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
Drew CrealUniversity of Illinois Urbana-ChampaignVerified email at illinois.edu
Marius OomsAssociate Professor of Econometrics VU University AmsterdamVerified email at feweb.vu.nl
Bernd SchwaabResearch Economist; European Central BankVerified email at ecb.int
Rutger LitResearch fellow, VU AmsterdamVerified email at vu.nl
Michel van der WelProfessor, Erasmus University RotterdamVerified email at ese.eur.nl
Desislava PetrovaBarcelona Institute for Global Health (ISGlobal)Verified email at isglobal.org
Sunčica VujićUniversity of AntwerpVerified email at uantwerpen.be
Geert MestersUniversitat Pompeu Fabra, Barcelona GSE & Vrije Universiteit AmsterdamVerified email at upf.edu
M. Angeles CarneroUniversidad de AlicanteVerified email at ua.es
virginie dordonnatRéseau de transport d'électricité, FranceVerified email at rte-france.com
Marcel ScharthUniversity of Sydney Business SchoolVerified email at sydney.edu.au
António RuaBanco de PortugalVerified email at bportugal.pt
Julia SchaumburgProfessor of Econometric Methods and Applications, Vrije Universiteit AmsterdamVerified email at vu.nl
John AstonStatistical Laboratory, DPMMS, University of CambridgeVerified email at statslab.cam.ac.uk
Albert J. MenkveldVrije Universiteit AmsterdamVerified email at vu.nl
Falk BräuningFederal Reserve Bank of BostonVerified email at bos.frb.org
Mengheng LiUniversity of Technology SydneyVerified email at uts.edu.au
Eric ZivotProfessor of Economics, University of WashingtonVerified email at uw.edu

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 Oxford University Press (UK), 2012	5660	2012
Generalized autoregressive score models with applications D Creal, SJ Koopman, A Lucas Journal of applied econometrics 28 (5), 777-795, 2013	1147	2013
STAMP 6.0: Structural time series analyser, modeller and predictor SJ Koopman, AC Harvey, JA Doornik, N Shephard London: Timberlake Consultants, 2000	1063	2000
A simple and efficient simulation smoother for state space time series analysis J Durbin, SJ Koopman Biometrika 89 (3), 603-616, 2002	907	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	796	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	689	1999
Monte Carlo maximum likelihood estimation for non-Gaussian state space models J Durbin, SJ Koopman Biometrika 84 (3), 669-684, 1997	619	1997
An introduction to state space time series analysis JJF Commandeur, SJ Koopman Oxford university press, 2007	608	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	528	2000
Estimation of stochastic volatility models via Monte Carlo maximum likelihood G Sandmann, SJ Koopman Journal of Econometrics 87 (2), 271-301, 1998	499	1998
10 structural time series models AC Harvey, N Shephard Elsevier 11, 261-302, 1993	373	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	370	2011
Forecasting hourly electricity demand using time-varying splines A Harvey, SJ Koopman Journal of the American Statistical Association 88 (424), 1228-1236, 1993	350	1993
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	346	2007
Diagnostic checking of unobserved-components time series models AC Harvey, SJ Koopman Journal of Business & Economic Statistics 10 (4), 377-389, 1992	335	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	332	1997
Disturbance smoother for state space models SJ Koopman Biometrika 80 (1), 117-126, 1993	311	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	276	2002
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	251	2010
Fast filtering and smoothing for multivariate state space models SJ Koopman, J Durbin Journal of time series analysis 21 (3), 281-296, 2000	240	2000

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