Multiscale horizontal visibility entropy: Measuring the temporal complexity of financial time series

Xiaojun Zhao and Pengyuan Zhang

Physica A: Statistical Mechanics and its Applications, 2020, vol. 537, issue C

Abstract: In this paper, we propose a horizontal visibility entropy (HVE) to measure the temporal complexity of non-stationary financial time series. It is a graphic and information-theoretic approach. By transforming the time series into a horizontal visibility graph (HVG), the dynamics of the underlying systems can be traced out through the topology structure of the graph. Then, we use a multiscale analysis of the Shannon entropy to characterize the complexity of time series under a range of time scales. The new method is free of any pre-requisite of additional parameters on estimating the probability distribution of continuous time series, which, therefore, has the advantages of robustness, high repeatability, and low requirement on the data length. We also compare our new method with the permutation entropy (PE), and apply it to financial time series analysis, which gives some new results.

Keywords: Horizontal visibility entropy; Multiscale analysis; Complexity; Node degree; Financial time series (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:537:y:2020:i:c:s0378437119315250

DOI: 10.1016/j.physa.2019.122674

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