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Aknouche, Abdelhakim (2013): Periodic autoregressive stochastic volatility. Published in: Statistical Inference for Stochastic Processes
Aknouche, Abdelhakim (2015): Unified quasi-maximum likelihood estimation theory for stable and unstable Markov bilinear processes. Published in: Nova Publisher Science (2015)
Aknouche, Abdelhakim and Al-Eid, Eid and Demouche, Nacer (2016): Generalized quasi-maximum likelihood inference for periodic conditionally heteroskedastic models.
Aknouche, Abdelhakim and Bendjeddou, Sara and Touche, Nassim (2016): Negative binomial quasi-likelihood inference for general integer-valued time series models. Forthcoming in: Journal of Time Series Analysis
Aknouche, Abdelhakim and Bentarzi, Wissam and Demouche, Nacer (2017): On periodic ergodicity of a general periodic mixed Poisson autoregression.
Aknouche, Abdelhakim and Demouche, Nacer (2018): Ergodicity conditions for a double mixed Poisson autoregression.
Aknouche, Abdelhakim and Demmouche, Nacer and Touche, Nassim (2018): Bayesian MCMC analysis of periodic asymmetric power GARCH models.
Aknouche, Abdelhakim and Francq, Christian (2018): Count and duration time series with equal conditional stochastic and mean orders.
Aknouche, Abdelhakim and Dimitrakopoulos, Stefanos and Touche, Nassim (2019): Integer-valued stochastic volatility.
Aknouche, Abdelhakim and Francq, Christian (2019): Two-stage weighted least squares estimator of the conditional mean of observation-driven time series models.
Aknouche, Abdelhakim and Almohaimeed, Bader and Dimitrakopoulos, Stefanos (2020): Periodic autoregressive conditional duration.
Aknouche, Abdelhakim and Almohaimeed, Bader and Dimitrakopoulos, Stefanos (2020): Forecasting transaction counts with integer-valued GARCH models.
Aknouche, Abdelhakim and Francq, Christian (2020): Stationarity and ergodicity of Markov switching positive conditional mean models.
Dimitrakopoulos, Stefanos and Tsionas, Mike G. and Aknouche, Abdelhakim (2020): Ordinal-response models for irregularly spaced transactions: A forecasting exercise.
