1992 …2020

Research output per year

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Research Output

Long-term forecasting of El Niño events via dynamic factor simulations

Li, M., Koopman, S. J., Lit, R. & Petrova, D., 2020, In : Journal of Econometrics. 214, 1, p. 46-66 21 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Multiyear statistical prediction of ENSO enhanced by the tropical Pacific observing system

Petrova, D., Ballester, J., Koopman, S. J. & Rodó, X., 1 Jan 2020, In : Journal of Climate. 33, 1, p. 163-174 12 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Nonlinear autoregressive models with optimality properties

Blasques, F., Koopman, S. J. & Lucas, A., 2 Jul 2020, In : Econometric Reviews. 39, 6, p. 559-578 20 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access

Partially censored posterior for robust and efficient risk evaluation

Borowska, A., Hoogerheide, L., Koopman, S. J. & van Dijk, H. K., 1 Jan 2020, (Accepted/In press) In : Journal of Econometrics. 217, 2, p. 335-355

Research output: Contribution to JournalArticleAcademicpeer-review

The dynamic factor network model with an application to international trade

Bräuning, F. & Koopman, S. J., Jun 2020, In : Journal of Econometrics. 216, 2, p. 494-515 22 p.

Research output: Contribution to JournalArticleAcademicpeer-review

2019

Accelerating score-driven time series models

Blasques, F., Gorgi, P. & Koopman, S. J., 2019, In : Journal of Econometrics. 212, 2, p. 359-376 18 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Bayesian Risk Forecasting for Long Horizons

Borowska, A., Hoogerheide, L. F. & Koopman, S. J., 2019, 018/III ed., Amsterdam: Tinbergen Institute, 40 p. (TI Discussion Paper Series; vol. 2019, no. 018/III).

Research output: Working paperAcademic

Forecasting economic time series using score-driven dynamic models with mixed-data sampling

Gorgi, P., Koopman, S. J. & Li, M., 2019, In : International Journal of Forecasting. 35, 4, p. 1735-1747 13 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Forecasting football match results in national league competitions using score-driven time series models

Koopman, S. J. & Lit, R., Apr 2019, In : International Journal of Forecasting. 35, 2, p. 797-809 13 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Modified efficient importance sampling for partially non-Gaussian state space models

Koopman, S. J., Lit, R. & Nguyen, T. M., 1 Feb 2019, In : Statistica Neerlandica. 73, 1, p. 44-62 19 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access

Sensitivity of large dengue epidemics in Ecuador to long-lead predictions of El Niño

Petrova, D., Lowe, R., Stewart-Ibarra, A., Ballester, J., Koopman, S. J. & Rodó, X., 1 Mar 2019, (Accepted/In press) In : Climate Services. 15, p. 1-9 9 p., 100096.

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access

The analysis and forecasting of tennis matches by using a high dimensional dynamic model

Gorgi, P., Koopman, S. J. & Lit, R., 2019, In : Journal of the Royal Statistical Society. Series A: Statistics in Society. 182, 4, p. 1393-1409 17 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access

Trend analysis of the airborne fraction and sink rate of anthropogenically released CO2

Bennedsen, M., Hillebrand, E. & Jan Koopman, S., 26 Sep 2019, In : Biogeosciences. 16, 18, p. 3651-3663 13 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access
2018

A Time-Varying Parameter Model for Local Explosions

Blasques Albergaria Amaral, F., Koopman, S. J. & Nientker, M. H. C., 2018, Amsterdam: Tinbergen Institute, 39 p. (TI Discussion Paper Series; vol. 18-088/III).

Research output: Working paperAcademic

Bayesian dynamic modeling of high-frequency integer price changes

Barra, I., Borowska, A. & Koopman, S. J., 1 Jun 2018, In : Journal of Financial Econometrics. 16, 3, p. 384-424 41 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Dynamic discrete copula models for high-frequency stock price changes

Koopman, S. J., Lit, R., Lucas, A. & Opschoor, A., Nov 2018, In : Journal of Applied Econometrics. 33, 7, p. 966-985 20 p., 33.

