quantitative

🧠 Explore Item Response Theory (IRT) to enhance AI-based adaptive testing with accurate measurements and improved assessment techniques.

OSS Tradingview with your own AI, free and unlimited.

Test AI-driven scoring of Reddit stock reasoning to build portfolios and compare their performance against the S&P 500.

stock. Obtain stock data, calculate stock indicators, chip distribution, identify stock patterns, comprehensive stock selection, stock selection strategy,

📊 Analyze and validate trading strategies with a high-performance backtesting engine using PySpark, processing thousands of backtests on real market data.

Live US macro release schedule with house forecasts and Kalshi consensus by Chirag Mirani

Library for sequence-to-sequence numeric prediction, applicable to any tokenizable input, and allows pretraining and fine-tuning over multiple tasks.

Football Edge research & production workspace — NFL/NCAAF odds collection, model validation, forward-shadow evidence, CLV, plus legacy EV betting tools.

Validate crypto market signals with AI for live trading, research, and quant analysis

Automate stock and futures signal display, bridge execution, and message push setup in one Flask dashboard for live data and paper trading

Provide an optimized multi-agent system for stock research, paper trading, historical backtesting, and automated Telegram updates.

A quantitative soccer forecasting project using historical match data, team and player statistics, and statistical models to evaluate and predict match outcomes.

Financial Quantitative Analysis

Java-based Open-Source Trading Engine Framework focused on speed, extensibility, maintainability. Contains both Backtest & execution engines.

ValueRay — independent third-party profile of a public API surface, by API Evangelist. AI-ready financial data API for stocks and ETFs. ValueRay aggregates technical, quantitative, and sentiment data with risk metrics, peer percentiles, and market regime signals into AI/LLM-friendly responses optimized for agents that need explainable financial ove

Pure-Python sports betting math: odds conversion, de-vigging, Kelly criterion. Zero dependencies.

Quantitative risk and performance analysis package for financial time series powered by the Julia language.

Quantitative analysis tools for Rust

Sports-vs-prediction-market arbitrage scanner in TypeScript, with a survival-rate feedback loop that calibrates its own thresholds

Framework for quantitative trading. Complete framework for development, backtesting, and deploying automated trading algorithms and trading bots.