Price Trackers Inspired by Immune Memory

Abstract. In this paper we outline initial concepts for an immune inspired algorithm to evaluate price time series data. The proposed solution evolves a short term pool of trackers dynamically through a process of proliferation and mutation, with each member attempting to map to trends in price movements. Successful trackers feed into a long term memory pool that can generalise across repeating trend patterns. Tests are performed to examine the algorithm's ability to successfully identify trends in a small data set. The influence of the long term memory pool is then examined. We find the algorithm is able to identify price trends presented successfully and efficiently.

• Type: Journal
• Year: 2010
• Where: CORR
• Authors: William O. Wilson, Phil Birkin, Uwe Aickelin
• Keywords: CORR 2010, Education, Immune Inspired Algorithm, Long Term Memory, Term Memory Pool