Sequence outlier detection based on chaos theory and its application on stock market

Authors:
Chi Xie;Zuo Chen;Xiang Yu
Affiliations:
College of Business Administration, Hunan University, Changsha, Hunan, P.R. China;College of Business Administration, Hunan University, Changsha, Hunan, P.R. China;College of Business Administration, Hunan University, Changsha, Hunan, P.R. China
Venue:
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
Year:
2006

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Abstract

There are many observable factors that could influence and determine the time series. The dynamic equations of their interaction are always nonlinear, sometimes chaotic. This paper applied phase space reconstruction method to map time series into multi-dimension space based on chaos theory. Extracted from multi-dimension phase space by the method of sequential deviation detection, outlier set was used to construct a decision tree in order to identify the kinds of outliers. According to the results of decision tree, a trading strategy was set up and applied to Chinese stock market. The results show that, even in bear market, the strategy dictated by decision tree brought in considerable yield.