Time irreversibility is one of the most important properties of nonstationary time series. Complex time series often demonstrate even multiscale time irreversibility, such that not only the original but also coarse-grained time series are asymmetric over a wide range of scales. We study the multiscale time irreversibility of time series. In this paper, we develop a method called multiscale multifractal time irreversibility analysis (MMRA), which allows us to extend the description of time irreversibility to include the dependence on the segment size and statistical moments. We test the effectiveness of MMRA in detecting multifractality and time irreversibility of time series generated from delayed Henon map and binomial multifractal model. Then we employ our method to the time irreversibility analysis of stock markets in different regions. We find that the emerging market has higher multifractality degree and time irreversibility compared with developed markets. In this sense, the MMRA method may provide new angles in assessing the evolution stage of stock markets. (C) 2016 Elsevier B.V. All rights reserved.
机构:
Anhui Univ, Sch Math Sci, Hefei 230601, Peoples R China
Univ Sci & Technol China, Sch Management, Hefei 230026, Peoples R ChinaAnhui Univ, Sch Math Sci, Hefei 230601, Peoples R China
Chen, Yuwen
Zheng, Tingting
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Anhui Univ, Sch Math Sci, Hefei 230601, Peoples R ChinaAnhui Univ, Sch Math Sci, Hefei 230601, Peoples R China
机构:
Univ Pau, CATT, Pau, FranceUniv Pau, CATT, Pau, France
Bouoiyour, Jamal
Selmi, Refk
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Univ Pau, CATT, Pau, France
Univ Tunis El Manar, ERNA, Tunis, TunisiaUniv Pau, CATT, Pau, France
Selmi, Refk
Wohar, Mark E.
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Univ Nebraska, Coll Business Adm, 6708 Pine St, Omaha, NE 68182 USA
Loughborough Univ Technol, Sch Business & Econ, Loughborough LE11 3TU, Leics, EnglandUniv Pau, CATT, Pau, France