
Every tool a quantitative trader needs — from strategy generation to risk management, data sourcing to portfolio composition.
Five distinct AI modes for generating, predicting, and managing trades with large language models.
Classify market conditions into Trend, Range, Consolidation, Oscillation, or Bespoke regimes, then generate regime-aware entry signals. Two-layer approach separates classification from entry logic.
Time-series forecasting with three model sizes (mini/small/base). Multi-dimensional signal filtering separates prediction accuracy from noise for robust entry signals.
LLM evaluates every price bar with full context — philosophy, indicators, and market state — for granular buy/sell/hold decisions on each candle.
LLM decisions at configurable intervals (every N bars) instead of every bar. 10-20x reduction in API calls while maintaining AI reasoning for swing trading.
Describe strategies in natural language, iterate via chat, get executable Python code. Eliminates the programming barrier for traders with strong intuition.
Defense-in-depth exit rules and market condition filters to protect capital.
Block trades during unfavorable conditions using indicator-based observation rules. Separates "should I trade?" from "what trade?" to reduce false signals and drawdowns.
Five-rule exit system: Circuit Breaker, Time Limit, Regime Detection, Drawdown Limit, and Indicator Guard. Multiple independent safety layers prevent catastrophic losses.
Multi-source market data with local caching and real-time backtest analytics.
Six providers: YFinance, Dukascopy, ClickHouse, Alpaca, CCXT, BaoStock. Local Parquet caching with zero-copy executor access and concurrent download queue.
Live equity curves, trade logs, and 7-metric dashboard (PnL, Sharpe, MaxDD, Win Rate, Profit Factor) streaming as backtest executes. Discover failing strategies early.
500-1000x faster than Python. C++ executor with embedded Python via pybind11 delivers zero-copy NumPy access through Apache Arrow. Enables 100+ backtests per hour.
Free Deep Dive →Institutional-grade multi-signal fusion with statistical weighting and factor screening.
Institutional-grade signal fusion combining 1000+ signals with 5 weighting methods: Equal, Confidence, Voting, Max Confidence, Min Confidence. IC/ICIR/Sharpe screening.
Ücretsiz katman, C++ geriye dönük test motorunu, rejim tespitini ve YFinance + Dukascopy verilerini içerir; yani geniş ölçekte oluşturmaya başlamak için ihtiyacınız olan her şey.