
QuantOfficeEnergy
Advanced systematic trading solutions for energy markets
QuantOffice Energy includes out-of-the-box market data connectors to data vendors and exchanges, supporting all major energy asset classes, along with other exchanges and FX LPs. Setting up the QuantOffice Energy universe is often as simple as selecting your trading venues and the instruments of interest in the QuantOffice Universe Configurator – everything else is pre-configured. Often, with little effort, the data is streamed and stored on the server in TimeBase - a proprietary, high-performance, enterprise-grade time-series database.
A wide range of data analysis tools and means are available for researchers. These include streaming APIs (Java, Python, C#, C++) and a wide range of commercial and open-source tools like Jupyter that are not integrated into the QuantOffice Energy suite. The SQL-dialect query engine is at the researcher's disposal as well, and the representation of the data as Py pandas is supported too, etc. QuantOffice itself is a powerful and reliable tool for working with time series and especially high-frequency data, providing a high-level, effective, and convenient API with no-code/low-code means.
The QuantOffice Energy platform offers an unmatched variety of development capabilities. QuantOffice gives the user a choice to develop C# or Python models, strategies, and algorithms in a convenient, efficient, all-inclusive package. A complete set of financial libraries and our non-invasive code-generator/co-pilot increase the productivity of the programmer by an order of magnitude. You can debug the strategy code either with 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 Strategy Server.
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 a user to develop, run, debug, and refine the 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, different lists of instruments and use 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 QuantOffice API. The assemblies and portfolios of strategy can also be back tested using the QuantOffice Studio extension called Multi-Strategy Runner. Another QuantOffice Studio extension is called Optimizer. It can be used to run Brute Force or Genetic Optimization processes directly with your strategies as-is. Alternatively, by utilizing QuantOffice API, a user can integrate a 3rd-party optimization framework of a choice to work with the strategies developed in QuantOffice. The results of back testing can be stored in BacktestExporer for further refinement, fine-grain lifecycle management of the strategy, and rerun with current data and group access.
The strategy can be deployed at any time with live data supplied by out-of-the-box market data connectors offered by QuantOffice Energy to be test-run in an environment closely resembling live trading. Playback of historical data “as-live” is supported as well.
Paper trading, involving the Risk Manager for creating realistic scenarios of live strategies execution in combination with QuantOffice and Ember trading simulators, is the most critical test before finally running them in a live trading ecosystem.
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 together with 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 keeping going 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 Energy trading connectors activated on Execution Server (Ember). QuantOffice Energy offers a variety of easily customizable Live monitoring applications: Trading Console, Strategy Server Monitor, Ember Monitor, and Risk Monitor. All the financial transactions are stored in the trading history warehouse. Out-of-the-box Integrations with widely popular IT tools such as Grafana, Graylog, Kafka, and more, a special FIX drop-copy are also provided as part of the ecosystem.
Key Features
Market Connectivity
Connect your strategies and algorithms to tradable energy assets across the globe. Combine it with the extendable and ever-growing list of connectors for cross-asset trading, hedging, and risk management.
Strategy Development
Use the QuantOffice Studio together with the data stored in TimeBase to develop and deploy advanced custom trading strategies, models, and algorithms, supporting .NET, and Python. Use MS Visual Studio Code or Visual Studio for effective coding and debugging. The execution server also provides an ultra-low latency API for building and running custom Java algos.
Backtesting and Paper Trading
Backtest your models and algorithms using Deltix’s advanced proprietary simulators. Run them with playback or live data and simulated paper-trading accounts along with pre-trade risk limits enacted in the most realistic test harness available before going live.
Live Trading
Deploy ready-to-go strategies and algos on Deltix's Trading Server to trade on single or multiple exchanges simultaneously. Trade fully automatically or semi-automatically in a high-performance, safe, and controlled environment. Monitor your trading ecosystem with a multitude of tools and applications addressing the needs of different business users.
Risk Control and Monitoring
Set and monitor pre-trade risk limits on any combination of attributes such as global, trader, account, exchange, team, etc. Use standard risk measures, such as exposures, draw-down, frequency, size, volume of trades, etc. and easily develop your custom limits with the provided SDK. Monitor the risk state of the system via out-of-the-box applications or develop your own screens.
Comprehensive Deployment Options
Deploy the entire system or parts of it on the cloud, in-house, collocated or with any combination of these for unmatched flexibility depending on your business and budgetary preferences.
High Performance Application Servers
Gain an instant advantage over your competition by utilizing QuantOffice's high-performance ecosystem, designed to process millions of messages per second with low latencies using generic out-of-the-box hardware, tunable to microseconds where demanded.
Efficiency Out-of-the-Box
Reduce TTM and TCO by leveraging hundreds or man/years of our investment to deliver battle-tested, time-proven high-performance products, tools, libraries, and APIs to build the most demanding research and trading capabilities covering the full cycle of systematic trading on energy markets.
Case Studies
Enhancing Gas Market Trading with the Quant Office Energy Suite
Background
Challenges
- A way to efficiently consolidate and analyze large historic datasets (e.g., level 2 price data).
- Tools to optimize strategy development and back testing.
- Real-time execution for market making, trading on OTC/other markets, and hedging FX exposures.
Solutions
- TimeBase: Consolidated historic and real-time data from unstructured and structured sources.
- QuantOffice: Enabled Python and proprietary strategy development, back testing, and optimization.
- ExecutionServer: Facilitated deployment of strategies for market-making, trading, and hedging.
- Real-Time Aggregator: Streamed live data directly into strategies for paper and live trading and to TimeBase to increment the historic data set for further research.
Results
- Unified historic and live datasets allowed efficient strategy development and refinement.
- Improved real-time execution for gas trading, market making, and FX hedging.
- Increased trading effectiveness directly on Trayport and other energy markets.
- The team using QuantOffice Energy became a key source of positive P&L within the firm.
to schedule
a quick demo