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Testing Serial Independence via Density-Based Measures of Divergence

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Abstract

This article reviews some nonparametric serial independence tests based on measures of divergence between densities. Among others, the well-known Kullback–Leibler, Hellinger, Tsallis, and Rosenblatt divergences are analyzed. Moreover, their copula-based version is taken into account. Via a wide simulation study, the performances of the considered serial independence tests are compared under different settings. Both single-lag and multiple-lag testing procedures are investigated to find out the best “omnibus” solution.

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Authors and Affiliations

  1. Dipartimento di Discipline Matematiche, Finanza Matematica e Econometria, Università Cattolica del Sacro Cuore, Via Necchi 9, 20123, Milano, Italy

    Luca Bagnato

  2. Dipartimento di Statistica e Metodi Quantitativi, Università di Milano-Bicocca, Via Bicocca degli Arcimboldi 8, 20126, Milano, Italy

    Lucio De Capitani

  3. Dipartimento di Economia e Impresa, Università di Catania, Corso Italia 55, 95129, Catania, Italy

    Antonio Punzo

Authors
  1. Luca Bagnato
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  2. Lucio De Capitani
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  3. Antonio Punzo
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Correspondence to Antonio Punzo.

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Bagnato, L., De Capitani, L. & Punzo, A. Testing Serial Independence via Density-Based Measures of Divergence. Methodol Comput Appl Probab 16, 627–641 (2014). https://doi.org/10.1007/s11009-013-9320-4

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  • DOI: https://doi.org/10.1007/s11009-013-9320-4

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