  • FVA (Funding Value Adjustment)
  • COLVA (Collateral Value Adjustment)
  • MVA (Margin Value Adjustment)

for portfolios with netting, variation and initial margin agreements.

The first release of ORE in October 2016 covered the simulation of interest rate and FX risk factors and portfolios of Interest Rate Swaps, Caps/Floors, Swaptions, FX Forwards, Cross Currency Swaps and FX Options.

The second release in May 2017 added more product coverage with Bonds/Loans, Equity Forwards and Options,  CPI and Year-on-Year Inflation Swaps. The simulation framework was extended to cover IR/FX and Equity. Moreover, a framework was added for sensitivity analysis and stress testing as a first step in building out the market risk coverage.


Quaternion is committed to extend ORE’s scope over a sequence of further releases from Q4 2017 onwards, with respect to both financial products and analytics.


The derivative product and the risk factor range will be built out to cover

  • Inflation
  • Credit
  • Commodity

choosing one basic risk factor evolution model in each category. For inflation we are considering Jarrow-Yildirim and Dodgson-Kainth, for credit a simple Gaussian model to start with, for commodity a log-normal model. Our goal is to provide a broad coverage first.


  • Subsequent ORE releases will also compute regulatory capital charges, e.g.  for counterparty credit risk under internal model method and the new standardised approach (SA-CCR),
  • the Monte Carlo based market risk measures will be complemented by Parametric VaR methods, e.g. for benchmarking various initial margin calculation models applied in cleared and non-cleared derivatives business,
  • and following the introduction of cash products with the second release we intend to also add credit portfolio migration and default risk analytics, with the option to integrate credit and market risk views

The order in which we contribute these ORE extensions is not fixed yet, and we are interested in the community’s feedback before we make the next steps.