IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v460y2016icp283-293.html
   My bibliography  Save this article

Linear combination of power-law functions for detecting multiscaling using detrended fluctuation analysis

Author

Listed:
  • Echeverria, J.C.
  • Rodriguez, E.
  • Aguilar-Cornejo, M.
  • Alvarez-Ramirez, J.

Abstract

In many instances, the fluctuation function obtained from detrended fluctuation analysis (DFA) cannot be described by a uniform power-law function along scales. In fact, the manifestation of crossover scales may reflect the simultaneous action of different stochastic mechanisms displayed predominantly within certain scale ranges. This note proposes the use of a linear combination of power-law functions for adjusting DFA data. The idea is that each power-law function recast the dominance of certain stochastic mechanisms (e.g., the mean-reversion and long-term trends) at specific scale domains. Different values of the scaling exponents are numerically estimated by means of a nonlinear least-squares fitting of power-law functions. Examples of crude oil market and heart rate variability are discussed with some detail for illustrating the advantages of taking a linear combination of power-law functions for describing scaling behavior from DFA.

Suggested Citation

  • Echeverria, J.C. & Rodriguez, E. & Aguilar-Cornejo, M. & Alvarez-Ramirez, J., 2016. "Linear combination of power-law functions for detecting multiscaling using detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 283-293.
  • Handle: RePEc:eee:phsmap:v:460:y:2016:i:c:p:283-293
    DOI: 10.1016/j.physa.2016.05.029
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037843711630214X
    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.2016.05.029?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. Telesca, Luciano & Hattori, Katsumi, 2007. "Non-uniform scaling behavior in ultra-low-frequency (ULF) earthquake-related geomagnetic signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 522-528.
    2. Bessembinder, Hendrik, et al, 1995. "Mean Reversion in Equilibrium Asset Prices: Evidence from the Futures Term Structure," Journal of Finance, American Finance Association, vol. 50(1), pages 361-375, March.
    3. Alvarez-Ramirez, Jose & Alvarez, Jesus & Solis, Ricardo, 2010. "Crude oil market efficiency and modeling: Insights from the multiscaling autocorrelation pattern," Energy Economics, Elsevier, vol. 32(5), pages 993-1000, September.
    4. Gulich, Damián & Zunino, Luciano, 2014. "A criterion for the determination of optimal scaling ranges in DFA and MF-DFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 397(C), pages 17-30.
    5. Grech, Dariusz & Mazur, Zygmunt, 2013. "On the scaling ranges of detrended fluctuation analysis for long-term memory correlated short series of data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(10), pages 2384-2397.
    6. Fama, Eugene F., 1998. "Market efficiency, long-term returns, and behavioral finance," Journal of Financial Economics, Elsevier, vol. 49(3), pages 283-306, September.
    7. Telesca, Luciano & Lovallo, Michele & Kanevski, Mikhail, 2016. "Power spectrum and multifractal detrended fluctuation analysis of high-frequency wind measurements in mountainous regions," Applied Energy, Elsevier, vol. 162(C), pages 1052-1061.
    8. Wang, Yudong & Wei, Yu & Wu, Chongfeng, 2010. "Auto-correlated behavior of WTI crude oil volatilities: A multiscale perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5759-5768.
    9. Alvarez-Ramirez, J. & Echeverria, J.C. & Rodriguez, E., 2012. "Temporal variations of long-term correlations in seismic activity fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(6), pages 2261-2267.
    10. Martina, Esteban & Rodriguez, Eduardo & Escarela-Perez, Rafael & Alvarez-Ramirez, Jose, 2011. "Multiscale entropy analysis of crude oil price dynamics," Energy Economics, Elsevier, vol. 33(5), pages 936-947, September.
    11. Erjia Ge & Yee Leung, 2013. "Detection of crossover time scales in multifractal detrended fluctuation analysis," Journal of Geographical Systems, Springer, vol. 15(2), pages 115-147, April.
    Full references (including those not matched with items on IDEAS)

