QuantLib Applications, Enhancement & Support
In cooperation with BN Algorithms Ltd we offer comprehensive services related to the QuantLib open-source library. Please contact us at email@example.com for enquiries. Types of projects we have undertaken for clients in the past:
- Deployment of QuantLib-based analytic in managed cloud environments (Spark/Lambda/Map-Reduce) at very large scale
- Enhancement of QuantLib models for pricing of options, CDS, puttable bonds etc.
- Reproduce third-party pricing of IR Swaps, Equity Options, CDS, puttable bonds, swaptions, etc using QuantLib-based analytics
- Software Engineering assistance (software builds/software architecture). See our Java and C#/.Net pages.
Rapid & Scalable QuantLib cloud deployment
We offer ready-made components and consulting on deploying QuantLib using Python notebooks coupled to moder scalable web-applications – see our Quant Panel pages.
QLW – Quantlib from Java
We are pleased to announce our QLW product, allowing efficient access to QauntLib from Java and excellent parallelisation capabilities. QLW allows direct translation of QuantLib Excel Addin spreadsheet into Java which allows, for example, easy linkage between Excel-based pricing and Java risk analysis systems.
An evaluation version is available for download
Some examples of QLW use are also documented at http://www.bnikolic.co.uk/ql/addindoc/
QuantLib Applications, Enhancements & Support
QuantLib is an open source project providing a large library of routines to price commonly traded financial instruments according to the models currently used by the major participants in the market. We are pleased to offer services related to this library, including support, development of enhancements to the existing library, documentation, and development of applications based on the library. For all enquiries please contact us at firstname.lastname@example.org.
We also are developing documentation for the QuantLib Addin which is available at http://www.bnikolic.co.uk/ql/addindoc/.
QuantLib on AWS/Azure/Google Cloud
We have substantial experience deploying analytic to cloud-like environments: