Algorithmic Strategy Inference

Algorithmic strategy inference is the practice of identifying the trading patterns and execution logic of automated market participants by analyzing their historical trade data and order book activity. By applying statistical methods and machine learning, researchers can determine whether an algorithm is a market maker, a trend follower, or an arbitrageur.

This involves clustering trades to identify execution signatures, such as iceberg orders or specific latency-sensitive behaviors. Understanding these strategies allows other participants to anticipate market moves and adjust their own positioning accordingly.

It is a core component of competitive market microstructure analysis, helping traders optimize their execution quality. This inference provides a clearer picture of the competitive landscape and the behavioral dynamics driving liquidity in digital asset markets.