In cooperation with BN Algorithms Ltd we offer comprehensive services related to the QuantLib open-source library as well as some ready-to-license software components. Please contact us at webs@bnikolic.co.uk for enquiries.

Sample analytic-related projects which we have undertaken for clients:

Sample software-engineering / integration type of projects:

QuantLib via REST interface

We offer ready-to-license wrapping of QuantLib and other libraries via REST interface, suitable for fast and durable development of applications: see following dedicated website and this blog post

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.

See QLW pages for more information or contact us at webs@bnikolic.co.uk. For information on Parallel Quantlib execution see our Parallel Quantlib pages.

An evaluation version is available for download

Some examples of QLW use are also documented at https://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 webs@bnikolic.co.uk.

We also are developing documentation for the QuantLib Addin which is available at https://www.bnikolic.co.uk/ql/addindoc/.

QuantLib on AWS/Azure/Google Cloud

We have substantial experience deploying analytic to cloud-like environments:

  • Tightly integrated Python Notebooks / Web applications using state-of-art technologies: Quant Panel

  • Scale-out using map-reduce clusters (Hadoop, Spark) or server-less (AWS Lambda)

  • Wrapping of QuantLib into Java/.Net (see e.g., QLW)

Copyright and published by: BN Algorihtms Ltd 2023. For general information only. Not to be relied for any purpose. Not advice about investment. No warranty of any kind. No liability for any use of this information accepted. Contact: webs@bnikolic.co.uk