Web-based options research platform for scanning watchlists, comparing contracts and modeling strategies
Quantitative research platform for building and testing systematic trading strategies with point-in-time backtests and walk-forward validation
Stage
Not given
Startup
Founded
Not given
2025
Based in
Not given
DE
Pricing model
Paid
Freemium
Pricing
Visualizer: $10 USD/month or $100 USD/year; Pro: $30 USD/month or $300 USD/year; All Access: $50 USD/month or $500 USD/year. Seven-day All Access trial available with card required.
Starter €7.99/month, Practitioner €19.50/month (regularly €39), Research €34.50/month (regularly €69). All prices include VAT. Every new account gets 30 days of Practitioner free with no card required.
Key features
Live options strategy visualizer with payoff modeling across price and time
Options Yield Matrix for comparing contracts by monthly yield, breakeven and probability
Short Options Scanner for cash-secured puts and covered calls
Advanced Strategy Scanner for multi-leg option structures
Auto-calibration to update strike targets based on market levels
Trade journal with thesis, fills, adjustments, rolls and outcome tracking
AI Analyst for questioning assumptions and comparing setups
Live ThetaData market data with streaming updates
Portfolio view with profitability and campaign history
Learning Hub with lessons on strategies and risk management
Visual strategy builder with circuit diagram interface
Point-in-time backtesting over 20 years of history
Walk-forward validation and robustness testing
Indicator strategies with mean reversion and momentum
Stochastic methods including Kalman filter and Ornstein-Uhlenbeck models
Factor model and portfolio construction tools
Paper trading with daily marked prices
Python code export for backtests and strategies
Regime analysis and market regime detection
What makes it different
Connected workflow from watchlist scanning through trade completion in one platform instead of multiple disconnected tools
Monthly Yield % metric that standardizes returns across different expiries and strikes for easier comparison
Auto-calibration to keep strike targets current with market positioning instead of manual updates
Built by a trader for traders, starting with one core problem to solve
Point-in-time data discipline prevents look-ahead bias and ensures strategies see only information available on each date
113 published research articles and studies with reproducible methodology and full audit trail
Circuit diagram interface makes strategy design accessible without requiring extensive coding
Full Python export enables strategies to be deployed outside the platform
QuanterLab