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Price Trackers Inspired by Immune Memory

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  • William Wilson
  • Phil Birkin
  • Uwe Aickelin

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.

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File URL: http://arxiv.org/pdf/1004.3939
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Bibliographic Info

Paper provided by arXiv.org in its series Papers with number 1004.3939.

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Date of creation: Apr 2010
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Publication status: Published in Proceedings of the 5th International Conference on Artificial Immune Systems (ICARIS2006), Lecture Notes in Computer Science 4163, p362-375, 2006
Handle: RePEc:arx:papers:1004.3939

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Web page: http://arxiv.org/

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