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access

Feasible invertibility conditions and maximum likelihood estimation for observation-driven models

Blasques, F., Gorgi, P., Koopman, S. J. & Wintenberger, O., Mar 2018, In : Electronic Journal of Statistics. 12, 1, p. 1019-1052 34 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access

Forecasting economic time series using score-driven dynamic models with mixed-data sampling

Gorgi, P. & Koopman, S. J., 2018, Amsterdam: Tinbergen Institute, 25 p. (TI Discussion Paper Series; vol. 18, no. 026/III).

Research output: Working paperAcademic

Missing Observations in Observation-Driven Time Series Models

Blasques Albergaria Amaral, F., Gorgi, P. & Koopman, S. J., 2018, 013/III ed., Amsterdam: Tinbergen Institute, 39 p. (TI Discussion Paper Series; vol. 2018, no. 013/III).

Research output: Working paperAcademic

The analysis and forecasting of ATP tennis matches using a high-dimensional dynamic model

Gorgi, P., Koopman, S. J. & Lit, R., 2018, Amsterdam: Tinbergen Institute, 18 p. (TI Discussion Paper Series; vol. 18, no. 009/III).

Research output: Working paperAcademic

Unobserved Components with Stochastic Volatility in U.S. Inflation: Estimation and Signal Extraction

Li, M. & Koopman, S. J., 2018, Amsterdam: Tinbergen Institute, 37 p. (TI Discussion Paper Series; vol. 18, no. 027/III).

Research output: Working paperAcademic

2017

Empirical Bayes Methods for Dynamic Factor Models

Koopman, S. J. & Mesters, G., 2017, In : Review of Economics and Statistics. 99, 3, p. 486-498 13 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access

Forecasting Football Match Results in National League Competitions Using Score-Driven Time Series Models

Koopman, S. J. & Lit, R., 2017, Amsterdam: Tinbergen Institute, 42 p. (TI Discussion Paper Series; vol. 17, no. 062/III).

Research output: Working paperAcademic

Global Credit Risk: World, Country and Industry Factors

Schwaab, B., Koopman, S. J. & Lucas, A., 2017, In : Journal of Applied Econometrics. 32, 2, p. 296-317 22 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Improving the Long-Lead Predictability of El Nino Using a Novel Forecasting Scheme Based on a Dynamic Components Mode

Petrova, D., Koopman, S. J., Ballester, J. & Rodo, X., 2017, In : Climate Dynamics. 48, 3-4, p. 1249–1276 28 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Intraday Stochastic Volatility in Discrete Price Changes: the Dynamic Skellam Model

Koopman, S. J., Lit, R. & Lucas, A., 2017, In : Journal of the American Statistical Association. 112, 520, p. 1490-1503 14 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access

Joint Bayesian Analysis of Parameters and States in Nonlinear, Non-Gaussian State Space Models

Barra, I., Hoogerheide, L. F., Koopman, S. J. & Lucas, A., 2017, In : Journal of Applied Econometrics. 32, 5, p. 1003-1026 24 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Testing for parameter instability across different modeling frameworks

Calvori, F., Creal, D., Koopman, S. J. & Lucas, A., 2017, In : Journal of Financial Econometrics. 15, 2, p. 223-246 24 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Time Varying Transition Probabilities for Markov Regime Switching Models

Bazzi, M., Blasques Albergaria Amaral, F., Koopman, S. J. & Lucas, A., 2017, In : Journal of Time Series Analysis. 38, 3, p. 458–478 21 p.

Research output: Contribution to JournalArticleAcademicpeer-review

2016

Bayesian Dynamic Modeling of High-Frequency Integer Price Changes

Barra, I. & Koopman, S. J., 2016, Amsterdam: Tinbergen Institute, 52 p. (TI Discussion Paper; no. 16-028/III).

