English

Price Trackers Inspired by Immune Memory

Artificial Intelligence 2010-07-05 v1 Neural and Evolutionary Computing Data Analysis, Statistics and Probability Portfolio Management

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.

Cite

@article{arxiv.1004.3939,
  title  = {Price Trackers Inspired by Immune Memory},
  author = {William Wilson and Phil Birkin and Uwe Aickelin},
  journal= {arXiv preprint arXiv:1004.3939},
  year   = {2010}
}

Comments

14 pages, 5 figures, 3 tables, 5th International Conference on Artificial Immune Systems (ICARIS2006)

R2 v1 2026-06-21T15:13:35.588Z