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Why frequency matters for unit root testing

Boswijk, Herman Peter; Klaassen, Franc - 2004 - Rev.

recent work on unit root and cointegration testing based non-Gaussian likelihood functions. The essential idea is that such …

Persistent link: https://www.econbiz.de/10011342578

Pseudo-variance quasi-maximum likelihood estimation of semiparametric time series models

Armillotta, Mirko; Gorgi, Paolo - 2023

We propose a novel estimation approach for a general class of semi-parametric time series models where the conditional … are available in the literature. Furthermore, the testing approach can be used to build specification tests for parametric …

Persistent link: https://www.econbiz.de/10014380737

Score-driven time-varying parameter models with splinebased densities

Brummelen, Janneke van; Gorgi, Paolo; Koopman, Siem Jan - 2025

We develop a score-driven time-varying parameter model where no particular parametric error distribution needs to be specified. The proposed method relies on a versatile spline-based density, which produces a score function that follows a natural cubic spline. This flexible approach nests the...

Persistent link: https://www.econbiz.de/10015198647

Measuring financial cycles in a model-based analysis : empirical evidence for the United States and the euro area

Galati, Gabriele; Hindrayanto, Irma; Koopman, Siem Jan; … - 2016

We adopt an unobserved components time series model to extract financial cycles for the United States and the five largest euro area countries over the period 1970 to 2014. We find that credit, the credit-to-GDP ratio and house prices have medium-term cycles which share a few common statistical...

Persistent link: https://www.econbiz.de/10011456728

On the correlations in linearized multivariate stochastic volatility models

Moussa, Karim - 2025

In the analysis of multivariate stochastic volatility models, many estimation procedures begin by transforming the data …

Persistent link: https://www.econbiz.de/10015333113

The analysis of stochastic volatility in the presence of daily realised measures

Koopman, Siem Jan; Scharth, Marcel - 2011

Persistent link: https://www.econbiz.de/10010191086

Maximum likelihood estimation for generalized autoregressive score models

Blasques, Francisco; Koopman, Siem Jan; Lucas, André - 2014

We study the strong consistency and asymptotic normality of the maximum likelihood estimator for a class of time series models driven by the score function of the predictive likelihood. This class of nonlinear dynamic models includes both new and existing observation driven time series models....

Persistent link: https://www.econbiz.de/10010250505

Maximum likelihood estimation for correctly specified generalized autoregressive score models : feedback effects, contraction conditions and asymptotic properties

Blasques, Francisco; Koopman, Siem Jan; Lucas, André - 2014

The strong consistency and asymptotic normality of the maximum likelihood estimator in observation-driven models usually requires the study of the model both as a filter for the time-varying parameter and as a data generating process (DGP) for observed data. The probabilistic properties of the...

Persistent link: https://www.econbiz.de/10010364739

An hourly periodic state space model for modelling French national electricity load

Dordonnat, V.; Koopman, Siem Jan; Ooms, Marius; … - 2008

We present a model for hourly electricity load forecasting based on stochastically time-varying processes that are designed to account for changes in customer behaviour and in utility production efficiencies. The model is periodic: it consists of different equations and different parameters for...

Persistent link: https://www.econbiz.de/10011373810

Likelihood functions for state space models with diffuse initial conditions

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

initial conditions. Different likelihood functions can be adopted for the estimation of parameters in time series models with … diffuse likelihood can not be used generally for parameter estimation. Our newly proposed marginal likelihood function is … likelihood function for the estimation of parameters in linear time series models. The results in our paper confirm the earlier …

Persistent link: https://www.econbiz.de/10011374403