IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v534y2019ics0378437119312968.html
   My bibliography  Save this article

Nonuniversality of the horizontal visibility graph in inferring series periodicity

Author

Listed:
  • Xiong, Hui
  • Shang, Pengjian
  • He, Jiayi

Abstract

The filter horizontal visibility graph (fHVg) algorithm was recently proposed to detect the hidden periodicity of intrinsically periodic series under the pollution of noise. In this work, we evaluate the reliability of this algorithm by taking into account the effect of finite size and noise pollution, and something intriguing is found. The fHVg is first applied to logistic map with period 2 and 3, and numerical results suggest that the accuracy of fHVg is not affected by the length of tested series. It is effective in analyzing very short time series but sensitive to extrinsic noises. However, the fHVg has unexpected limitations that lead to spurious results. It lacks generality and shows inability when applied to logistic map with period 4 and to the monthly mean temperature dataset from real-world.

Suggested Citation

  • Xiong, Hui & Shang, Pengjian & He, Jiayi, 2019. "Nonuniversality of the horizontal visibility graph in inferring series periodicity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    • Handle: RePEc:eee:phsmap:v:534:y:2019:i:c:s0378437119312968
    DOI: 10.1016/j.physa.2019.122234
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119312968
    Download Restriction: 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
    File URL: https://libkey.io/10.1016/j.physa.2019.122234?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Xiong, Hui & Shang, Pengjian & Bian, Songhan, 2017. "Detecting intrinsic dynamics of traffic flow with recurrence analysis and empirical mode decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 70-84.
    2. Lucas Lacasa & Ryan Flanagan, 2016. "Irreversibility of financial time series: a graph-theoretical approach," Papers 1601.01980, arXiv.org.
    3. Serinaldi, Francesco & Kilsby, Chris G., 2016. "Irreversibility and complex network behavior of stream flow fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 585-600.
    4. Xie, Wen-Jie & Zhou, Wei-Xing, 2011. "Horizontal visibility graphs transformed from fractional Brownian motions: Topological properties versus the Hurst index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3592-3601.
    5. Kantelhardt, Jan W. & Zschiegner, Stephan A. & Koscielny-Bunde, Eva & Havlin, Shlomo & Bunde, Armin & Stanley, H.Eugene, 2002. "Multifractal detrended fluctuation analysis of nonstationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 87-114.
    6. Chen, Wei-Shing, 2011. "Use of recurrence plot and recurrence quantification analysis in Taiwan unemployment rate time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(7), pages 1332-1342.
    7. Gao-Feng Gu & Wei-Xing Zhou, 2010. "Detrending moving average algorithm for multifractals," Papers 1005.0877, arXiv.org, revised Jun 2010.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jamshid Ardalankia & Jafar Askari & Somaye Sheykhali & Emmanuel Haven & G. Reza Jafari, 2020. "Mapping Coupled Time-series Onto Complex Network," Papers 2004.13536, arXiv.org, revised Aug 2020.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xiong, Hui & Shang, Pengjian & Xia, Jianan & Wang, Jing, 2018. "Time irreversibility and intrinsics revealing of series with complex network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 241-249.
    2. İşcanoğlu-Çekiç, Ayşegül & Gülteki̇n, Havva, 2019. "Are cross-correlations between Turkish Stock Exchange and three major country indices multifractal or monofractal?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 978-990.
    3. Ruan, Qingsong & Bao, Junjie & Zhang, Manqian & Fan, Limin, 2019. "The effects of exchange rate regime reform on RMB markets: A new perspective based on MF-DCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 122-134.
    4. Wang, Dong-Hua & Yu, Xiao-Wen & Suo, Yuan-Yuan, 2012. "Statistical properties of the yuan exchange rate index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(12), pages 3503-3512.
    5. Zhuang, Xiaoyang & Wei, Yu & Ma, Feng, 2015. "Multifractality, efficiency analysis of Chinese stock market and its cross-correlation with WTI crude oil price," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 101-113.
    6. Manimaran, P. & Narayana, A.C., 2018. "Multifractal detrended cross-correlation analysis on air pollutants of University of Hyderabad Campus, India," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 228-235.
    7. Horta, Paulo & Lagoa, Sérgio & Martins, Luís, 2014. "The impact of the 2008 and 2010 financial crises on the Hurst exponents of international stock markets: Implications for efficiency and contagion," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 140-153.
    8. Li Wang & Xing-Lu Gao & Wei-Xing Zhou, 2023. "Testing for intrinsic multifractality in the global grain spot market indices: A multifractal detrended fluctuation analysis," Papers 2306.10496, arXiv.org.
    9. Wang, Gang-Jin & Xie, Chi, 2013. "Cross-correlations between Renminbi and four major currencies in the Renminbi currency basket," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1418-1428.
    10. Ruan, Qingsong & Meng, Lu & Lv, Dayong, 2021. "Effect of introducing Bitcoin futures on the underlying Bitcoin market efficiency: A multifractal analysis," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
    11. Yudong Wang & Chongfeng Wu, 2013. "Efficiency of Crude Oil Futures Markets: New Evidence from Multifractal Detrending Moving Average Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 42(4), pages 393-414, December.
    12. Dutta, Srimonti & Ghosh, Dipak & Samanta, Shukla, 2014. "Multifractal detrended cross-correlation analysis of gold price and SENSEX," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 195-204.
    13. Yao, Can-Zhong & Liu, Cheng & Ju, Wei-Jia, 2020. "Multifractal analysis of the WTI crude oil market, US stock market and EPU," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    14. Mali, Provash & Mukhopadhyay, Amitabha & Singh, Gurmukh, 2016. "Multifractal detrended moving average analysis of particle density functions in relativistic nuclear collisions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 323-332.
    15. He, Shanshan & Wang, Yudong, 2017. "Revisiting the multifractality in stock returns and its modeling implications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 11-20.
    16. Chattopadhyay, Anirban & Khondekar, Mofazzal H. & Bhattacharjee, Anup Kumar, 2018. "Fractality and singularity in CME linear speed signal: Cycle 23," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 542-550.
    17. Zhou, Wei-Xing, 2012. "Finite-size effect and the components of multifractality in financial volatility," Chaos, Solitons & Fractals, Elsevier, vol. 45(2), pages 147-155.
    18. Fan, Qingju & Li, Dan, 2015. "Multifractal cross-correlation analysis in electricity spot market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 17-27.
    19. Zhou, Yuan-Wu & Liu, Jin-Long & Yu, Zu-Guo & Zhao, Zhi-Qin & Anh, Vo, 2014. "Fractal and complex network analyses of protein molecular dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 21-32.
    20. Wang, Fang & Wang, Lin & Chen, Yuming, 2022. "Multi-affine visible height correlation analysis for revealing rich structures of fractal time series," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:534:y:2019:i:c:s0378437119312968. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.