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m-ichaels/README.md

Michael Sharp

FX and Credit Trading Business Analyst at Crédit Agricole CIB, London. MEng Chemical Engineering, University of Birmingham.

Research interests: machine learning, statistical arbitrage, market microstructure, NLP. Python, C++, SQL, kdb+/q.

First author, International Journal of Hydrogen Energy, in press, 2026.

LinkedIn · m.chaelsharp@gmail.com

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  1. fx-skew-internalisation fx-skew-internalisation Public

    FX dealer market making: skew, internalisation, adverse selection and price reading. C++ simulator + HJB solver extending Barzykin-Bergault-Gueant (2023/2025) on EURUSD ticks

    C++

  2. lob-execution-sim lob-execution-sim Public

    Order-book execution simulator and TCA: replay / queue-reactive / zero-intelligence modes, FIX 4.4 gateway, self-recorded L2/L3 feeds, kdb+ and DuckDB storage

    C++

  3. rates-curve-nlp rates-curve-nlp Public

    Machine-learned Treasury yield curves for pricing, hedging and RFQ quoting: kernel-ridge discount curve vs Hagan-West bootstrap, learned hedge ratios, FOMC/ECB statement NLP nowcasts and an event-d…

    Python

  4. options-mm options-mm Public

    Options market-making engine: SSVI/SVI surfaces, a quoting engine replayed on recorded Deribit books, RFQ pricer, microstructure of quoting

    Jupyter Notebook

  5. execution-ops execution-ops Public

    Systematic execution operations stack: portfolio-to-orders, FIX 4.4 order lifecycle, live monitor with fault injection, SQL reconciliation, corporate actions and calendars, TCA with a broker wheel

    Python

  6. vol-dynamics vol-dynamics Public

    Volatility dynamics research and systematic volatility strategies: realised-variance library, HAR forecasts with implied vol, the variance risk premium by asset and tenor, earnings and FOMC premia,…

    Python