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Quantile-Based Spectral Analysis in an Object-Oriented Framework and a Reference Implementation in R: The quantspec Package

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  • Kley, Tobias

Abstract

Quantile-based approaches to the spectral analysis of time series have recently attracted a lot of attention. Several methods for estimation have been proposed in the literature and their statistical properties were analyzed. Yet, so far, neither a systematic method for computation nor a comprehensive software implementation are available to date. This paper contains two main contributions. First, an extensible framework for quantile-based spectral analysis of time series is developed and documented using object-oriented models. A comprehensive, open source reference implementation of this framework is provided in the R package quantspec, which is available from the Comprehensive R Archive Network. The second contribution of the present paper is to provide a detailed tutorial, with worked examples, for this R package. A reader who is already familiar with quantile-based spectral analysis and whose primary interest is not the design of the quantspec package, but how to use it, can read the tutorial and worked examples (Sections 3 and 4) independently.

Suggested Citation

  • Kley, Tobias, 2016. "Quantile-Based Spectral Analysis in an Object-Oriented Framework and a Reference Implementation in R: The quantspec Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 70(i03).
    • Handle: RePEc:jss:jstsof:v:070:i03
    DOI: http://hdl.handle.net/10.18637/jss.v070.i03
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    References listed on IDEAS

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    1. Holger Dette & Marc Hallin & Tobias Kley & Stanislav Volgushev, 2011. "Of Copulas, Quantiles, Ranks and Spectra - An L1-Approach to Spectral Analysis," Working Papers ECARES ECARES 2011-038, ULB -- Universite Libre de Bruxelles.
    2. Zeileis, Achim & Grothendieck, Gabor, 2005. "zoo: S3 Infrastructure for Regular and Irregular Time Series," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i06).
    3. Tobias Kley & Stanislav Volgushev & Holger Dette & Marc Hallin, 2014. "Quantile Spectral Processes: Asymptotic Analysis and Inference," Working Papers ECARES ECARES 2014-07, ULB -- Universite Libre de Bruxelles.
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    Cited by:

    1. Stefan Birr & Stanislav Volgushev & Tobias Kley & Holger Dette & Marc Hallin, 2017. "Quantile spectral analysis for locally stationary time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1619-1643, November.
    2. Yuichi Goto & Tobias Kley & Ria Van Hecke & Stanislav Volgushev & Holger Dette & Marc Hallin, 2021. "The Integrated Copula Spectrum," Working Papers ECARES 2021-29, ULB -- Universite Libre de Bruxelles.
    3. Maghyereh, Aktham & Abdoh, Hussein, 2020. "Tail dependence between Bitcoin and financial assets: Evidence from a quantile cross-spectral approach," International Review of Financial Analysis, Elsevier, vol. 71(C).
    4. Stefan Birr & Holger Dette & Marc Hallin & Tobias Kley & Stanislav Volgushev, 2016. "On Wigner-Ville Spectra and the Unicity of Time-Varying Quantile-Based Spectral Densities," Working Papers ECARES ECARES 2016-38, ULB -- Universite Libre de Bruxelles.
    5. Zhang, Shibin, 2019. "Bayesian copula spectral analysis for stationary time series," Computational Statistics & Data Analysis, Elsevier, vol. 133(C), pages 166-179.
    6. Kołodziejczyk, Hanna, 2023. "Stablecoins as diversifiers, hedges and safe havens: A quantile coherency approach," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).
    7. Chen, Tianbo & Sun, Ying & Li, Ta-Hsin, 2021. "A semi-parametric estimation method for the quantile spectrum with an application to earthquake classification using convolutional neural network," Computational Statistics & Data Analysis, Elsevier, vol. 154(C).
    8. Kliber, Agata & Łęt, Blanka, 2022. "Degree of connectedness and the transfer of news across the oil market and the European stocks," Energy, Elsevier, vol. 239(PC).

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