On the ARCH model with stationary liquidity
Document type :
Compte-rendu et recension critique d'ouvrage
Title :
On the ARCH model with stationary liquidity
Author(s) :
Voutilainen, Marko [Auteur]
Ilmonen, Pauliina [Auteur]
Torres, Soledad [Auteur]
Tudor, Ciprian [Auteur]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Viitasaari, Lauri [Auteur]
Ilmonen, Pauliina [Auteur]
Torres, Soledad [Auteur]
Tudor, Ciprian [Auteur]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Viitasaari, Lauri [Auteur]
Journal title :
Metrika
Pages :
195-224
Publisher :
Springer Verlag
Publication date :
2020-06-24
ISSN :
0026-1335
HAL domain(s) :
Mathématiques [math]
English abstract : [en]
Abstract The classical ARCH model together with its extensions have been widely applied in the modeling of financial time series. We study a variant of the ARCH model that takes account of liquidity given by a positive ...
Show more >Abstract The classical ARCH model together with its extensions have been widely applied in the modeling of financial time series. We study a variant of the ARCH model that takes account of liquidity given by a positive stationary process. We provide minimal assumptions that ensure the existence and uniqueness of the stationary solution for this model. Moreover, we give necessary and sufficient conditions for the existence of the autocovariance function. After that, we derive an AR(1) characterization for the stationary solution yielding Yule–Walker type quadratic equations for the model parameters. In order to define a proper estimation method for the model, we first show that the autocovariance estimators of the stationary solution are consistent under relatively mild assumptions. Consequently, we prove that the natural estimators arising out of the quadratic equations inherit consistency from the autocovariance estimators. Finally, we illustrate our results with several examples and a simulation study.Show less >
Show more >Abstract The classical ARCH model together with its extensions have been widely applied in the modeling of financial time series. We study a variant of the ARCH model that takes account of liquidity given by a positive stationary process. We provide minimal assumptions that ensure the existence and uniqueness of the stationary solution for this model. Moreover, we give necessary and sufficient conditions for the existence of the autocovariance function. After that, we derive an AR(1) characterization for the stationary solution yielding Yule–Walker type quadratic equations for the model parameters. In order to define a proper estimation method for the model, we first show that the autocovariance estimators of the stationary solution are consistent under relatively mild assumptions. Consequently, we prove that the natural estimators arising out of the quadratic equations inherit consistency from the autocovariance estimators. Finally, we illustrate our results with several examples and a simulation study.Show less >
Language :
Anglais
Popular science :
Non
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