Loading...
Roadmap
Home / Roadmap

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. Through releases 2-4 up to May 2019 the product class coverage has grown across six asset classes – Interest Rate, FX, Inflation, Credit, Equity and Commodity derivatives, also adding Bond/Loan instruments, the exposure simulation framework was extended to cover five of the six asset classes, and, moreover, a framework was added for sensitivity analysis and stress testing. The latest release has also opened ORE up to other languages by providing the beginning of ORE SWIG wrappers that allow using ORE components in Python or Java, etc.

 

Roadmap


Quaternion is committed to broaden ORE’s scope further, completing the vanilla product coverage across the six asset classes and the sensitivity and simulation framework to cover these.

 

In the Open Source Risk User Meeting in November 2018 in Frankfurt, the participants gathered a high level list of features they would like to see in ORE over time, including

  • Comprehensive ORE Python wrappers
  • Payoff language for exotic payoff coverage
  • Loan products
  • Portfolio evolution models
  • Interfaces and adapters for widely used systems
  • Analytics for capital requirements calculation, standard appproaches
  • Analytics for credit portfolio migration and default risk
  • Analytics for integrated market and credit risk
  • P&L, P&L decomposition
  • Excel integration

some of which Quaternion might cover over the next releases.
The community is invited to contribute to ORE’s growth along these lines.