The Market Data Research Environment (MDRE) is a cloud-based platform designed for quantitative analysts and data scientists to build, test, and deploy machine learning models using comprehensive tick-by-tick market data from over 200 global exchanges. It provides a Python API similar to pandas, integrated machine learning tools, and a library of ready-to-use analytics and use cases, all within a secure, scalable, and collaborative environment.

Key Features

Comprehensive Market Data Access Access to tick-by-tick data from 200+ exchanges, including equities, futures, options, and crypto.

• Minute bars and official opening/closing prices available
• Corporate action adjustments and symbology management

Python API & Analytics Library Pandas-like Python API for rapid development and analysis.

• Library of runnable use cases and documented examples
• Ready-to-use TCA (Transaction Cost Analysis) and backtesting tools

Integrated Machine Learning Platform Built-in ML framework for time-series data science.

• Simple pipeline creation, data pre-processing, feature selection
• Experiment tracking, model comparison, and model serving

Scalable & Secure Environment Hosted on a secure, isolated infrastructure with DevOps support.

• No need for user-side infrastructure or configuration
• Collaborative environment for teams

MLOps & Automation Combines open-source (JupyterHub, Ray, MLFlow, Docker, Kubernetes, Airflow) and proprietary (OneTick) technologies.

• Scalable hyperparameter tuning
• Automated experiment management

Benefits

Accelerated Research & Development Enables rapid prototyping and deployment of trading strategies and ML models.

• Reduces time-to-insight for quants and data scientists
• Eliminates infrastructure and data management overhead

Improved Trading Performance Facilitates advanced analytics and backtesting to optimize trading strategies.

• Access to high-quality, historical, and real-time data
• Avoids common programming and data pitfalls

Collaboration & Scalability Supports team-based research in a secure, scalable environment.

• Enables sharing and comparison of models and results
• Grows with organizational needs