Permutation transition entropy: Measuring the dynamical complexity of financial time series

Xiaojun Zhao, Mengfan Ji, Na Zhang and Pengjian Shang

Chaos, Solitons & Fractals, 2020, vol. 139, issue C

Abstract: In this paper, we propose a new approach to measure the dynamical complexity of a single time series. We characterize the changes of the states of the underlying system, by quantifying the Markov states transition between adjacent permutations. Unlike many static-complexity measures, the new method of permutation transition entropy (PTE) is able to identify the dynamical complexity with respect to the change of the temporal structure. With the numerical analyses, we show that the PTE can give the information that other methods, like the permutation entropy (PE), cannot. We apply the PTE method to the financial time series analysis, which reveals the existence of the momentum effect in the daily closing price and the daily trading volume of Chinese stock markets. It indicates that the dynamical complexity of these two indexes in stock markets is lower than that of the random time series. While the logarithm return and the logarithm change of trading volume show very similar PTE values with those of the random time series, which represents higher randomness.

Keywords: Permutation transition entropy; Dynamical complexity; Markov state transition; Financial time series analysis (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077920303611
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:139:y:2020:i:c:s0960077920303611

DOI: 10.1016/j.chaos.2020.109962

Access Statistics for this article

Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros

More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().