{"repo":"CameronScarpati/lob-regime-scanner","free":true,"listed":false,"github":"https://github.com/CameronScarpati/lob-regime-scanner","clone":"git clone https://github.com/CameronScarpati/lob-regime-scanner.git","description":"HMM-based market microstructure regime detection for cryptocurrency order books — 30+ features, Gaussian HMM, C++/pybind11 LOB engine, interactive Plotly Dash dashboard","language":"Python","stars":13,"topics":["backtesting","cpp","cryptocurrency","data-visualization","financial-engineering","hidden-markov-model","high-frequency-trading","hmm","machine-learning","market-microstructure"],"license":"MIT","category":"trading","readme_excerpt":"LOB Regime Scanner Hidden Markov Model Regime Detection for Cryptocurrency Order Books A learning project exploring latent market microstructure regimes in Level 2 order book data using Gaussian HMMs, microstructure features (OFI, VPIN, Kyle's λ), and an interactive four-panel Plotly Dash dashboard. Exploratory, not a production trading signal. --- Methodology · Results · Notebooks · Quick Start Four-panel interactive dashboard: Bookmap-style LOB heatmap with regime overlay, HMM state probabilities, 3D depth surface, and toxicity diagnostics (VPIN, OFI, spread, PnL). Overview An end-to-end pipeline, built as a learning project, that infers hidden regimes from noisy order book signals. The core flow: The model separates the data into three hidden states , which I label Quiet, Trending, and Toxic by ordering them on variance. On the synthetic and sample data used here they show different volatility and liquidity characteristics. The labels are interpretive, and the separation has not been validated on real market data. Author: Cameron Scarpati What the Model Produces After fitting, the three states sort cleanly by variance, and on the synthetic and sample data used here they line up with an intuitive reading of the order book: - Quiet is the lowest-variance state: tighter spreads, balanced order flow, near-zero return autocorrelation. - Trending sits in the middle: directional order flow imbalance and positive short-horizon return autocorrelation, a ","default_branch":null,"files":null,"tree":[],"storefront":"/r/CameronScarpati","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/CameronScarpati/lob-regime-scanner/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}