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Finding Hidden Pattern of Financial Time Series Based on Score Matrix in Sequence Alignment

Yong Shi, Ye-Ran Tang, Wen Long, Ying-Jie Tian and Wen-Ning Yang
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Yong Shi: School of Economics & Management, University of Chinese Academy of Sciences, Beijing 100190 P.R. China; Research Center on Fictitious Economy & Data Science, Chinese Academy of Sciences, Beijing, 100190 P.R. China; Key Laboratory of Big Data Mining & Knowledge Management, Chinese Academy of Sciences, Beijing, 100190 P.R. China; College of Information Science and Technology, University of Nebraska at Omaha, Omaha, NE 68182, USA
Ye-Ran Tang: School of Economics & Management, University of Chinese Academy of Sciences, Beijing 100190 P.R. China; Research Center on Fictitious Economy & Data Science, Chinese Academy of Sciences, Beijing, 100190 P.R. China; Key Laboratory of Big Data Mining & Knowledge Management, Chinese Academy of Sciences, Beijing, 100190 P.R. China
Wen Long: School of Economics & Management, University of Chinese Academy of Sciences, Beijing 100190 P.R. China; Research Center on Fictitious Economy & Data Science, Chinese Academy of Sciences, Beijing, 100190 P.R. China; Key Laboratory of Big Data Mining & Knowledge Management, Chinese Academy of Sciences, Beijing, 100190 P.R. China
Ying-Jie Tian: School of Economics & Management, University of Chinese Academy of Sciences, Beijing 100190 P.R. China; Research Center on Fictitious Economy & Data Science, Chinese Academy of Sciences, Beijing, 100190 P.R. China; Key Laboratory of Big Data Mining & Knowledge Management, Chinese Academy of Sciences, Beijing, 100190 P.R. China
Wen-Ning Yang: School of Economics & Management, University of Chinese Academy of Sciences, Beijing 100190 P.R. China; Research Center on Fictitious Economy & Data Science, Chinese Academy of Sciences, Beijing, 100190 P.R. China; Key Laboratory of Big Data Mining & Knowledge Management, Chinese Academy of Sciences, Beijing, 100190 P.R. China

Asian Economic and Financial Review, 2018, vol. 8, issue 12, 1439-1456

Abstract: This paper applies sequence alignment method of bioinformatics to financial analysis to find hidden pattern from financial markets. Results of simulation suggest that sequence alignment method can be used to identify key points to inset, delete and replace data in time series, to find lead-lag relationship between two time series, and to analyze matching patterns. We further propose a new score matrix named similarity-oriented matrix which is designed based on the characteristics of financial time series, and apply it to China?s stock market. The empirical analysis verifies the validity of our proposed score matrix, and tests the sensitivity for different threshold values of symbols definition.

Keywords: Sequence alignment; Score matrix; Financial time series. (search for similar items in EconPapers)
JEL-codes: G17 C65 (search for similar items in EconPapers)
Date: 2018
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