Tuesday March 5  2013
13.00
Scuola Normale Superiore
Aula Bianchi

Federico Poloni
Dipartimento di Informatica – Università di Pisa
Giacomo Sbrana
Rouen Business School

Abstract

We present an algorithm to estimate the parameters of multivariate ARMA, GARCH and stochastic volatility models. The approach is based on a moment estimator; a similar approach has already been suggested in literature for univariate GARCH but its generalization to multivariate models requires some more linear algebra machinery, especially in the field of matrix equations.
The resulting estimator is extremely fast to compute, in comparison to maximum-likelihood approaches. We also discuss methods to regularize and improve this estimate.