Gene trajectory clustering for learning the stock market sectors

Authors:
Darie Moldovan;Gheorghe Cosmin Silaghi
Affiliations:
Babes Bolyai University, Business Information Systems Dept., Cluj-Napoca, Romania;Babes Bolyai University, Business Information Systems Dept., Cluj-Napoca, Romania
Venue:
ICANNGA'09 Proceedings of the 9th international conference on Adaptive and natural computing algorithms
Year:
2009

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Abstract

Hybrid Gene Trajectory Clustering (GTC) algorithm [1,2] proves to be a good candidate to cluster multi-dimensional noisy time series. In this paper we apply the hybrid GTC to learn the structure of the stock market and to infer interesting relationships out of closing prices data. We conclude that hybrid GTC can successfully identify homogeneous and stable stock clusters and these clusters can further help the investors.