Three-factor profile analysis with GARCH innovations

  • Authors:
  • Pui-Lam Leung;Wing-Keung Wong

  • Affiliations:
  • Department of Statistics, The Chinese University of Hong Kong, China;Risk Management Institute and Department of Economics, National University of Singapore, Block S16, Level 5, 6 Science Drive 2, Singapore 117546, Singapore

  • Venue:
  • Mathematics and Computers in Simulation
  • Year:
  • 2008

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Abstract

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.