Trend Extraction and Similarity Matching of Financial Time Series Based on EMD Method

Author

Jia, Suling ; Guo, Yanqin ; Wang, Qiang ; Zhang, Jian

Author_Institution

Sch. of Econ. & Manage., Beijing Univ. of Aeronaut. & Astronaut., Beijing, China

Volume

4

fYear

2009

fDate

March 31 2009-April 2 2009

Firstpage

526

Lastpage

530

Abstract

Data Mining of time series is a very important part of DM (Data Mining).This article proposes a trend extraction method of financial time series which are non-stationary and non-linear. And this article also gives the definition of trend of time series based on different time intervals and the criterion to measure the precision of the trend extracted. Experiments of trend extraction based on EMD method are conducted and the result verifies the effectiveness of EMD method in trend extraction of financial time series.

Keywords

data mining; financial data processing; pattern matching; time series; EMD method; data mining; empirical mode decomposition; financial time series; similarity matching; trend extraction method; Computer science; Data engineering; Data mining; Engineering management; Extraterrestrial measurements; Financial management; Frequency; Stock markets; Time measurement; Time series analysis; EMD Method; Financial Time Series; Similarity Matching; Trend Extraction;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Information Engineering, 2009 WRI World Congress on

Conference_Location

Los Angeles, CA

Print_ISBN

978-0-7695-3507-4

Type

conf

DOI

10.1109/CSIE.2009.654

Filename

5171052