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Kelly Criterion calculation

Zigma is an algorithmic trading framework built with the Zig programming language, leveraging an actor-based concurrency model. It aims to provide an efficient, low-latency system for algorithmic trading through components handling market data, strategy execution, order management, risk, and data persistence.

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

Data Analysis Studies on Value Investing

Self-hosted AI trading strategy lab — paper trading, overnight strategy tournaments, 15+ technical indicators

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

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

Quantitative factor research skills for AI coding assistants

Self-tuning multi-agent AI trading system. 8-source signal fusion (Polymarket + Kalshi + 10 ML models incl. Kronos foundation model), Bull/Bear/Judge debate on Claude Opus 4.7, Portfolio Manager gate.

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.

A Python SDK for FinancialData.Net API - Real-time & Historical Stock Market Data

📚 MesoSim's Strategy Library

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.

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

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.

Terminal ETF research & portfolio analytics via SEC EDGAR and IBKR

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

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

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.

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

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.