Awesome Quant

Free, open source crypto trading bot

Extremely fast Query Engine for DataFrames, written in Rust

Production-grade Rust-native trading engine with deterministic event-driven architecture

Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.

SciPy library main repository

Python toolkit for quantitative finance

This is a database of 300.000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets.

Probabilistic time series modeling in Python

Python library for backtesting trading strategies & analyzing financial markets (formerly pythalesians)

xlwings is a Python library that makes it easy to call Python from Excel and vice versa. It works with Excel on Windows, macOS, and Excel on the web.

Read and analyze SEC EDGAR filings in Python. 10-K, 8-K, XBRL financials, Form 3/4/5, 13F, ADV — clean API, well-typed, MIT-licensed.

Backtestable AI trading agents and Python algorithmic trading strategies for stocks, options, crypto, futures, forex, SEC filings, FRED macro data, and real brokers.

Financial data reader

Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.

Exchange calendars to use with pandas for trading applications

Python wrapper for an unofficial Yahoo Finance API

Collection of algorithms for online portfolio selection

A Python async and event driven framework for algorithmic trading, with a focus on crypto currencies.

AI-based stock analysis and trading system

Calendars for various securities exchanges.

A fixed income library for pricing bonds and bond futures, and derivatives such as interest rate swaps (IRS), cross-currency swaps (XCS) and FX swaps. Contains tools for full curveset construction with market standard optimisers and automatic differentiation (AD) and risk sensitivity calculations including delta and cross-gamma.

Python client for tardis.dev - historical tick-level cryptocurrency market data replay API.

Python interface to Brazilian Central Bank web services

Get meaningful OHLCV datasets

python module for currencies

Analysis of financial instruments

Time series and portfolio analytics for quantitative finance.

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.

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.

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

EDINET XBRL parsing library and MCP server for Japanese financial data

e-Stat API client and MCP server for Japanese government statistics (政府統計の総合窓口)

Financial Market Intelligence MCP Server — stock quotes, technical analysis, crypto data, and portfolio insights for AI agents

Trading terminal for macOS. Scans 3 370 symbols across 12 timeframes to surface what's moving together. Tauri + Python + React. Open source, runs on your machine.

MCP server for TDNET timely disclosures (適時開示) — earnings, dividends, M&A, buybacks from Tokyo Stock Exchange

Cent-accurate mortgage amortization schedules for Python — validated against CFPB, Fannie Mae, textbooks, and real-world published examples.

Binance USDT-M futures scanner — 57 indicators × 12 timeframes + futures-microstructure/regime/MTF overlays, whale-divergence filter, one consensus verdict per symbol. Desktop (Python + React "Depth Terminal") & Android (Compose). Public data only, no keys.

Tracker for U.S. public-company equity stakes in Anthropic and OpenAI. Built from primary SEC filings, court records, and press releases. Each row confidence-tagged (V/P/S).

Distributional crypto-return forecasting via Wasserstein-geodesic extrapolation in quantile-function space. WGeo family wins 12/12 (asset × horizon) cells over 6.75y walk-forward CRPS vs GARCH and classical baselines. v0.4.