Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
-
Updated
Aug 27, 2022 - Jupyter Notebook
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
Open-source desktop application for real-time market microstructure analysis. Explore live Level 2 order books, trades, liquidity, and built-in studies.
We release `LOBFrame', a novel, open-source code base which presents a renewed way to process large-scale Limit Order Book (LOB) data.
Real-time Crypto Futures depth heatmap in Rust (egui/eframe) with live order flow and trade tape.
Implementation of various deep learning models for limit order book. DeepLOB (Zhang et al., 2018), TransLOB (Wallbridge, 2020), DeepFolio (Sangadiev et al., 2020), etc.
A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.
Algo Library for Order Flow Inference and TCA
Sub-microsecond bare-metal execution engine with deterministic replay, lock-free order path, and hardware-timestamped latency measurement.
High-performance limit order book engine with C++ core and Python SDK. Processes 20M+ msgs/sec with µs latency. Supports real crypto/equity data replay, spread/imbalance/impact analytics, and backtesting of VWAP, TWAP, POV, and market-making strategies with reproducible PnL and risk metrics.
Exchange-grade CLOB matching engine + microstructure analytics in C++20
Academic python library that records changes to instances of the limit order book for pairs supported on the coinbase exchange.
Bookmap-style order flow visualizer in a single HTML file — real-time heatmaps, trade bubbles, DOM ladder, volume profile, CVD, and liquidity wall detection. Works with OpenAlgo WebSocket for live Indian market data (NSE/NFO/BSE/MCX).
From-scratch limit order book + matching engine in Rust. ~100 ns book ops replaying 104M operations from real NASDAQ ITCH 5.0 data; 143-fill sweeps in 2 µs. Binary OUCH order entry, 10 µs order-to-ack.
Optimization techniques on the financial area for the hedging, investment starategies, and risk measures
A comprehensive bundle of utilities for the estimation of probability of informed trading models: original PIN in Easley and O'Hara (1992) and Easley et al. (1996); Multilayer PIN (MPIN) in Ersan (2016); Adjusted PIN (AdjPIN) in Duarte and Young (2009); and volume-synchronized PIN (VPIN) in Easley et al. (2011, 2012). Implementations of various …
LLM structural reasoning validation via gamma exposure analysis in options markets. Papers 1 & 2 complete. Digital Finance (Springer) submission in progress.
Options-flow features, unusual activity, dealer positioning, and short-horizon forecasting.
A high-frequency tool that monitors the "Bid-Ask" spread and order book depth to predict the next 10-second price move.
The ultimate collection of institutional trading resources: order flow, market microstructure, options GEX, and algorithmic frameworks.
机构级 A股量化系统 - Hermes 多智能体 + Barra 中性化 + Level2 微结构 + 15 个圈内 tricks 完整实现
Add a description, image, and links to the market-microstructure topic page so that developers can more easily learn about it.
To associate your repository with the market-microstructure topic, visit your repo's landing page and select "manage topics."