1. Introduction

Financial markets, particularly in crypto and high-volatility equities, are characterized by rapid regime shifts, low signal-to-noise ratios, and strong path dependency in short timeframes. Traditional technical indicators and generic machine learning models often fail to adapt quickly enough to these conditions.

ZKSeer addresses this gap by focusing on a narrow but high-value problem: accurate, interpretable short-horizon flow prediction.

Core principles#

The system is built around three core principles:

• Custom-trained models rather than prompted generalist LLMs
• Exclusive use of public market data
• Complete trade context on every forecast (target + range + invalidation)