11th Release

[Roland Lichters]

Hi all,

We are happy to announce our next release of ORE on https://github.com/OpenSourceRisk.

Main contribution this time is Acadia’s scripted trade framework that allows representing complex payoffs (hybrids, baskets, with path-dependence, early exercise) using an ORE scripting language, so that new instruments can be added without recompiling ORE.

Scripted trades are fully integrated into ORE, with pricing, sensitivity analysis, par sensitivity conversion, fast exposure simulation and XVA using American Monte Carlo.

Moreover, the new framework is the basis for an ORE implementation of Algorithmic Differentiation (AD) for trade sensitivities and ultimately XVA risk and SA-CVA.

And finally, the framework provides an external compute device interface for utilising GPUs.

The current release also adds SIMM 2.6, as well as one-day SIMM for SIMM versions >= 2.2.

ORE v11 is based on QuantLib 1.31.1.

To get started with ORE as a Python module, just call “pip install open-source-risk-engine” and see the ORE User Guide
at https://opensourcerisk.org/documentation

Best wishes,
Roland

[Anonymous]

Hi Roland,

Many thanks for this release and including scripted trade framework in this release. I am trying to use the pre compiled ORE executable located under App/bin/x64/Release/ as described in the userguide. However, I couldn’t find this folder in this release. Can you please mention where can I find pre compiled ORE executable?

Thanks

[Roland Lichters]

Hi,
apologies, I should have said that in the announcement: We cannot provide the executable at the moment, because we need to follow stricter IT security policies now, which involve scanning of the codebase and artefacts like ore.exe before releasing. We managed to get this done for the source code (see the note on Blackduck and Coverity scans in News.txt) , but not for the ore executable, because we did not want to delay the release further. We will look into including the executable next time again, or we will look at GitHub actions to build post release.
In the meantime, how about using the Python wheels? When you install the ORE Python module with “pip install open-source-risk-engine”, then you can run ORE through Python effectively in the same way as running the executable, without any loss of functionality or speed. Example 42 demonstrates that use case.
Best wishes,
Roland

[Anonymous]

Hi Roland,

I wanted to as about the Jarrow-Yildrim model in scripted trade framework. The scripted userguide mentions that in JY model, real rate volatility and real rate reversion is constant and not calibrated but in non-scripted framework, userguide mentions that real rate reversion and real rate volatility can be calibrated. Going forward, is this feature planned to be incorporated in the scripted trade framework as well?

Thanks

[Peter Caspers]

Hi, that’s correct. At the moment the calibration of the JY model in the scripted trade pricing engine is limited to using ATM CPI Cap / Floors to determine the CPI process volatility and using a hardcoded real rate volatility. It is generally easy to add more calibration strategies. What exactly do you have in mind, i.e. which calibration instruments do you want to use for the joint calibration of CPI and real rate volatilities?

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