QuantConnect
Research, backtest, and trade your investments on the world's leading algorithmic trading platform.
About QuantConnect
QuantConnect is a cloud-based algorithmic trading platform that gives quants, developers, and institutional traders a unified API for research, backtesting, and live trading. Built on the open-source LEAN engine, it provides terabytes of equity, options, futures, forex, and crypto data, plus 40+ alternative datasets, with one-click deployment to 20+ brokerages. Strategies can run in the cloud or on-premises using Python or C#.
Pros & Cons
Pros
- Free plan includes unlimited backtesting across all major asset classes
- Massive curated data library (since 1998 for US equities) plus 40+ alternative data vendors with point-in-time delivery
- Open-source LEAN engine means you can run strategies locally or on-premises without lock-in
- Connects to 20+ brokerages for paper and live trading from a single API
- Users retain full IP ownership with AES-256 encryption and 2FA available
Cons
- Steep learning curve; requires programming skills in Python or C#
- Not suitable for beginners or non-technical traders
- Alternative data and futures live feeds are paid add-ons that can add hundreds per month
- Limited support for European exchanges and markets
- Higher tiers get expensive quickly, with per-user minimums on Team and above
Key Features
Cloud Research Notebooks
Jupyter-style research terminals attached to terabytes of financial, fundamental, and alternative data, with popular ML and feature-selection libraries preinstalled.
Unlimited Backtesting
Event-driven backtesting across equities, options, futures, forex, and crypto with realistic portfolio, margin, and corporate-action modeling, available even on the free plan.
LEAN Open-Source Engine
The core open-source, event-driven trading engine that powers both cloud and local deployments, contributed to by 180+ engineers worldwide.
Live Trading & Deployment
Deploy strategies to 20+ supported brokerages including Interactive Brokers, Charles Schwab, TradeStation, Alpaca, Binance, Kraken, and Coinbase.
Multi-Asset Data Library
US equities and ETFs since 1998, equity and index options, futures, forex, CFDs, and thousands of crypto pairs from tick to daily resolution.
Alternative Data
40+ alternative data vendors delivered point-in-time and auto-linked to underlying securities via FIGI, CUSIP, and ISIN to avoid look-ahead bias.
Strategy Optimization
Parameter optimization and large-scale parallel compute nodes to tune strategies and scan parameter spaces quickly.
Web IDE with Debugging
Browser-based IDE with autocomplete, web debugging, and professional PDF backtest reports, with local coding via the LEAN CLI in VS Code.
AI Assistance
Built-in AI automation to help write, document, and schedule strategy code, with advanced AI routing on higher tiers.
On-Premises Platform
Institution tier offers a self-hosted local platform with AES-256 code encryption and FIX/professional brokerage connectivity.
Pricing
- Equities, indexes, forex, crypto, futures, options data
- Unlimited backtesting
- Community support
- 1 user
- Local coding (VS Code / LEAN CLI)
- Expanded dataset access
- Unlimited projects, larger files
- Add up to 2 compute nodes
- Basic AI automation
- Everything in Quant Researcher
- Project collaboration (up to 10 collaborators)
- Increased log and file limits
- Add up to 10 compute nodes
- Minimum 2 users
- Everything in Team
- Team project ownership
- Permissions management
- Add unlimited compute nodes
- Advanced AI scheduling
- Everything in Trading Firm
- On-premises platform
- AES-256 code encryption
- FIX / professional brokerages
- Bring your own key AI routing
- Minimum 5 users
Best For
Systematic Strategy Development
Quants and developers research, backtest, and refine algorithmic trading strategies against decades of multi-asset historical data.
Automated Live Trading
Deploy proven strategies to live or paper accounts at supported brokerages with co-located execution and real-time data.
Quant Research & Machine Learning
Use cloud research notebooks with ML libraries and alternative data to build and validate factor and ML-driven signals.
Institutional & Firm Infrastructure
Trading firms and institutions run the platform with team collaboration, permissions, and an on-premises option instead of building in-house.
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