Siem Jan Koopman

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Andre LucasVrije Universiteit Amsterdam and Tinbergen InstituteVerified email at vu.nl
Neil ShephardFrank B. Baird Jr, Professor of Science, Dept of Economics & Dept of Statistics, Harvard UniversityVerified email at fas.harvard.edu
Marius OomsAssociate Professor of Econometrics VU University AmsterdamVerified email at feweb.vu.nl
Bernd SchwaabResearch Economist; European Central BankVerified email at ecb.int
Drew CrealUniversity of Notre DameVerified email at nd.edu
Rutger LitResearch fellow, VU AmsterdamVerified email at vu.nl
Michel van der WelProfessor, Erasmus University RotterdamVerified email at ese.eur.nl
Geert MestersUniversitat Pompeu Fabra, Barcelona GSE & Vrije Universiteit AmsterdamVerified email at upf.edu
virginie dordonnatRéseau de transport d'électricité, FranceVerified email at rte-france.com
Sunčica VujićUniversity of AntwerpVerified email at uantwerpen.be
M. Angeles CarneroUniversidad de AlicanteVerified email at ua.es
Desislava PetrovaBarcelona Institute for Global Health (ISGlobal)Verified email at isglobal.org
António RuaBanco de PortugalVerified email at bportugal.pt
Marcel ScharthUniversity of Sydney Business SchoolVerified email at sydney.edu.au
John AstonStatistical Laboratory, DPMMS, University of CambridgeVerified email at statslab.cam.ac.uk
Julia SchaumburgProfessor of Econometric Methods and Applications, Vrije Universiteit AmsterdamVerified email at vu.nl
Falk BräuningFederal Reserve Bank of BostonVerified email at bos.frb.org
Albert J. MenkveldVrije Universiteit AmsterdamVerified email at vu.nl
Eric ZivotProfessor of Economics, University of WashingtonVerified email at uw.edu
Marco RianiUniversity of ParmaVerified email at unipr.it

Siem Jan Koopman

Professor of Econometrics, Vrije Universiteit Amsterdam

Verified email at vu.nl - Homepage

Econometrics Time Series Financial Econometrics Forecasting Kalman filter


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Time series analysis by state space methods J Durbin, SJ Koopman OUP Oxford, 2012	5144	2012
STAMP 6.0: Structural time series analyser, modeller and predictor SJ Koopman, AC Harvey, JA Doornik, N Shephard London: Timberlake Consultants, 2000	1041	2000
Generalized autoregressive score models with applications D Creal, SJ Koopman, A Lucas Journal of Applied Econometrics 28 (5), 777-795, 2013	949	2013
A simple and efficient simulation smoother for state space time series analysis J Durbin, SJ Koopman Biometrika 89 (3), 603-616, 2002	834	2002
Forecasting daily variability of the S&P 100 stock index using historical, realised and implied volatility measurements SJ Koopman, B Jungbacker, E Hol Journal of Empirical Finance 12 (3), 445-475, 2005	758	2005
Statistical algorithms for models in state space using SsfPack 2.2 SJ Koopman, N Shephard, JA Doornik The Econometrics Journal 2 (1), 107-160, 1999	686	1999
Monte Carlo maximum likelihood estimation for non-Gaussian state space models J Durbin, SJ Koopman Biometrika 84 (3), 669-684, 1997	596	1997
An introduction to state space time series analysis JJF Commandeur, SJ Koopman Oxford University Press, USA, 2007	558	2007
Time series analysis of non-Gaussian observations based on state space models from both classical and Bayesian perspectives J Durbin, SJ Koopman Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2000	494	2000
Estimation of stochastic volatility models via Monte Carlo maximum likelihood G Sandmann, SJ Koopman Journal of Econometrics 87 (2), 271-301, 1998	471	1998
10 Structural time series models AC Harvey, N Shephard Elsevier 11, 261-302, 1993	355	1993
Forecasting hourly electricity demand using time-varying splines A Harvey, SJ Koopman Journal of the American Statistical Association 88 (424), 1228-1236, 1993	336	1993
A dynamic multivariate heavy-tailed model for time-varying volatilities and correlations D Creal, SJ Koopman, A Lucas Journal of Business & Economic Statistics 29 (4), 552-563, 2011	334	2011
Diagnostic checking of unobserved-components time series models AC Harvey, SJ Koopman Journal of Business & Economic Statistics 10 (4), 377-389, 1992	330	1992
Exact initial Kalman filtering and smoothing for nonstationary time series models SJ Koopman Journal of the American Statistical Association 92 (440), 1630-1638, 1997	323	1997
Periodic seasonal Reg-ARFIMA–GARCH models for daily electricity spot prices SJ Koopman, M Ooms, MA Carnero Journal of the American Statistical Association 102 (477), 16-27, 2007	322	2007
Disturbance smoother for state space models SJ Koopman Biometrika 80 (1), 117-126, 1993	307	1993
The stochastic volatility in mean model: empirical evidence from international stock markets SJ Koopman, E Hol Uspensky Journal of applied Econometrics 17 (6), 667-689, 2002	265	2002
Business and default cycles for credit risk SJ Koopman, A Lucas Journal of Applied Econometrics 20 (2), 311-323, 2005	230	2005
Analyzing the term structure of interest rates using the dynamic Nelson–Siegel model with time-varying parameters SJ Koopman, MIP Mallee, M Van der Wel Journal of Business & Economic Statistics 28 (3), 329-343, 2010	227	2010

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