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The scaling of time series size towards detrended fluctuation analysis

Author

Listed:
  • Xiaolei Gao

    (School of Science, Beijing Jiaotong University, Beijing 100044, P. R. China)

  • Liwei Ren

    (School of Science, Beijing Jiaotong University, Beijing 100044, P. R. China)

  • Pengjian Shang

    (School of Science, Beijing Jiaotong University, Beijing 100044, P. R. China)

  • Guochen Feng

    (School of Science, Beijing Jiaotong University, Beijing 100044, P. R. China)

Abstract

In this paper, we introduce a modification of detrended fluctuation analysis (DFA), called multivariate DFA (MNDFA) method, based on the scaling of time series size N. In traditional DFA method, we obtained the influence of the sequence segmentation interval s, and it inspires us to propose a new model MNDFA to discuss the scaling of time series size towards DFA. The effectiveness of the procedure is verified by numerical experiments with both artificial and stock returns series. Results show that the proposed MNDFA method contains more significant information of series compared to traditional DFA method. The scaling of time series size has an influence on the auto-correlation (AC) in time series. For certain series, we obtain an exponential relationship, and also calculate the slope through the fitting function. Our analysis and finite-size effect test demonstrate that an appropriate choice of the time series size can avoid unnecessary influences, and also make the testing results more accurate.

Suggested Citation

  • Xiaolei Gao & Liwei Ren & Pengjian Shang & Guochen Feng, 2016. "The scaling of time series size towards detrended fluctuation analysis," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 27(11), pages 1-15, November.
    • Handle: RePEc:wsi:ijmpcx:v:27:y:2016:i:11:n:s0129183116501382
    DOI: 10.1142/S0129183116501382
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