Aknouche, Abdelhakim and Francq, Christian (2018): Count and duration time series with equal conditional stochastic and mean orders.
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Abstract
We consider a positivevalued time series whose conditional distribution has a timevarying mean, which may depend on exogenous variables. The main applications concern count or duration data. Under a contraction condition on the mean function, it is shown that stationarity and ergodicity hold when the mean and stochastic orders of the conditional distribution are the same. The latter condition holds for the exponential family parametrized by the mean, but also for many other distributions. We also provide conditions for the existence of marginal moments and for the geometric decay of the betamixing coefficients. We give conditions for consistency and asymptotic normality of the Exponential QuasiMaximum Likelihood Estimator (QMLE) of the conditional mean parameters. Simulation experiments and illustrations on series of stock market volumes and of greenhouse gas concentrations show that the multiplicativeerror form of usual duration models deserves to be relaxed, as allowed in the present paper.
Item Type:  MPRA Paper 

Original Title:  Count and duration time series with equal conditional stochastic and mean orders 
English Title:  Count and duration time series with equal conditional stochastic and mean orders 
Language:  English 
Keywords:  Absolute regularity, Autoregressive Conditional Duration, Count time series models, Distance correlation, Ergodicity, Exponential QMLE, Integervalued GARCH, Mixing. 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C13  Estimation: General C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C18  Methodological Issues: General C  Mathematical and Quantitative Methods > C5  Econometric Modeling C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C58  Financial Econometrics 
Item ID:  97392 
Depositing User:  Prof. Abdelhakim Aknouche 
Date Deposited:  12 Dec 2019 02:02 
Last Modified:  12 Dec 2019 02:02 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/97392 
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Count and duration time series with equal conditional stochastic and mean orders. (deposited 29 Dec 2018 17:08)
 Count and duration time series with equal conditional stochastic and mean orders. (deposited 12 Dec 2019 02:02) [Currently Displayed]