QuantOffice

QuantOffice data connectivity works with 100 + exchanges, brokers, ECNs, and other financial institutions worldwide. Simply select the trading venues and instruments you are interested in using in our new Universe Configurator – everything else is pre-configured. With very little effort, the data is streamed and stored on the server in TimeBase - a proprietary, high-performance, enterprise-grade data warehouse. For strategy development, analyze time-series data stored in TimeBase using a new approach based on the Python Jupyter environment, or use your favorite data analysis tools, including QuantOffice itself.

You can develop QuantOffice strategies in C# or Python. Build your strategy skeletons in QuantOffice Studio using the intent-sensitive code-generation functionality and continue coding from there, or proceed with developing and debugging in your favorite IDE, such as Microsoft Visual Studio or PyCharm. You can debug the strategy code with either the historical data stored in TimeBase or with streamed real-time data, whichever suits you best. The integration of your components or trading logic coded in different languages and environments, such as Java, C++, R, etc., is also supported via the rich and flexible API of QuantOffice, TimeBase, or StrategyServer.

QuantOffice Studio covers a comprehensive set of development and testing capabilities for the trading model lifecycle. The Universal Strategy Runner is built into the QuantOffice Studio for users to develop, run, debug, and refine strategy code in a single integrated sandbox. Back testing is a natural continuation of this process when a single run can be defined for tables of parameters, different calendars and custom sessions, and different lists of instruments. The Universal Strategy Runner uses a variety of simulators, from coarse bar-based to substantially more precise L2 (MBP and MBO) simulators.

Moreover, if required, a user can develop a custom strategy runner using the QuantOffice API. The Multi-Strategy Runner extension of QuantOffice Studio back-tests strategy assemblies and portfolios. Optimizer, another QuantOffice Studio extension, can run Brute Force or Genetic Optimization processes directly with your strategy as-is. Alternatively, by utilizing the QuantOffice API, users can choose a 3rd-party optimization framework to integrate work with the strategies developed in QuantOffice. The results of the back testing can be stored in BacktestExporer to examine and further refine the lifecycle management of the strategy at a detailed level, enabling the rerun with current data.

Run your strategy with live data supplied by numerous market data connectors and provided by QuantOffice, out of the box. Use our trading simulators to test, manage, and analyze the results of the strategies working in real time, or streaming historical data from TimeBase, before deploying them for live trading.

Risk rules and limits are defined in Risk Manager application before switching the system to live mode. The application provides out-of-the-box risk rules along with an SDK to define and manage custom risk rules. The user is in full control of the type of restraints the system must impose on the strategy that breaches the risk limits, ranging from rejecting the order and continuing the strategy, to stopping the strategy or “kill-switching” the entire system, depending on the severity of the breach.

When all aspects of the trading system are ready, tested, and proven to work as expected, the ready-to-go strategies are switched from Paper trading to Live trading using QuantOffice trading connectors activated on Execution Server (Ember). QuantOffice offers a variety of easily customizable Live monitoring applications: Trading Console, Strategy Server Monitor, Ember Monitor, and Risk Monitor. All financial transactions are stored in the trading history warehouse. Out-of-the-box integrations with widely popular IT tools such as Grafana, Graylog, and Kafka, and special FIX drop-copy are also provided as part of the ecosystem.