Three-factor profile analysis with GARCH innovations

Pui-Lam Leung, Wing-Keung Wong*

*Corresponding author for this work

    Research output: Contribution to journalJournal articlepeer-review

    8 Citations (Scopus)
    21 Downloads (Pure)


    The technique of ANOVA has been widely used in economics and finance where the observations are usually time-dependent but the model itself is treated as independent in time. In this paper, we extend an ANOVA model by relaxing the assumption of independence in time. We further relax the assumption of homoskedasticity in the traditional profile analysis by introducing GARCH innovations in our proposed profile analysis that allows for both autoregressive and moving average components in the heteroskedastic variance to display a high degree of persistence. We reprise the model with regards to the issue of American depository receipts by relaxing the time-dependence assumption that has been ignored in the literature. Applying our model, we find that the returns from the stocks and the American depository receipts are time-dependent and hence the traditional ANOVA cannot fully explore the time effect from the data.

    Original languageEnglish
    Pages (from-to)1-8
    Number of pages8
    JournalMathematics and Computers in Simulation
    Issue number1
    Early online date13 Jan 2007
    Publication statusPublished - Feb 2008

    Scopus Subject Areas

    • Theoretical Computer Science
    • Computer Science(all)
    • Numerical Analysis
    • Modelling and Simulation
    • Applied Mathematics

    User-Defined Keywords

    • American depository receipts
    • ANOVA
    • GARCH model
    • MANOVA
    • Profile analysis
    • Time-dependence
    • Treatment


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