Awesome Quant

Repo for code examples in Quantitative Finance with Python (1st edition) by Chris Kelliher

Detect trend in time series, drawdown, drawdown within a constant look-back window , maximum drawdown, time underwater.

Quantitative systematic trading strategy development and backtesting in Julia

Self-hosted Python strategy research and Alpaca paper trading with broker reconciliation, evidence gates, and live execution disabled.

A python library for computing technical analysis indicators on streaming data.

Implement, demonstrate, reproduce and extend the results of the Risk articles 'Differential Machine Learning' (2020) and 'PCA with a Difference' (2021) by Huge and Savine, and cover implementation details left out from the papers.

Vanilla and exotic option pricing library to support quantitative R&D. Focus on pricing interesting/useful models and contracts (including and beyond Black-Scholes), as well as calibration of financial models to market data.

Use Python like a spreadsheet!

Kelly Criterion calculation

Time series implementation for the Julia language focused on efficiency and flexibility

Data Analysis Studies on Value Investing

A zero-alloc, compile-time hardened FIX engine built for sub-100ns execution.

High performance, low-latency backtesting engine for testing quantitative trading strategies on historical and live data in Rust

Python API for accessing Lake high frequency tick trades & order book data

Quantitative factor research skills for AI coding assistants

Self-tuning multi-agent AI trading system. 8-source signal fusion, Bull/Bear/Judge debate on Claude Opus 4.7, Kelly + ATR position sizing. Python · Kalshi + Polymarket adapters.

An open-source toolkit for quantitative analysis of crypto & stock markets, featuring an advanced market screener, portfolio backtester, and companion tools for the Gunbot trading bot.

QuantLib with AAD

PriceHub: Unified Python Package for Collecting OHLC Prices from Binance, Bybit, OKX, Coinbase, Kraken APIs into a DataFrame

Open-source investment analytics platform bridging academic research and retail finance. Features include portfolio risk decomposition [Fama-French Five Factor Model], retirement sustainability modeling [Block Bootstrap Monte Carlo], max drawdown/CVaR dashboards, and risk-return optimisation [Markowitz, Ledoit-Wolf] via an intuitive user interface.

Python algorithmic trading bot framework for Kubernetes: backtesting, hyperparameter optimization, 150+ technical analysis indicators (RSI, MACD, Bollinger Bands, ADX), portfolio management, PostgreSQL integration, Helm deployment, CronJob scheduling. Minimal overhead, production-ready, Yahoo Finance data.

AI-powered trading research platform. Test any idea on stocks, futures, and crypto with event studies, backtesting, and statistical validation. MCP server with 8 tools. pip install varrd.

RL stock selection for China A-share — bundled polars-native factor library (105 Alpha101 + 191 GTJA Alpha191 = 296 factors), board-aware price limits, GPU train + ONNX CPU infer, MIT-licensed.

📚 MesoSim's Strategy Library

Fast Risks with QuantLib in Python

Market-making strategy that placed #2 in Paradigm's Prediction Market Challenge. 110 iterations, 8 hours.

Zipline Extensions for QuantRocket

Terminal ETF research & portfolio analytics via SEC EDGAR and IBKR

Contingency Random Number Generator — numbers with controllable fat tails, volatility clustering, and scale convergence

High-fidelity synthetic financial data generator using Heston Stochastic Volatility and Jump Diffusion.

BTC order book microstructure analysis: OBI, CVD, and spread statistics from 38 days of Binance data

63 deterministic quant computation tools for autonomous financial agents. Options, derivatives, risk, portfolio, statistics, crypto/DeFi, macro/FX, TVM. 1,000 free calls/day — no signup.

Python SDK for the FlashAlpha options analytics API — live options screener, gamma exposure (GEX), DEX/VEX/CHEX, options flow, 0DTE, VRP, volatility surfaces, greeks

Local-first backtesting engine with built-in overfitting detection. Asset-class agnostic. MCP-native.

Realistic limit-order fill simulator for options credit/debit spreads. Engine-agnostic, data-source-agnostic.

Official MCP server for Horus Flow Intelligence: Institutional-grade market microstructure and orderflow physics for AI trading agents.

Sextant is a local Python Financial Backtest app with a Streamlit interface. The core is a strict bar-by-bar event loop (MarketEvent → SignalEvent → OrderEvent → FillEvent) — fully deterministic, with a complete JSON audit trail of every event.