Backtesting & live trading engine built for AI agents. Zipline rebuilt on Polars with a native MCP server for Claude, Cursor & Codex. Stocks, ETFs, futures.
Drag-and-drop algorithmic trading bot builder for crypto. Features live charting, built-in risk management (kill-switches), and asynchronous execution via FastAPI and CCXT.
키움증권 REST/WebSocket 기반 AI 스캘핑 엔진 — 메인 봇·위젯·에피소드 매매와 장후 EV 자동 튜닝
Momentum investing strategy backtester with statistical validation and interactive Streamlit dashboard
👑 Enterprise-grade, high-frequency quantitative scalp trading engine for XAUUSD (Gold). Driven by PyTorch (TCN + Self-Attention), Smart Money Concepts (SMC/ICT) , Win32 C++ MT5 IPC bindings, and a real-time FastAPI Canvas Web Dashboard.
15-strategy algorithmic paper trading platform on AWS EC2 — systemd-supervised Python services, risk engine with kill-lines, market regime detection, and automated analytics pipeline
A high-performance algorithmic trading system built in Rust for backtesting, live trading, and strategy optimization with Binance & MT5 support, parallel execution, advanced risk management, and extensible architecture.
Production-grade quantitative volatility surfaces, Greek analytics, and backtesting signals. 2.6M+ IV ops/sec.
Stock price prediction using Python, yfinance and Random Forest Regression.
High-performance Terminal User Interface (TUI) library for Go, engineered with almost zero heap allocations and zero GC pauses.
A High-Performance Multi-Symbol Backtesting Engine Reflecting the Binance Futures Market Structure
Advanced IDX Market Intelligence & Screener Platform featuring AI-powered Reasoning, Deep Broker Flow Detection, and Automated Trading Journal.
LightGBM cross-sectional ranking on Indian equities (Nifty 100, MidCap 150), with walk-forward retraining, purged labels and real Zerodha costs. Execution layer ported to NautilusTrader and reconciled to the research engine on 93 of 93 rebalance dates.
Autonomous Institutional Options Trading Swarm with Deterministic Zero-Hallucination Risk Gate & 24/7 Position Guardian. Built with FastAPI, Next.js, LangGraph & Alpaca.
ASRQuant is an open-source Python framework for auditable quantitative finance research, combining backtesting, Monte Carlo simulation, derivatives pricing, risk analytics, portfolio modelling, econometrics, machine learning, visualization, reproducibility, and implementation-sensitivity analysis.
A Python framework for testing trading strategies against the ways backtests mislead: look-ahead audits, matched-exposure controls, and block-bootstrap significance tests. The tester is itself tested - a property fuzzer plus mutation testing (4 planted engine bugs, all caught). Includes three case studies of rejected ideas.
Statistical arbitrage research platform in OCaml. Event-driven, paper trading only for now.
Survivability-first quantitative research system. An AI council debates every architecture decision before code; deterministic, tested strategies do the trading. Walk-forward + purged CV + deflated Sharpe. LLMs never place trades.
NSE swing-trading research platform — cross-sectional alpha scoring, LM-based news sentiment, and rigorous A/B backtesting. 100% free data, zero paid APIs.
Quantitative AI hedge fund platform: Flask backend, ML/RL trading models, React web and React Native mobile clients.
To associate your repository with the algorithmic-trading-quantitative topic, visit your repo's landing page and select "manage topics."