github.com• Nov 13, 2025• 1 min read
Show HN: Qantify – GPU-Accelerated Trading Library with Advanced Math and AutoMLI've been building Qantify for the past 2 years - an open-source Python library for algorithmic trading that combines institutional-grade math models with modern ML/AutoML pipelines.*What makes it different:*Most trading libraries are either: - Too slow (Backtrader: ~5ms/point, Zipline: ~10ms/point) - Missing advanced math (no quantum finance, chaos theory, optimal execution models) - No AutoML pipeline (QuantConnect has basic ML but no AutoML) - No GPU accelerationQantify addresses all of these.*Performance:* - 0.008ms per data point (50-100x faster than alternatives) - GPU acceleration: 2-3x speedup on compatible hardware - 1767+ comprehensive tests, 100% code coverage - 106K+ lines of code*Advanced Math Models* (what hedge funds use):on # GARCH volatility modeling from qantify.math.econometrics import GARCHModel garch = GARCHModel(returns) vol_forecast = garch.forecast(horizon=10)# Heston stochastic volatility from qantify.math.stochastic import HestonProcess, MonteCarloEngine hesto