DocumentCode :
3065275
Title :
AIS for Trend Change Detection
Author :
Domaradzki, Andrzej
fYear :
2007
fDate :
28-30 June 2007
Firstpage :
161
Lastpage :
165
Abstract :
This article present outstanding results given by the new application of artificial immune systems in trend change detection in time series. Author´s system (GRASICA3), has been evaluated on a financial time series containing daily quotas of the main index of the Warsaw´s stock exchange (WIG) and additionally on a synthetic time series generated using the Monte Carlo method. Very good results which have been obtained (>60% of accuracy in trend change signals) are compared to results of other systems known from a bibliography, designed by Gutjahr and Kingdon. In the next stage the author provides a comparison of the GRASICA3 results to results given traditional statistical modeling methods such as, a very popular Box-Jenkins and Arima X-12 algorithms.
Keywords :
Monte Carlo methods; artificial life; software performance evaluation; stock markets; time series; GRASICA3 system; Monte Carlo method; Warsaw stock exchange; artificial immune systems; financial time series; statistical modeling; synthetic time series; system evaluation; trend change detection; trend change signals; Artificial immune systems; Bibliographies; Immune system; Lymphatic system; Microorganisms; Organisms; Proteins; Signal design; Stock markets; Viruses (medical);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Information Systems and Industrial Management Applications, 2007. CISIM '07. 6th International Conference on
Conference_Location :
Minneapolis, MN
Print_ISBN :
0-7695-2894-5
Type :
conf
DOI :
10.1109/CISIM.2007.10
Filename :
4273514
Link To Document :
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