Phase distribution and phase correlation of financial time series

Ming Chya Wu, Ming Chang Huang, Hai Chin Yu, Thomas C. Chiang

Research output: Contribution to journalArticlepeer-review

40 Scopus citations

Abstract

The scaling, phase distribution, and phase correlation of financial time series are investigated based on the Dow Jones Industry Average and NASDAQ 10-min intraday data for a period from 1 Aug. 1997 to 31 Dec. 2003. The returns of the two indices are shown to have nice scaling behaviors and belong to stable distributions according to the criterion of Lévy's α stable distribution condition. An approach catching characteristic features of financial time series based on the concept of instantaneous phase is further proposed to study the phase distribution and correlation. Analysis of the phase distribution concludes that return time series fall into a class which is different from other nonstationary time series. The correlation between returns of the two indices probed by the distribution of phase difference indicates that there was a remarkable change of trading activities after the event of the 9/11 attack, and this change persisted in later trading activities.

Original languageEnglish
Article number016118
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume73
Issue number1
DOIs
StatePublished - Jan 2006

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