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A new method to compare the spectral densities of two independent periodically correlated time series

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  • Mahmoudi, Mohammad Reza
  • Heydari, Mohammad Hossein
  • Roohi, Reza

Abstract

In some situations, for example in signal processing, economics, electronic, finance, and climatology, researchers wish to determine whether the two time series are generated by the same stochastic mechanism or their random behavior differs. In this work, the asymptotic distribution for the discrete Fourier transform of periodically correlated time series is applied to derive hypothesis testing for the equality of two periodically correlated time series. Then the Monte Carlo simulation study is provided to investigate the performance of proposed method.

Suggested Citation

  • Mahmoudi, Mohammad Reza & Heydari, Mohammad Hossein & Roohi, Reza, 2019. "A new method to compare the spectral densities of two independent periodically correlated time series," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 160(C), pages 103-110.
    • Handle: RePEc:eee:matcom:v:160:y:2019:i:c:p:103-110
    DOI: 10.1016/j.matcom.2018.12.008
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    References listed on IDEAS

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    1. Broszkiewicz-Suwaj, E & Makagon, A & Weron, R & Wyłomańska, A, 2004. "On detecting and modeling periodic correlation in financial data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(1), pages 196-205.
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    4. A. R. Nematollahi & A. R. Soltani & M. R. Mahmoudi, 2017. "Periodically correlated modeling by means of the periodograms asymptotic distributions," Statistical Papers, Springer, vol. 58(4), pages 1267-1278, December.
    5. Peter J. Diggle & Nicholas I. Fisher, 1991. "Nonparametric Comparison of Cumulative Periodograms," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 40(3), pages 423-434, November.
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    7. Franses, Philip Hans, 1996. "Periodicity and Stochastic Trends in Economic Time Series," OUP Catalogue, Oxford University Press, number 9780198774549, Decembrie.
    8. Mohammad Reza Mahmoudi & Mohsen Maleki, 2017. "A new method to detect periodically correlated structure," Computational Statistics, Springer, vol. 32(4), pages 1569-1581, December.
    9. A. R. Soltani & M. Azimmohseni, 2007. "Simulation of Real‐Valued Discrete‐Time Periodically Correlated Gaussian Processes with Prescribed Spectral Density Matrices," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(2), pages 225-240, March.
    10. D. S. Coates & P. J. Diggle, 1986. "Tests For Comparing Two Estimated Spectral Densities," Journal of Time Series Analysis, Wiley Blackwell, vol. 7(1), pages 7-20, January.
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    Cited by:

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    2. Mahmoudi, Mohammad Reza, 2021. "A computational technique to classify several fractional Brownian motion processes," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).

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