Microservices-Based-Algorithmic-Trading-System

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Microservices-Based-Algorithmic-Trading-System (MBATS) is an Open Source finance tool that provides a Docker-based platform for developing, testing, and deploying algorithmic trading strategies. It focuses on machine learning-based algorithms, offering a modular and easy-to-setup trading infrastructure.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is Microservices-Based-Algorithmic-Trading-System?

MBATS is an open-source, Docker-based platform designed for quantitative analysts and algorithmic traders to develop, test, and deploy trading strategies, with a strong emphasis on machine learning. It simplifies the process of bringing trading ideas to production by integrating various open-source tools like Backtrader for strategy development, MLflow for managing machine learning models, and PostgreSQL for market data storage. The platform also includes Apache Airflow for orchestrating jobs and Apache Superset for visualizing backtested and live strategy performance. MBATS offers a modular architecture, making it easy to scale and migrate components to cloud environments like GCP, and supports multiple symbol and strategy types for both backtesting and live trading.

Best used for

Ideal for developers and data scientists who need to develop, test, and deploy algorithmic trading strategies, manage machine learning models, and visualize trading performance. Especially valuable for those seeking a modular, open-source infrastructure to move trading ideas from concept to live execution with ease.

Common actions

develop trading strategies

deploy trading algorithms

manage machine learning models

backtest trading performance

visualize trading data

github copilot"AI Agents"face swappingdeepfakeautomated workflowworkflowslow-code/no-codeopen-sourcecollaboration

Capabilities

Key features

Docker-based platform
Algorithmic trading strategies
Machine learning integration
Backtesting capabilities
Live trading support
Workflow orchestration
Performance visualization

Target Audience

developerdata scientist

Integrations

dockerbacktradermlflowapache-airflowapache-supersetpostgresqlminiooanda

Pricing & Plans

Open Source

Free

FAQs

What technologies are integrated into MBATS?

MBATS integrates several open-source technologies including Docker for containerization, Backtrader for trading strategy development, MLflow for machine learning model management, Apache Airflow for workflow orchestration, Apache Superset for data visualization, PostgreSQL for database management, and Minio for object storage.

Can MBATS be used for live trading?

Yes, MBATS supports live trading strategies. It includes integration with the Oanda Broker API for Forex trading, and the architecture can be modified to accommodate other brokers like Interactive Brokers for equity trading. Strategies can be scheduled using dynamic DAGs in Airflow.

How does MBATS handle machine learning models?

MBATS uses MLflow to manage the ML lifecycle, including experimentation, reproducibility, and deployment. ML models can be tracked, and their artifacts are stored in Minio. Models can also be served via MLflow pyfunc or as a REST API.

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Financial Modeling Financial Data & Research Risk & Fraud Detection Personal Finance Crypto & Blockchain Fintech

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Coding & Development › Code Assistants Coding & Development › DevOps & Infrastructure Data & Analytics › Predictive Analytics

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