Use Case Track

A streaming Quantitative Analytics engine

The application of Quantitative Analytics to trades for the generation of Risk and P&L metrics has traditionally followed a batch based approach. Regulatory changes impose increasing demand for compute on financial institutions along with a growing demand for real time analytics due to increased volumes in eTrading across all asset classes

The talk is based on a use case for pricing Interest Rate Swaps, using Apache Beam, with a call to an external C++ analytics process. It describes the performance characteristics when operating in a non-cloud environment using Apache Flink as opposed to Google Cloud Dataflow

The talk will touch upon the subtle difference when operating across multiple runners. It will make suggestions on approaches to portability when architecting for a multi-runner operational environment.

Authors

Dr Raj Subramani
Dr Raj Subramani
Flumaion Ltd
Dr Raj Subramani

Raj has over 20 years’ experience in Investment Banking. Raj has worked primarily in the Fixed Income business at HSBC, J P Morgan and Deutsche Bank. He started his career in FX Options at Citibank. Raj has a PhD in Engineering from the University of Newcastle upon Tyne and holds a certificate in Quantitative Finance from the CQF Institute in London.

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