Dynamic Regime Identification and Prediction Based on Observed Behavior in Electronic Marketplaces

Wolfgang Ketter

We present a method for an autonomous agent to identify dominant market conditions, such as oversupply or scarcity. The characteristics of economic regimes are learned from historic data and used, together with real-time observable information, to identify the current market regime and to forecast market changes. The approach is validated with data from the Trading Agent Competition for Supply Chain Management.

Subjects: 7.1 Multi-Agent Systems; 7.2 Software Agents

Submitted: Apr 5, 2005


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