quant-signal-engine 0.1.1

Signal Processing and Statistical Alpha Generation

Signal-Engine 📡

Real-time Signal Processing & Alpha Generation

signal-engine provides the statistical machinery to extract tradable signals from noisy financial time series.

Core Features

• Kalman Filtering: Recursive state estimation to identify the "latent" price trend in volatile regimes.
• Mean Reversion: Statistical Z-Score modeling for identifying overextended price moves.
• Stat-Arb Ready: Optimized for high-frequency signal calculation with minimal latency.

Usage

from signal_engine.nucleus.kalman_filter import KalmanPriceFilter
kf = KalmanPriceFilter()
clean_price = kf.update(raw_market_price)