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

Business School, Dublin City University, 9 Dublin, Ireland
Econometrics 2019, 7(4), 48; https://doi.org/10.3390/econometrics7040048
Received: 9 August 2019 / Revised: 9 December 2019 / Accepted: 10 December 2019 / Published: 16 December 2019
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. View Full-Text
Keywords: multiplicative error model; non-negative valued time series; conditional variance dynamics; zero-inflated mixture distribution multiplicative error model; non-negative valued time series; conditional variance dynamics; zero-inflated mixture distribution
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Kawakatsu, H. Jointly Modeling Autoregressive Conditional Mean and Variance of Non-Negative Valued Time Series. Econometrics 2019, 7, 48.

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