"Building the bridge between biological intelligence and silicon efficiency."
Status: High School Student (Tunisia) · Class of 2027
Focus: Quantitative research, distributed systems, computational biology.
I build autonomous infrastructure for market-adaptive execution across global derivatives venues. Source code stays private; architecture and methodology are open.
Currently: Scaling systematic trading infrastructure · Exploring computational biology and longevity research.
A multi-venue systematic trading infrastructure targeting 24/7 perpetual derivatives markets and regulated index futures. Source code is proprietary; architecture and methodology are publicly documented.
Role: Founder & Lead Researcher
Stack: Python · Polars · Event-driven backtesting · Google Cloud Platform
Pipeline:
- Data Layer — Institutional-grade Level-2 order book and derivatives flow ingestion via venue APIs, with redundant capture for forward-stream resilience.
- Validation Layer — Anti-overfit pipeline grounded in López de Prado methodology: Combinatorial Purged Cross-Validation, Deflated Sharpe Ratio, Probability of Backtest Overfitting.
- Execution Layer — Event-driven backtesting infrastructure with multi-venue adapters and comprehensive real-time risk management (drawdown control, latency monitoring, venue-health surveillance).
📂 Documentation: https://github.com/DisuzaQuantitative/Disuza-Quantitative
Public repo contains system documentation, architectural diagrams, and methodology. Core execution engine remains private.
| Domain | Stack |
|---|---|
| Core |  |
| Data Engineering |     |
| Quantitative |   |
| Environment |    |
- Now — Refining systematic trading infrastructure (research and validation phase).
- Near Future — Structuring capital allocation and the operating entity.
- Long Term — Computational biology and longevity research.
© 2026 Fares Bendhiab