IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v387y2008i21p5246-5254.html
   My bibliography  Save this article

High frequency intrinsic modes in El Niño/Southern Oscillation Index

Author

Listed:
  • Petroni, Filippo
  • Ausloos, Marcel

Abstract

Recent daily data of the Southern Oscillation Index have been analyzed. The power spectrum indicates major intrinsic geophysical short periods. We find interesting “high frequency” oscillations at 24, 27, 37, 76, 100 and 365 days. In particular the 24 days peaks may correspond to the Branstator–Kushnir wave, the 27 days may be due to the moon effect rotation, the 37 days peaks are most probably related to the Madden and Julian Oscillation. It is not yet clear the explanations for the 76 days which may be associated with interseasonal oscillation in the tropical atmosphere; the 100 days could be resulting from a mere beat between the 37 and 27 periods, or the 76 and 365 days. We use these periods to reconstruct the signal and to produce a forecast for the next 9 months, at the time of writing. After cleansing the signal of those periodicities a detrended fluctuation analysis is performed to reveal the nature of the stochastic structures in the signal and whether specific correlation can be found. We study the evolution of the distribution of first return times, in particular between extreme events. A markedly significant difference from the expected distribution for uncorrelated events is found.

Suggested Citation

  • Petroni, Filippo & Ausloos, Marcel, 2008. "High frequency intrinsic modes in El Niño/Southern Oscillation Index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5246-5254.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:21:p:5246-5254
    DOI: 10.1016/j.physa.2008.05.021
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437108004512
    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.2008.05.021?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. Vandewalle, N. & Ausloos, M., 1997. "Coherent and random sequences in financial fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 246(3), pages 454-459.
    2. Ausloos, M, 2002. "Empirical Analysis of Time Series," MPRA Paper 28700, University Library of Munich, Germany.
    3. Ivanova, K & Ausloos, M, 1999. "Application of the detrended fluctuation analysis (DFA) method for describing cloud breaking," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 274(1), pages 349-354.
    4. Ausloos, M. & Petroni, F., 2007. "Tsallis non-extensive statistical mechanics of El Niño southern oscillation index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 721-736.
    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. Samuel T. Ogunjo, 2023. "The impact of the 2007–2008 global financial crisis on the multifractality of the Nigerian Stock Exchange," SN Business & Economics, Springer, vol. 3(1), pages 1-17, January.
    2. Huang, Xu & Maçaira, Paula Medina & Hassani, Hossein & Cyrino Oliveira, Fernando Luiz & Dhesi, Gurjeet, 2019. "Hydrological natural inflow and climate variables: Time and frequency causality analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 480-495.

    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. Yuan, Naiming & Fu, Zuntao & Mao, Jiangyu, 2010. "Different scaling behaviors in daily temperature records over China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(19), pages 4087-4095.
    2. Stavros-Richard G. Christopoulos & Nicholas V. Sarlis, 2017. "An Application of the Coherent Noise Model for the Prediction of Aftershock Magnitude Time Series," Complexity, Hindawi, vol. 2017, pages 1-27, February.
    3. Koçak, Kasım, 2009. "Examination of persistence properties of wind speed records using detrended fluctuation analysis," Energy, Elsevier, vol. 34(11), pages 1980-1985.
    4. Kavasseri, Rajesh G. & Nagarajan, Radhakrishnan, 2005. "A multifractal description of wind speed records," Chaos, Solitons & Fractals, Elsevier, vol. 24(1), pages 165-173.
    5. Shang, Pengjian & Lu, Yongbo & Kamae, Santi, 2008. "Detecting long-range correlations of traffic time series with multifractal detrended fluctuation analysis," Chaos, Solitons & Fractals, Elsevier, vol. 36(1), pages 82-90.
    6. Rotundo, G. & Ausloos, M. & Herteliu, C. & Ileanu, B., 2015. "Hurst exponent of very long birth time series in XX century Romania. Social and religious aspects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 109-117.
    7. Marcel Ausloos, 2013. "Econophysics: Comments on a Few Applications, Successes, Methods and Models," IIM Kozhikode Society & Management Review, , vol. 2(2), pages 101-115, July.
    8. Lavička, Hynek & Kracík, Jiří, 2020. "Fluctuation analysis of electric power loads in Europe: Correlation multifractality vs. Distribution function multifractality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    9. Petroni, Filippo & Rotundo, Giulia, 2008. "Effectiveness of measures of performance during speculative bubbles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(15), pages 3942-3948.
    10. Currenti, Gilda & Negro, Ciro Del & Lapenna, Vincenzo & Telesca, Luciano, 2005. "Fluctuation analysis of the hourly time variability of volcano-magnetic signals recorded at Mt. Etna Volcano, Sicily (Italy)," Chaos, Solitons & Fractals, Elsevier, vol. 23(5), pages 1921-1929.
    11. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2001. "Microscopic Models of Financial Markets," Papers cond-mat/0110354, arXiv.org.
    12. Kyaw, NyoNyo A. & Los, Cornelis A. & Zong, Sijing, 2006. "Persistence characteristics of Latin American financial markets," Journal of Multinational Financial Management, Elsevier, vol. 16(3), pages 269-290, July.
    13. Kononovicius, A., 2019. "Illusion of persistence in NBA 1995–2018 regular season data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 250-256.
    14. Johann Lussange & Ivan Lazarevich & Sacha Bourgeois-Gironde & Stefano Palminteri & Boris Gutkin, 2021. "Modelling Stock Markets by Multi-agent Reinforcement Learning," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 113-147, January.
    15. Vygintas Gontis & Aleksejus Kononovicius, 2014. "Consentaneous Agent-Based and Stochastic Model of the Financial Markets," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-12, July.
    16. Jiang, Lei & Zhang, Jiping & Liu, Xinwei & Li, Fei, 2016. "Multi-fractal scaling comparison of the Air Temperature and the Surface Temperature over China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 783-792.
    17. Domino, Krzysztof, 2012. "The use of the Hurst exponent to investigate the global maximum of the Warsaw Stock Exchange WIG20 index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 156-169.
    18. Zhang, Hong-Yan & Kang, Ming-Cui & Li, Jing-Qiang & Liu, Hai-Tao, 2017. "R/S analysis of reaction time in Neuron Type Test for human activity in civil aviation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 859-870.
    19. Struzik, Zbigniew R., 2001. "Wavelet methods in (financial) time-series processing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 296(1), pages 307-319.
    20. Lux, Thomas & Alfarano, Simone, 2016. "Financial power laws: Empirical evidence, models, and mechanisms," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 3-18.

    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:387:y:2008:i:21:p:5246-5254. 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.