DocumentCode :
3367296
Title :
Comparison of Subsequence Pattern Matching Methods for Financial Time Series
Author :
Xueyuan Gong ; Yain-Whar Si
Author_Institution :
Dept. of Comput. & Inf. Sci., Univ. of Macau, Macau, China
fYear :
2013
fDate :
14-15 Dec. 2013
Firstpage :
154
Lastpage :
158
Abstract :
In contrast to general time series analysis, only a few numbers of studies are devoted to subsequence pattern matching methods for financial time series. In this paper, we compare the processing time and accuracy of three well-known pattern matching methods from financial time series domain and two pattern matching methods from general time series area. Our experiment was conducted on the historical data of Hang Seng Index (HSI) from Hong Kong Stock Market. Our experiment reveals that segmentation step and time distortion issues can significantly affect the performance of these methods.
Keywords :
pattern matching; stock markets; time series; HSI; Hang Seng index; Hong Kong stock market; financial time series domain; general time series analysis; processing time; segmentation step issues; subsequence pattern matching methods; time distortion issues; Accuracy; Equations; Euclidean distance; Mathematical model; Pattern matching; Time series analysis; financial time series; segmentation; subsequence pattern matching; technical pattern;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Security (CIS), 2013 9th International Conference on
Conference_Location :
Leshan
Print_ISBN :
978-1-4799-2548-3
Type :
conf
DOI :
10.1109/CIS.2013.39
Filename :
6746375
Link To Document :
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