Oil Price Trackers Inspired by Immune Memory

Wilson, William; Birkin, Phil; Aickelin, Uwe

Abstract

We outline initial concepts for an immune inspired algorithm to evaluate and predict oil price time series data. The proposed solution evolves a short term pool of trackers dynamically, with each member attempting to map trends and anticipate future price movements. Successful trackers feed into a long term memory pool that can generalise across repeating trend patterns. The resulting sequence of trackers, ordered in time, can be used as a forecasting tool. Examination of the pool of evolving trackers also provides valuable insight into the properties of the crude oil market.

Citation

Wilson, W., Birkin, P., & Aickelin, U. Oil Price Trackers Inspired by Immune Memory.

• Conference Name: Proceedings of the Workshop on Artificial Immune Systems and Immune System Modelling (AISB 2006)
• Deposit Date: Oct 22, 2007
• Peer Reviewed: Peer Reviewed
• Public URL: https://nottingham-repository.worktribe.com/output/1019776