Genetic Algorithms and Genetic Programming in Computational Finance
Genetic Algorithms and Genetic Programming in Computational Finance
AINE: An Immunological Approach to Data Mining
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
The application of antigenic search techniques to time series forecasting
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Learning and optimization using the clonal selection principle
IEEE Transactions on Evolutionary Computation
Motif detection inspired by immune memory
ICARIS'07 Proceedings of the 6th international conference on Artificial immune systems
Review Article: Recent Advances in Artificial Immune Systems: Models and Applications
Applied Soft Computing
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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.