    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. Zhang, Guofu & Li, Jingjing, 2018. "Multifractal analysis of Shanghai and Hong Kong stock markets before and after the connect program," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 611-622.
    2. Gu, Rongbao & Zhang, Bing, 2016. "Is efficiency of crude oil market affected by multifractality? Evidence from the WTI crude oil market," Energy Economics, Elsevier, vol. 53(C), pages 151-158.
    3. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Commodity futures and market efficiency," Energy Economics, Elsevier, vol. 42(C), pages 50-57.
    4. Hasan, Rashid & Mohammad, Salim M., 2015. "Multifractal analysis of Asian markets during 2007–2008 financial crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 746-761.
    5. Hasan, Rashid & Mohammed Salim, M., 2017. "Power law cross-correlations between price change and volume change of Indian stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 620-631.
    6. Gulich, Damián & Baglietto, Gabriel & Rozenfeld, Alejandro F., 2018. "Temporal correlations in the Vicsek model with vectorial noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 590-604.
    7. Liu, Li & Wan, Jieqiu, 2012. "A study of Shanghai fuel oil futures price volatility based on high frequency data: Long-range dependence, modeling and forecasting," Economic Modelling, Elsevier, vol. 29(6), pages 2245-2253.
    8. Gulich, Damián & Zunino, Luciano, 2014. "A criterion for the determination of optimal scaling ranges in DFA and MF-DFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 397(C), pages 17-30.
    9. Aurelio F. Bariviera & Luciano Zunino & M. Belen Guercio & Lisana B. Martinez & Osvaldo A. Rosso, 2015. "Efficiency and credit ratings: a permutation-information-theory analysis," Papers 1509.01839, arXiv.org.
    10. George P. Papaioannou & Christos Dikaiakos & Akylas C. Stratigakos & Panos C. Papageorgiou & Konstantinos F. Krommydas, 2019. "Testing the Efficiency of Electricity Markets Using a New Composite Measure Based on Nonlinear TS Tools," Energies, MDPI, vol. 12(4), pages 1-30, February.
    11. Darko Stosic & Dusan Stosic & Irena Vodenska & H. Eugene Stanley & Tatijana Stosic, 2021. "A new look at calendar anomalies: Multifractality and day of the week effect," Papers 2106.06164, arXiv.org.
    12. Sensoy, Ahmet & Hacihasanoglu, Erk, 2014. "Time-varying long range dependence in energy futures markets," Energy Economics, Elsevier, vol. 46(C), pages 318-327.
    13. Itami, A.S. & Antonio, F.J. & Mendes, R.S., 2015. "Very prolonged practice in block of trials: Scaling of fitness, universality and persistence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 82-89.
    14. Liu, Li & Chen, Ching-Cheng & Wan, Jieqiu, 2013. "Is world oil market “one great pool”?: An example from China's and international oil markets," Economic Modelling, Elsevier, vol. 35(C), pages 364-373.
    15. Li, Daye & Nishimura, Yusaku & Men, Ming, 2016. "Why the long-term auto-correlation has not been eliminated by arbitragers: Evidences from NYMEX," Energy Economics, Elsevier, vol. 59(C), pages 167-178.
    16. Yuan, Ying & Zhuang, Xin-tian & Liu, Zhi-ying & Huang, Wei-qiang, 2014. "Analysis of the temporal properties of price shock sequences in crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 235-246.
    17. Zhou, Weijie & Dang, Yaoguo & Gu, Rongbao, 2013. "Efficiency and multifractality analysis of CSI 300 based on multifractal detrending moving average algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1429-1438.
    18. Morales Martínez, Jorge Luis & Segovia-Domínguez, Ignacio & Rodríguez, Israel Quiros & Horta-Rangel, Francisco Antonio & Sosa-Gómez, Guillermo, 2021. "A modified Multifractal Detrended Fluctuation Analysis (MFDFA) approach for multifractal analysis of precipitation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    19. Wang, Yudong & Wu, Chongfeng, 2012. "What can we learn from the history of gasoline crack spreads?: Long memory, structural breaks and modeling implications," Economic Modelling, Elsevier, vol. 29(2), pages 349-360.
    20. García-Carranco, Sergio M. & Bory-Reyes, Juan & Balankin, Alexander S., 2016. "The crude oil price bubbling and universal scaling dynamics of price volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 60-68.

    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:460:y:2016:i:c:p:283-293. 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.