Our QOEMS solution supports multiple asset classes and is available via the web, mobile and/or rich client applications. The internal quote management functionality provides fully audited and state management of quotes before they turn into an actual executable order. Multi-asset class quote and order management is becoming increasingly important to support the requirements in the MiFID II regulatory changes.
Our Internal Quote Management functionality allows a firm to have a concept of a “quote” which can be either a buy, a sell or a two sided (both buy and sell) quote request. This can be integrated to an external pricing engine including Excel, utilising the genesis pricing engine or a user can use the genesis platform to manually respond to quote requests.
Our External Quote Management functionality allows a sell-side firm (either broker dealer or treasury desk) to have a concept of a “quote” which can be either a buy, a sell or a two sided (both buy and sell) quote request between themselves and their buy-side client.
Within the genesis QOEMS platform we provide a basket and order management system to manage the workflows of either a broker dealer or a buy-side firm.
The R language is increasingly used among statisticians and data miners for developing statistical software and data analysis. It is therefore suitable for transaction cost analysis, pre-trade and post-trade calculations, and its popularity is building up quickly. The genesis framework offers two different ways of working with R (Renjin and rJava), each one of them having different strengths. We provide out of the box TCA calculations written in R.
The genesis QOEMS platform includes the genesis Automated Rules engine to allow our users to define their preferred order routing methods based on any order or trade data within the platform. This provides our clients with an extremely powerful solution to perform any variety of different functions to streamline and expedite their order and execution management functions (both front-office and back-office). This flexibility allows for full or part-automation of a client’s workflow through the use of rules; for example to allow a client to route incoming orders to a specific destination (to a user, a service, a market, and so on) based on configured parameters such as client, stock, volume, time, order type, country, sector, and so on. Additionally rules can be configured for onward processing for example where routing rules could be configured to identify trades to forward onward to a specific post trade venue or for compliance and operations checks.
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