Quant Office

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Architecture

Quant office employs a flexible, componentized architecture, that allows for a variety of deployment scenarios. Users work in a powerful integrated environment consisting of a number of desktop applications, each specialized in performing a specific group of tasks. The environment is called QuantOffice. QuantOffice applications provide sophisticated user interface, including numerous types of charts, tables, and graphs, running under the Microsoft.NET framework. Additionally, QuantOffice applications utilize the power of the user’s desktop system to locally perform many of the required calculations. QuantOffice applications retrieve financial data from a back end service, called the QuantServer. QuantServer multiplexes the data coming from multiple data vendors or sources, and presents a single, coherent and filtered view of the data to the client.

The core engine of QuantOffice is called QuantServer. QuantServer is developed under the Enterprise Java technology, which allows it to run on a variety of platforms. QuantServer plays several major roles in the QuantOffice architecture.

• By serving as a single point of contact for client applications, QuantServer hides the details of connecting to each of the data providers, as well as the different concepts and languages used by the different data providers.
• QuantServer aggregates and caches very large volumes of financial data in a single central location, in close proximity (network-wise) to the client applications.
• It reconciles and filters the data before it is delivered to the client applications. For instance, QuantServer can be configured to cross-check one data source against another, or filter out, the values of certain attributes when they lie outside of a preset range, or change dramatically in too short a period of time. Alternatively, the suspect values can be smoothed using various methods, rather than filtered out.
• Finally, when requested by the client applications, QuantServer performs the kinds of computation that require access to very large amounts of data.