What We Do
Markets Are Full of Beliefs That Don't Hold Up
Most investment decisions are still driven by intuition, narrative, and outdated heuristics. Popular market beliefs persist not because they're true, but because no one tests them rigorously. The result: strategies built on assumptions that don't survive contact with real data.
We exist to close that gap. PolQuant applies rigorous quantitative methods to test market beliefs, identify what actually works, and build systematic approaches grounded in evidence - not stories.
Evidence-Based Research & Technology
We subject every hypothesis to exhaustive out-of-sample testing with realistic transaction cost models, slippage assumptions, and market impact estimates. Strategies that survive this process are fundamentally different from those built on overfitted, frictionless simulations.
Our research and technology serve independent operators, family offices, and institutional allocators who want evidence, not opinions - people who treat investing as a research problem.
Research & Hypothesis Testing
Rigorous testing of market beliefs across US equities - from factor premia to microstructure effects - with full out-of-sample validation.
Data Infrastructure
Proprietary data pipelines for cleaning, normalizing, and enriching market data - including alternative data sources - built for research speed and production reliability.
Machine Learning & Analytics
ML pipelines with proper cross-validation, regime detection, and signal processing. Built to avoid overfitting - not to manufacture results.
Execution Technology
Execution infrastructure that models realistic transaction costs, slippage, and market impact. If a strategy doesn't survive these frictions, we say so.