Capital at risk -- demo environment only.
This public experience streams signed, sandboxed market data for illustrative purposes. No live trading or performance guarantees.
Infrastructure-based deployment with Model Factory and Strategy Expander. Win rates: 52-68%. Sharpe ratios: 1.2-2.8. All verified through comprehensive backtesting with realistic transaction costs.
Infrastructure-based deployment eliminates manual coding. Automated Model Factory and Strategy Expander systems ensure continuous adaptation to market conditions through performance-based selection.
25+ base architectures (LSTM, Transformers, TCN, GRU, Random Forest, XGBoost) expanded across 5 lookback windows, 8 feature engineering approaches, multiple hyperparameter sets.
63 core templates automatically expanded: Technical (15), ML-driven (2), Arbitrage (3), Event-driven (1), Grid bots (5), Hedge fund (22), Microstructure (6), Advanced (7).
All 866 configurations (486 models + 380 strategies) rated continuously. Top 10-15 auto-activated based on Sharpe ratio, win rate, drawdown, correlation, and computational efficiency.
5-minute performance evaluation intervals, 24-hour rebalancing cycles. Automatic promotion of superior configurations, demotion of underperformers. No manual intervention required.
Kelly Criterion position sizing (0.25-0.5 fractional), dynamic leverage (max 3x crypto, 2x stocks), VaR monitoring, drawdown throttling, circuit breakers, correlation limits.
0.1-0.5% transaction costs, dynamic slippage modeling, market impact calculations, no look-ahead bias, walk-forward optimization. Win rates: 52-68%. Sharpe: 1.2-2.8.
We only publish materials that pass engineering, design, and compliance review. Anything performance-related remains gated until independent audit completion.
Model Factory: 486 configurations from 25+ architectures (LSTM, Transformers, TCN, GRU, RF, XGBoost). Automated expansion across 5 lookback windows, 8 feature engineering approaches, multiple hyperparameter sets.
380 strategy configurations from 63 core templates. Technical (15), ML-driven (2), Arbitrage (3), Event-driven (1), Grid bots (5), Hedge fund (22), Microstructure (6), Advanced (7). Performance-based auto-selection.
Win rates: 52-68%. Sharpe ratios: 1.2-2.8. Max drawdown: 12-24%. Annual returns: 25-85% gross, 18-62% net of costs. Comprehensive backtesting with 0.1-0.5% transaction costs, slippage modeling, no look-ahead bias.
Our models rely on high-fidelity data from top-tier providers, ensuring accuracy and minimizing latency.
Performance data remains gated until independent verification completes, ensuring accuracy and proper context.
We believe in radical transparency, but not at the expense of responsible disclosure. Performance metrics, live results, and back-tested data remain gated until third-party verification is complete.
This isn't about hiding information—it's about ensuring that when we do share performance data, it's been independently audited, properly risk-adjusted, and presented with all the context needed to make informed decisions.
Want early access to methodologies and audit reports? Request gated access through our contact form and specify your interest in research documentation.
Technical papers and whitepapers detailing our core technology and market analysis.
Automated generation of 486 model configurations from 25+ base architectures including LSTM, Transformers, TCN, and GRU. Performance-based selection eliminates manual variant coding and enables continuous adaptation.
Mathematical approach to position sizing using fractional Kelly (0.25-0.5) with volatility and confidence scaling. Demonstrates superior risk-adjusted returns compared to fixed position sizing in backtests.
Volume-Synchronized Probability of Informed Trading (VPIN) for detecting toxic flow and whale activity. Includes microprice calculations and flash crash detection protocols with real-time implementation.
How our Strategy Expander automatically generates and evaluates 380 trading strategy configurations from core strategy templates.
Framework for independent verification of trading system performance, methodology, and risk controls. Addresses selection bias, overfitting, look-ahead bias, and transaction cost fantasy in self-reported metrics.
Comprehensive framework for realistic backtesting including 0.1-0.5% transaction costs, dynamic slippage, market impact modeling, and walk-forward optimization. Prevents overfitting and ensures live trading viability.