Kairos Engine

Kairos Engine serves as a cutting-edge quantitative strategy validation pipeline, designed to uncover optimal trading moments—or validate the absence of opportunities—within financial markets. The essence of Kairos lies in its ability to sift through market noise, utilizing statistical methods to identify moments of significance amidst an otherwise chaotic environment.

Overview

This comprehensive platform enables rigorous research on scalping strategies specifically in the foreign exchange (FX) and metals markets. It is engineered to process raw tick data, classify market regimes through a sophisticated statistical model, and evaluate an ensemble of contemporary time series foundation models. The strategies under evaluation must navigate a meticulous walk-forward backtesting process that incorporates a cost model grounded in actual market spreads.

Key Features

• Statistical Analysis: The engine employs a four-state Hidden Markov Model (HMM) for regime classification, ensuring accurate historical analysis without future data leakage.
• Diverse Model Evaluation: Strategies are analyzed using a blend of four independent time series foundation models to create robust predictive models through confidence-weighted voting techniques.
• Robust Backtesting: Each proposed strategy must pass through an expectancy gate that confirms its profitability net of all costs, validated through a significant number of trades drawn from real market conditions.

Process Overview

flowchart TD
    A["Dukascopy tick feed"] --> B["Regime classifier, 4 state HMM"]
    B --> C["Forecast ensemble, 4 TSFMs"]
    C --> D["Trade filters"]
    D --> E["Signal assembly"]
    E --> F["Walk forward backtest, session aware costs"]
    F --> G{"Expectancy gate"}
    G -->|PASS| H["Validated strategy"]
    G -->|FAIL| I["Rejected, no capital risked"]

    classDef stage fill:#001621,stroke:#FF4103,color:#FFFFFF,stroke-width:2px;
    classDef gate fill:#FF4103,stroke:#FF4103,color:#FFFFFF,stroke-width:2px;
    class A,B,C,D,E,F,H,I stage;
    class G gate;

The architecture incorporates real-time data processing and validation, where the system captures raw tick data and translates it into actionable trading insights. The engine has identified strategies that, while under rigorous testing, either succeeded in demonstrating a tangible profit or were systematically rejected to mitigate financial risk.

Validated Results

The validation process has produced noteworthy outcomes, including a successful strategy variant that demonstrated a substantial gross expectancy of 246.91 pips per trade, retaining a net expectancy of 222.91 pips per trade across a substantial dataset of 221 trades over one year.

Conclusion

Kairos Engine is not merely a validation tool that endorses every strategy; it adopts a rigorous stance, revealing as much through failures as it does through successes. The invaluable ability to eliminate ineffective strategies before they incur real financial losses underscores the project's commitment to reliable, data-driven insight.

For further exploration of the capabilities of Kairos Engine, detailed documentation and instructions are provided within the repository.