Economics at your fingertips  

Analysis of crude oil markets with improved multiscale weighted permutation entropy

Hongli Niu, Jun Wang and Cheng Liu

Physica A: Statistical Mechanics and its Applications, 2018, vol. 494, issue C, 389-402

Abstract: Entropy measures are recently extensively used to study the complexity property in nonlinear systems. Weighted permutation entropy (WPE) can overcome the ignorance of the amplitude information of time series compared with PE and shows a distinctive ability to extract complexity information from data having abrupt changes in magnitude. Improved (or sometimes called composite) multi-scale (MS) method possesses the advantage of reducing errors and improving the accuracy when applied to evaluate multiscale entropy values of not enough long time series. In this paper, we combine the merits of WPE and improved MS to propose the improved multiscale weighted permutation entropy (IMWPE) method for complexity investigation of a time series. Then it is validated effective through artificial data: white noise and 1∕f noise, and real market data of Brent and Daqing crude oil. Meanwhile, the complexity properties of crude oil markets are explored respectively of return series, volatility series with multiple exponents and EEMD-produced intrinsic mode functions (IMFs) which represent different frequency components of return series. Moreover, the instantaneous amplitude and frequency of Brent and Daqing crude oil are analyzed by the Hilbert transform utilized to each IMF.

Keywords: Complexity; Weighted permutation entropy; Improved multiscale weighted permutation entropy (IMWPE); Ensemble EMD; Crude oil (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

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:

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().

Page updated 2019-01-19
Handle: RePEc:eee:phsmap:v:494:y:2018:i:c:p:389-402