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Estimation of multivariate asymmetric power GARCH models

Statistics Theory 2019-10-17 v2 Applications Machine Learning Statistics Theory

Abstract

It is now widely accepted that volatility models have to incorporate the so-called leverage effect in order to to model the dynamics of daily financial returns.We suggest a new class of multivariate power transformed asymmetric models. It includes several functional forms of multivariate GARCH models which are of great interest in financial modeling and time series literature. We provide an explicit necessary and sufficient condition to establish the strict stationarity of the model. We derive the asymptotic properties of the quasi-maximum likelihood estimator of the parameters. These properties are established both when the power of the transformation is known or is unknown. The asymptotic results are illustrated by Monte Carlo experiments. An application to real financial data is also proposed.

Keywords

Cite

@article{arxiv.1812.02061,
  title  = {Estimation of multivariate asymmetric power GARCH models},
  author = {Yacouba Boubacar Maïnassara and Othman Kadmiri and Bruno Saussereau},
  journal= {arXiv preprint arXiv:1812.02061},
  year   = {2019}
}
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