In this paper we show how to simulate and estimate a COGARCH(p,q) model in the R package pkg{yuima}. Several routines for simulation and estimation are introduced. In particular, for the generation of a COGARCH(p,q) trajectory, the user can choose between two alternative schemes. The first is based on the Euler discretization of the stochastic differential equations that identify a COGARCH(p,q) model while the second considers the explicit solution of the equations defining the variance process. Estimation is based on the matching of the empirical with the theoretical autocorrelation function. Three different approaches are implemented: minimization of the mean squared error, minimization of the absolute mean error and the generalized method of moments where the weighting matrix is continuously updated. Numerical examples are given in order to explain methods and classes used in the yuima package.

COGARCH(p,q) : Simulation and Inference with yuima Package / S.M. Iacus, L. Mercuri, E. Rroji. - In: JOURNAL OF STATISTICAL SOFTWARE. - ISSN 1548-7660. - 80:(2017 Aug 28), pp. 1-49. [10.18637/jss.v080.i04]

COGARCH(p,q) : Simulation and Inference with yuima Package

S.M. Iacus
Primo
;
L. Mercuri
;
2017

Abstract

In this paper we show how to simulate and estimate a COGARCH(p,q) model in the R package pkg{yuima}. Several routines for simulation and estimation are introduced. In particular, for the generation of a COGARCH(p,q) trajectory, the user can choose between two alternative schemes. The first is based on the Euler discretization of the stochastic differential equations that identify a COGARCH(p,q) model while the second considers the explicit solution of the equations defining the variance process. Estimation is based on the matching of the empirical with the theoretical autocorrelation function. Three different approaches are implemented: minimization of the mean squared error, minimization of the absolute mean error and the generalized method of moments where the weighting matrix is continuously updated. Numerical examples are given in order to explain methods and classes used in the yuima package.
COGARCH(p,q) model, Inference, yuima package
Settore SECS-S/06 - Metodi mat. dell'economia e Scienze Attuariali e Finanziarie
Settore SECS-S/01 - Statistica
28-ago-2017
ott-2016
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/458206
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