Serial independence tests for innovations of conditional mean and variance models

Kilani Ghoudi, Bruno Rémillard

    Research output: Contribution to journalArticlepeer-review

    12 Citations (Scopus)

    Abstract

    In this paper, one studies the asymptotic behavior of empirical processes based on consecutive residuals of univariate conditional mean and variance models. These processes are then used to develop tests of serial independence of the innovations. Even if the limiting distributions of the empirical processes depend on unknown parameters, it is shown that a Monte Carlo method based on the so-called multipliers can be applied to estimate the P values of the proposed test statistics. A simulation study is carried out to demonstrate the effectiveness of the proposed tests and the behavior of the statistics is also studied under contiguous alternatives.

    Original languageEnglish
    Pages (from-to)3-26
    Number of pages24
    JournalTest
    Volume27
    Issue number1
    DOIs
    Publication statusPublished - Mar 1 2018

    Keywords

    • Bootstrap
    • Empirical copula
    • Empirical processes
    • GARCH models
    • Independence tests
    • Multipliers
    • Randomness
    • Residuals
    • Serial independence
    • Squared residuals

    ASJC Scopus subject areas

    • Statistics and Probability
    • Statistics, Probability and Uncertainty

    Fingerprint

    Dive into the research topics of 'Serial independence tests for innovations of conditional mean and variance models'. Together they form a unique fingerprint.

    Cite this