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Jointly Modeling Autoregressive Conditional Mean and Variance of Non-Negative Valued Time Series

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  • Hiroyuki Kawakatsu

    (Business School, Dublin City University, 9 Dublin, Ireland)

Abstract

This paper considers observation driven models with conditional mean and variance dynamics for non-negative valued time series. The motivation is to relax the restriction imposed on the higher order moment dynamics in standard multiplicative error models driven only by the conditional mean dynamics. The empirical fit of a zero inflated mixture distribution is assessed with trade duration data with a large fraction of zero observations. All authors have read and agreed to the published version of the manuscript.

Suggested Citation

  • Hiroyuki Kawakatsu, 2019. "Jointly Modeling Autoregressive Conditional Mean and Variance of Non-Negative Valued Time Series," Econometrics, MDPI, vol. 7(4), pages 1-19, December.
    • Handle: RePEc:gam:jecnmx:v:7:y:2019:i:4:p:48-:d:298380
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    References listed on IDEAS

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