Autoregressive conditional proportion: A multiplicative‐error model for (0,1)‐valued time series
نویسندگان
چکیده
We propose a multiplicative autoregressive conditional proportion (ARCP) model for (0,1)-valued time series, in the spirit of GARCH (generalized heteroscedastic) and ACD (autoregressive duration) models. In particular, our underlying process is defined as product independent identically distributed (i.i.d.) sequence inverted mean, which, turn, depends on past reciprocal observations such way that larger than unity. The probability structure studied context stochastic recurrence equation theory, while estimation parameters performed with exponential quasi-maximum likelihood estimator (EQMLE). consistency asymptotic normality EQMLE are both established under general regularity assumptions. Finally, usefulness proposed illustrated two real datasets.
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ژورنال
عنوان ژورنال: Journal of Time Series Analysis
سال: 2023
ISSN: ['1467-9892', '0143-9782']
DOI: https://doi.org/10.1111/jtsa.12679