Title :
Representing Financial Time Series Based on Important Extrema Points
Author :
Wu, Xueyan ; Huang, Daoping
Author_Institution :
Coll. of Autom. Sci. & Eng., South China Univ. of Technol., Guangzhou, China
Abstract :
This paper presents a novel method for financial time series representation. The method can generate accurate and effective representation and segmentation in different resolutions and get better experimental results on real stock data.
Keywords :
data mining; financial data processing; stock markets; time series; data mining; extrema points; financial time series; real stock data; Aggregates; Automation; Data mining; Educational institutions; Engineering management; Financial management; Information technology; Paper technology; Shape; Technology management; financial; representation; time series;
Conference_Titel :
Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on
Conference_Location :
Nanchang
Print_ISBN :
978-0-7695-3859-4
DOI :
10.1109/IITA.2009.127
