Testing for serial independence: beyond the Portmanteau approach

Luca Bagnato, Lucio De Capitani, Antonio Punzo

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Portmanteau tests are typically used to test serial independence even if, by construction, they are generally powerful only in presence of pairwise dependence between lagged variables. In this paper we present a simple statistic defining a new serial independence test which is able to detect more general forms of dependence. In particular, differently from the Portmanteau tests, the resulting test is powerful also under a dependent process characterized by pairwise independence. A diagram, based on p-values from the proposed test, is introduced to investigate serial dependence. Finally, the effectiveness of the proposal is evaluated in a simulation study and with an application on financial data. Both show that the new test, used in synergy with the existing ones, helps in the identification of the true data generating process.
Original languageEnglish
Pages (from-to)219-238
Number of pages20
JournalTHE AMERICAN STATISTICIAN
DOIs
Publication statusPublished - 2018

Keywords

  • Serial dependence, Portmanteau approach, Nonlinear time series

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