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Oil Price Trackers Inspired by Immune Memory

Wilson, William; Birkin, Phil; Aickelin, Uwe

Authors

William Wilson

Phil Birkin

Uwe Aickelin



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.

Peer Reviewed Peer Reviewed
APA6 Citation Wilson, W., Birkin, P., & Aickelin, U. Oil Price Trackers Inspired by Immune Memory
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf

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06aisb_wilson.pdf (20 Kb)
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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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