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Home>Solutions>QuantOffice Energy
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QuantOffice Energy Quantitative Energy Trading Platform

4.1

(24 ratings)
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QuantOffice Energy

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Overview
Differentiators
Features
Use Cases
Reviews
Overview
Differentiators
Features
Use Cases
Reviews

Solution Overview

QuantOffice Energy is a fully customizable energy trading platform giving researchers and traders, in the energy markets, the choice of how the system interacts with the markets. The system is product agnostic and can support all energy assets and instrument classes such as: gas, power, oil, coal, carbon, spot, forwards, futures, options. The solution can be fully customized to support users' requirements as these can vary greatly when trading different asset classes on the energy markets. Choice of data feeds, and execution venues is completely open, as are the types of data supported; price (L1, L2, L3) news, weather, shipping, inventory, fundamental etc.

It supports the creation of custom synthetic products, which can be back tested against multiple data sets from historical market data to analytical data stored in our TimeBase database. The tool kit supports the fast development of custom algorithms that can be immediately accessed to ensure an energy provider’s' book is fully balanced with no shortfalls. Integration with ETRM and CTRM systems for balance reconciliation is supported.

In addition, the platform comes with a custom UI designed for Spot trading energy/power markets. The trader also has the ability to manage the hundreds of possible intervals in a given day for the intraday and auction sessions. Custom algos can also be designed to facilitate closing of positions to ensure no shortfalls occur.

Customer problem

  • Quants in the energy market are forced to build trading models across multiple platforms

  • Standard UIs that don’t enable to trader to rapidly inspect their positions or fills across many different product intervals.

  • Lack of cross sector energy trading

EPAM Solution

QuantOffice Energy streamlines the process for building quantitative trading models by enabling them to perform their analysis and initiate execution from simulation to production environments under one single eco-system. This with our custom designed UIs for the energy sector ensure the traders can design their system to their liking regardless of the sector within energy.

The system supports, and stores, data from multiple sources; price (L1, L2, L3), weather, news, shipping, fundamental, political etc., to enable users to research back test, optimize and trade their ideas. Execution is via multiple routes; exchanges, brokers, ECNs, supporting ultra-low latency trading.

Key Differentiators

Open and customizable framework

Rich, flexible, and powerful environment for creating and running custom trading strategies and bots

Benefits

Deep-dive Analysis

Generate alpha by back testing fundamental and market data

Code Reusability

Employ the same code for both research and live trading, saving time and effort

Unrestricted Data Format Storage

Store and analyse any form of data in a centralized repository

Features

  • Custom-built UI: Special UI that allows users to visualize all intraday trading intervals in one UI
  • Analysis & optimization: Analyzing the results of back-testing and optimizing for improved results
  • Simulation with live data: Simulate with live data and analyze the effectiveness of the strategy
  • Multiple choices for trading execution: We have over 100+ different connectors to choose from for market/analytical data and execution routing
  • High-performance applications: Designed to process millions of messages per second with low latencies using generic out-of-the-box hardware, tunable to microseconds where demanded

Use Cases

Trading Research

Problem Statement

Usually platforms tie the users to use their data or offer no flexibility on the data types they can back-test against

Solution Proposed

To create a database that allows the user to use any source or format of data

Achieved Results

Our TimeBase database allows the user to source their own market data, and allows them to use any data format to back-test their models against

Risk Management

Problem Statement

Many systems in the energy markets do not offer customizable risk rules or limit the user to their internal risk rules which may not be up to par with a company’s risk parameters

Solution Proposed

Create a platform that allows users to build their own defined risk rules, while also offering them many prebuilt risk rules

Achieved Results

Risk Manager allows the users to ensure their risk parameters meet their internal teams’ parameters set by the risk team

Customer Ratings & Reviews

4.1

Based on 24 votes

5 stars
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4 stars
15
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Questions & Answers

What types of data can be used for back testing?

Our TimeBase database allows for any format of data. This data can be recorded or uploaded from historic files and referred to in back testing and execution.

How can your system be deployed?

Our system can be deployed on a cloud server, or on prem hardware.

Have a question? We are ready to help you.

license type

Tech Requirements

Windows and Linux, on-prem, and AWS, Azure and GCP are all supported

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