Title: Nonlinear time series modelling
Description:
The nature of many real phenomena in physics,
economics and finance is inherently non-linear. In this framework, classical
time series models based on the linearity assumption are likely to fail in the
task of providing an adequate description of the dynamic structure of the
phenomena under study. This consideration has contributed to the increasing
interest in non-linear time series models which has characterized the last two
decades. At the same, the research in this field has also been greatly
stimulated by the recent advances in data collection and computing technologies.
The rapidly evolving field of non-linear models for time series is offering a
large amount of new models and techniques. Within this, much attention has been
dedicated to some specific families of models which have been found to be
particularly useful in real applications. Successful examples include, among the
others, the class of ARCH models and their generalizations, the Regime Switching
models, together with their multivariate extensions. Even if, in these years,
some important issues related to the statistical analysis of non-linear time
series have been successfully dealt with, there are still many open problems
which are currently under study. The emphasis is on model selection, model
specification, stochastic properties, such as stationarity and ergodicity,
estimation, generation of multi-step ahead forecasts and evaluation of their
properties.
We will cover methodological and computational aspects of non-linear time series
analysis as well as empirical applications to real case studies.
Focus:
Models for the conditional mean
Models for the conditional variance
Stochastic Properties
Model selection
Estimation and testing
Diagnostics
Recent developments in forecasting
Forecast combination and evaluation
Fat tails
Empirical Applications
Co-Chairs:
Alessandra Amendola
Department of Economics and Statistics
University of Salerno
84084 Fisciano (SA) - Italy
Tel: +39 089962207
Fax: +39 089962049
E-mail: alamendola@unisa.it
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Siem Jan Koopman
Faculty of Economics and Business Administration,
Vrije Universiteit Amsterdam,
De Boelelaan 1105, NL 1081 HV Amsterdam
The Netherlands
Tel: +31 20 444 60 19
Fax: +31 20 444 60 20
E-mail: s.j.koopman@feweb.vu.nl |
Christian Francq
University Lille 3
Domaine Universitaire du Pont de Bois, BP 149
59653 Villeneuve d'Ascq Cedex
France
Tel: +33 3 20 41 60 00
Fax: +33 3 20 91 91 71
E-mail: freancqniv-lille3.fr |
Wai-Sum Chan,
Department of Statistics & Actuarial Science
The University of Hong Kong
Pokfulam Road, Hong Kong
Tel: +852 2857 8318
Fax: +852 2858 9041
E-mail:
chanws@hku.hk
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