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 […]

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. […]

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 […]

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 […]

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 […]

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 […]

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, […]

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 […]

Microservices and the Amazon Cloud

Capital Markets have been at the leading edge of adopting software technology to gain advantage and increase automation, but in the recent past have fallen behind the curve compared to the infrastructure, practices and technologies used by the Tech sector. Background I remember like it was yesterday (actually 1990 🙂 ) using Cobol on an IBM Mainframe while […]

SDR Data via Microservices

SDR Prices can be retrieved directly from Clarus using very simple code This allows our users to efficiently bring the data into any suitable environment This means that SDR data is available via an API This API is also simple to implement and simple to access. As I said last time, I’m not a coder. Fortunately, our developers help me […]