Explore live open-source projects and AI models.

This course, taught by Prof.Jerzy in NYU, applies the R programming language to momentum trading, statistical arbitrage (pairs trading), and other active portfolio management strategies. The course implements volatility and price forecasting models, asset pricing and factor models, and portfolio ... Read more

No description available from source.

Windows/Linux/MacOS Desktop App to browse QuantConnect Lean engine's backtest and monitor live performances. Original project https://github.com/mirthestam/lean-monitor

This framework provides robust tools for backtesting, forward trading, and live trading. Simulates over 400 exchanges, and supports HFT real-time trading with tickdata websocket feed from Binance over Mexc to Pancakeswap. Easy to set up, requiring as few as 3 lines of code to start trading.

No description available from source.

Backtest asset allocation strategies in Python with only a background in pandas necessary

Probability of Backtest Overfitting

Backtesting tool and connector for the platform Bots.

A next-generation AI-powered algorithmic trading platform supporting strategy backtesting, live/paper trading, parameter optimization, and intelligent analysis.

sharpe is a unified, interactive, general-purpose environment for backtesting or applying machine learning(supervised learning and reinforcement learning) in the context of quantitative trading