Quant Engine
Systematic trend-following powered by time-series momentum, volatility targeting, and regime detection — academic-grade quant for every public company.
Pro Feature
Unlock the Quant Engine
Multi-window momentum ranking, volatility-scaled signals, HMM regime prediction, and execution management — all running on standardized Finpoint data. Get it as part of Finpoint Pro.
- Composite momentum signals (1m, 3m, 12m windows)
- Volatility targeting with hysteresis deadband
- HMM regime detection (bull/bear market states)
- Weekly ranking updates via REST API
How it works
The Quant Engine implements time-series momentum (Moskowitz et al. 2012, Hurst et al. 2017) — a systematic trend-following strategy that ranks stocks by the strength and persistence of their price trends.
Multi-Window Momentum
Every ticker gets three volatility-scaled signals: 21-day, 63-day, and 252-day returns. The composite score is the equal-weighted average — catching both fast breakouts and slow-burn trends.
Hurst, Ooi & Pedersen (2017) — 137 years of data
Volatility Targeting
Positions are sized by inverse volatility — the most volatile names get smaller weights. A hysteresis deadband prevents whipsaw trades.
Moskowitz, Ooi & Pedersen (2012) — Journal of Financial Economics
Regime Detection
A Hidden Markov Model classifies the market into bull/bear states. The engine adjusts position sizing and signal thresholds based on the detected regime.