Title Time Series Segmentation and Statistical Characterisation of the Spanish Stock Market Ibex-35 Index
Authors Cruz-Ramirez, M. , de la Paz-Marin, M. , PÉREZ ORTIZ, MARÍA, Hervas-Martinez, C.
External publication No
Means Lect. Notes Comput. Sci.
Scope Proceedings Paper
Nature Científica
JCR Quartile 4
SJR Quartile 2
SJR Impact 0.35400
Publication date 01/01/2014
ISI 000342836300007
Abstract The discovery of characteristic time series patterns is of fundamental importance in financial applications. Repetitive structures and common type of segments can provide very useful information of patterns in financial time series. In this paper, we introduce a time series segmentation and characterisation methodology combining a maximal likelihood optimisation procedure and a clustering technique to automatically segment common patterns from financial time series and address the problem of stock market prices trends. To do so, the obtained segments are transformed into a five-dimensional space composed of five typical statistical measures in order to group them according to their statistical properties. The experimental results show that it is possible to exploit the behaviour of the stock market Ibex-35 Spanish index (closing prices) to detect homogeneous segments of the time series.
Keywords Clustering; Ibex-35 index; segmentation; stock market; time series
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