SQL-driven order flow analytics for equity execution desks — schema design, analytical queries, and interactive notebook
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Updated
Mar 31, 2026 - Jupyter Notebook
SQL-driven order flow analytics for equity execution desks — schema design, analytical queries, and interactive notebook
ML-driven smart order routing — gradient-boosting models predict venue-level slippage, fill probability, and latency from a live ROS 2 execution-quality pipeline (FastAPI + React), with rolling live validation against realized fills
An institutional-grade Transaction Cost Analysis (TCA) framework designed to evaluate execution quality for treasury and multi-asset desks. Built with Python and SQL to automate data ingestion, calculate slippage, and visualize commercial metrics via an interactive Streamlit dashboard.
Prediction-market execution research lab testing whether apparent short-horizon Polymarket BTC pricing edges survive spread, fill probability, latency, risk limits, and settlement frictions.
Execution cost on Solana, measured from public swaps. The median trade pays ~0 bps at any size; the worst decile spans 858x between a stablecoin pair and a platform token. Pre-registered hypotheses, controls, and the refutations.
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