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Achievement: YOLOAchievement: Pull Shark

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RaynorEtienn/README.md

Romain ETIENNE — Raynor / RaynorEtienn

X-HEC (École Polytechnique × HEC Paris) · Data & Finance - Quantitative Researcher

Quant researcher on a systematic equity long/short desk (London). Physics & ML background, focused on systematic alpha research and risk.

Focus

  • Alternative-data signal research (NLP), performance attribution (Brinson), backtesting
  • Risk modelling (VaR-based sizing), regime detection (HMM), covariance cleaning (RMT)
  • Equity long/short, statistical arbitrage, market microstructure

Stack

  • Python (primary) - NumPy, Pandas, PyTorch, Scikit-learn - research & NLP
  • Rust - low-latency systems (10k+ LOC multi-client/server QKD engine @ Thales, private)
  • R, MATLAB; C++ (familiar)

Featured

  • Financial-Data-Analysis - applied data-science / financial analysis (the work sample behind my current quant role)

Most recent work - current desk research, the Thales Rust systems, and a multiplayer game in development - lives in private or restricted repositories.

LinkedIn

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  1. Financial-Data-Analysis Financial-Data-Analysis Public

    Demonstrates applied data science techniques (Jupyter Notebook) for financial or risk reporting, including visualization and statistical inference.

    Jupyter Notebook 2