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Latent variable analysis and partial correlation graphs for multivariate time series

Fried, Roland; Didelez, Vanessa - 2003

We investigate the possibility of exploiting partial correlation graphs for identifying interpretable latent variables underlying a multivariate time series. It is shown how the collapsibility and separation properties of partial correlation graphs can be used to understand the relation between...

Persistent link: https://www.econbiz.de/10010306285

Panel intensity models with latent factors: An application to the trading dynamics on the foreign exchange market

Nolte, Ingmar; Voev, Valeri - 2007

We develop a panel intensity model, with a time varying latent factor, which captures the influence of unobserved time … & Hautsch (2006) to panel duration data. We show how to estimate the model parameters by a simulated maximum likelihood … behavioral biases and discuss implications for portfolio theory. …

Persistent link: https://www.econbiz.de/10010266949

Statistical tests and estimators of the rank of a matrix and their applications in econometric modelling

Camba-Méndez, Gonzalo; Kapetanios, George - 2008

Testing and estimating the rank of a matrix of estimated parameters is key in a large variety of econometric modelling scenarios. This paper describes general methods to test for and estimate the rank of a matrix, and provides details on a variety of modelling scenarios in the econometrics...

Persistent link: https://www.econbiz.de/10011604896

Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models

Liesenfeld, Roman; Richard, Jean-François - 2004

In this paper Efficient Importance Sampling (EIS) is used to perform a classical and Bayesian analysis of univariate and multivariate Stochastic Volatility (SV) models for financial return series. EIS provides a highly generic and very accurate procedure for the Monte Carlo (MC) evaluation of...

Persistent link: https://www.econbiz.de/10010296235

Dynamic Factor Models for Multivariate Count Data: An Application to Stock-Market Trading Activity

Jung, Robert; Liesenfeld, Roman; Richard, Jean-François - 2008

We propose a dynamic factor model for the analysis of multivariate time series count data. Our model allows for idiosyncratic as well as common serially correlated latent factors in order to account for potentially complex dynamic interdependence between series of counts. The model is estimated...

Persistent link: https://www.econbiz.de/10010296304

A two-factor model for electricity prices with dynamic volatility

Schlüter, Stephan - 2009

The wavelet transform is used to identify a biannual and an annual seasonality in the Phelix Day Peak and to separate the long-term trend from its short-term motion. The short-term/long-term model for commodity prices of Schwartz & Smith (2000) is applied but generalised to account for weekly...

Persistent link: https://www.econbiz.de/10010299753

Likelihood Functions for State Space Models with Diffuse Initial Conditions

Francke, Marc K.; Koopman, Siem Jan; de Vos, Aart - 2008

State space models with nonstationary processes and fixed regression effects require a state vector with diffuse initial conditions. Different likelihood functions can be adopted for the estimation of parameters in time series models with diffuse initial conditions. In this paper we consider...

Persistent link: https://www.econbiz.de/10010325962

A multivariate long-memory model with structural breaks

Caporale, Guglielmo Maria; Gil-Alana, Luis A. - 2007

This paper introduces a multivariate long-memory model with structural breaks. In the proposed framework, time series exhibit possibly fractional orders of integration which are allowed to be different in each subsample. The break date is endogenously determined using a procedure which minimises...

Persistent link: https://www.econbiz.de/10010264093

An inflated Multivariate Integer Count Hurdle model: An application to bid and ask quote dynamics

Bien, Katarzyna; Nolte, Ingmar; Pohlmeier, Winfried - 2007

In this paper we develop a model for the conditional inflated multivariate density of integer count variables with domain Zn. Our modelling framework is based on a copula approach and can be used for a broad set of applications where the primary characteristics of the data are: (i) discrete...

Persistent link: https://www.econbiz.de/10010266935

Fitting high-dimensional copulae to data

Okhrin, Ostap - 2010

This paper make an overview of the copula theory from a practical side. We consider different methods of copula … Gaussian copulae but also Hierarchical Archimedean Copulae. Afterwards we provide an empirical part to support the theory. …

Persistent link: https://www.econbiz.de/10010270716

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