# Efficient and Consistent Data-Driven Model Selection for Time Series

@inproceedings{Bardet2021EfficientAC, title={Efficient and Consistent Data-Driven Model Selection for Time Series}, author={Jean-Marc Bardet and Kamila Kare and William Kengne}, year={2021} }

This paper studies the model selection problem in a large class of causal time series models, which includes both the ARMA or AR(∞) processes, as well as the GARCH or ARCH(∞), APARCH, ARMA-GARCH and many others processes. We first study the asymptotic behavior of the ideal penalty that minimizes the risk induced by a quasi-likelihood estimation among a finite family of models containing the true model. Then, we provide general conditions on the penalty term for obtaining the consistency and…

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