Clarus Microservices

Software is moving from monolithic applications to microservices.

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SIMM, Margin, XVA, FRTB, Risk, Hedge, P&L, Compliance

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Code in Python, Perl, Node.js, R, Julia, C#, Java

Software Infrastructure for the future


Latest Posts

  • Nov, 14

    Released: A Julia library for Clarus Microservices

    A Julia library has been developed and released to support Clarus Microservices. The library provides convenient access to Clarus Microservices. Source code is available on GitHub. In a previous blog, ‘Microservices: Swap Equivalents in Julia’ we showed that it was possible to call the Clarus API from Julia. We have generalised the code example in […]

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    Oct, 16

    Trade Validation: A simple version of FpML rule IRD12

    Trade representations in CSV or FpML often have issues with stubs. FpML validation rule IRD12 has simple alternative for a wide range of cases. A form of FpML IRD12 can be represented in XPath for a wide range of cases. During proof-of-concept trials we are often asked to load up a prospects portfolio; either a […]

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  • Aug, 2

    ISDA SIMM™ IN PYTHON

    The Clarus Microservices API makes it very easy to compute ISDA SIMM™ from Python The input data required is a CRIF file contain risk sensitivities What-if trades can be easily added to determine the incremental change in margin We provide a Sandbox within our API Reference page for you to try the API methods Before moving […]

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    Jun, 14

    Microservices: Swap equivalents in Julia

    Julia is a modern high-level, high-performance language for numerical computing. Clarus API functions are easily accessed in Julia. What is Julia? Julia is a relatively new computing language, combining the ease of development (similar to python and matlab) with a Just-In-Time compiler and other language features to deliver runtime performance close to that of C. […]

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  • May, 24

    Microservices for Derivatives: What You Need to Know

    It has been some months since I wrote about Microservices and the Amazon Cloud and as we have recently released a major new version, I wanted to elaborate further on the importance of this technology. Background Microservices are fine-grained services that can be used to rapidly assemble a more complex service, a system, or a user interface. Unlike libraries […]

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    May, 2

    Microservices for absolute beginners

    After a career in Capital Markets enterprise software, I recently joined Clarus and other than their great blogs, my reason for joining is that I buy into the vision of cloud based technology as the future for our domain. Micro-services delivering sophisticated analytical computation, easily consumed into a firms existing infrastructure, applications and Excel, will be […]

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  • Apr, 18

    Microservices: ISDA SIMM™ in R

    The Clarus API has a function to compute ISDA SIMM™ from a CRIF file contain portfolio sensitivities. What-if analysis can be performed in addition to the portfolio margin calculation. The function is very easy to call from many popular languages, including R, Python, C++, Java and Julia. What is R? R is a language and […]

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    Apr, 4

    Microservices: A SIMM Sensitivities Calculator

    The Clarus API has a function to compute SIMM sensitivities from many trade description formats, including FpML and CSV trade lists. Results are in ISDA SIMM™ CRIF file format. The function is easily called from popular languages, e.g. Python, R, Julia, C++, and Java. Many related functions are available, see our API documentation. Calling directly […]

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  • Mar, 28

    Microservices: FRTB Modellable Risk Factors

    FRTB regulations specify that non-modellable risk factors are subject to stressed capital add-ons For a risk factor to be modellable it must pass a specific test for continuously available real prices The Clarus API provides functions for the risk factor modellability test for OTC Derivatives These functions are very easy to call from many popular languages, […]

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    Mar, 21

    Microservices: An FpML Cashflow Generator

    The Clarus API has a function to generate cashflows from an FpML description of a trade. The function is very easy to call from many popular languages, including Python, R, Julia, C++, and Java. Many related functions are available, see our API documentation. Calling directly in the browser To appreciate the ease with which the […]

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