Visibility Graph Based Time Series Analysis

Mutua Stephen, Changgui Gu and Huijie Yang

PLOS ONE, 2015, vol. 10, issue 11, 1-19

Abstract: Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it’s microscopic and macroscopic behaviors. However, most proposed approaches lead to the construction of static networks consequently providing limited information on evolutionary behaviors. In the present paper we propose a method called visibility graph based time series analysis, in which series segments are mapped to visibility graphs as being descriptions of the corresponding states and the successively occurring states are linked. This procedure converts a time series to a temporal network and at the same time a network of networks. Findings from empirical records for stock markets in USA (S&P500 and Nasdaq) and artificial series generated by means of fractional Gaussian motions show that the method can provide us rich information benefiting short-term and long-term predictions. Theoretically, we propose a method to investigate time series from the viewpoint of network of networks.

Date: 2015
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0143015

DOI: 10.1371/journal.pone.0143015

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