Traditional equity factor models are mostly static. Markets are not. New drivers appear fast and can dominate volatility before they show up in standard risk models.

Agitprop builds dynamic equity risk factors by combining quant methods with signals extracted from large generative AI models. Agitprop products are designed to integrate into existing risk and portfolio infrastructures. We provide dynamic factor data that plugs into your existing workflows, with clear factor definitions based on a robust methodology.

Factor definitions - human-readable descriptions suitable for internal documentation, plus stable identifiers for tracking over time.
Stock-level exposures - exposure vectors per factor for a given universe, suitable for attribution, constraints, and monitoring.
Factor time series - time series intended for analysis, monitoring, and regime detection.
Risk calculations - inputs needed for portfolio risk decomposition and scenario analysis.

Find out more at www.agitprop.ai

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