Research output: Working paperProfessional

Feasible Invertibility Conditions and Maximum Likelihood Estimation for Observation-Driven Models

Blasques, F., Gorgi, P. G., Koopman, S. J. & Wintenberger, O., 2016, Amsterdam: Tinbergen Institute, 34 p. (TI Discussion Paper; no. 16-082/III).

Research output: Working paperProfessional

Forecasting and nowcasting economic growth in the euro area using factor models

Hindrayanto, A. I. W., Koopman, S. J. & de Winter, J., 2016, In : International Journal of Forecasting. 32, 4, p. 1284-1305

Research output: Contribution to JournalArticleAcademicpeer-review

In-Sample Confidence Bands and Out-of-Sample Forecast Bands for Time-Varying Parameters in Observation Driven Models

Blasques, F., Koopman, S. J., Lasak, K. A. & Lucas, A., 2016, In : International Journal of Forecasting. 32, 3, p. 875-887

Research output: Contribution to JournalArticleAcademicpeer-review

Intervention time series analysis of crime rates: The case of sentence reform in Virginia

Vujic, S., Commandeur, J. J. F. & Koopman, S. J., 2016, In : Economic Modelling. 57, p. 311-323

Research output: Contribution to JournalArticleAcademicpeer-review

Measuring Financial Cycles in a Model-Based Analysis: Empirical Evidence for the United States and the Euro Area

Galati, E. B. G., Hindrayanto, A. I. W., Koopman, S. J. & Vlekke, M., 2016, In : Economics Letters. 145, p. 83-87

Research output: Contribution to JournalArticleAcademicpeer-review

Model-based Business Cycle and Financial Cycle Decomposition for Europe and the U.S.

Koopman, S. J., Lit, R. & Lucas, A., 2016, Amsterdam: Tinbergen Institute, 19 p. (TI Discussion Series; no. 16-051/IV).

Research output: Working paperProfessional

Model-based Business Cycle and Financial Cycle Decomposition for Europe and the U.S., Chapter 6

Koopman, S. J., Lit, R. & Lucas, A., 2016, Systemic Risk Tomography: Signals, Measurement and Transmission Channels. Billio, M., Pelizzon, L. & Savona, R. (eds.). London: ISTE-Elsevier

Research output: Chapter in Book / Report / Conference proceedingChapterAcademic

Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models

Mesters, G., Koopman, S. J. & Ooms, M., 2016, In : Econometric Reviews. 35, 4, p. 659-687

Research output: Contribution to JournalArticleAcademicpeer-review

Predicting time-varying parameters with parameter-driven and observation-driven models

Koopman, S. J., Lucas, A. & Scharth, M., 2016, In : Review of Economics and Statistics. 98, 1, p. 97-110

Research output: Contribution to JournalArticleAcademicpeer-review

Realized Wishart-GARCH: A Score-driven Multi-Asset Volatility Model

Hansen, R. R., Janus, P. & Koopman, S. J., 2016, Amsterdam: Tinbergen Institute, 36 p. (TI Discussion Series; no. 16-061/III).

Research output: Working paperProfessional

Spillover dynamics for systemic risk measurement using spatial financial time series models

Blasques, F., Koopman, S. J., Lucas, A. & Schaumburg, J., 2016, In : Journal of Econometrics. 195, 2, p. 211-223

Research output: Contribution to JournalArticleAcademicpeer-review

The Dynamic Factor Network Model with an Application to Global Credit-Risk

Brauning, F. U. & Koopman, S. J., 2016, Amsterdam: Tinbergen Institute, 47 p. (TI Discussion Papers; no. 105/III).

Research output: Working paperProfessional

The Information in Systemic Risk Rankings

Nucera, F., Schwaab, B., Koopman, S. J. & Lucas, A., 2016, In : Journal of Empirical Finance. 38A, September, p. 461-475

Research output: Contribution to JournalArticleAcademicpeer-review

Weighted Maximum Likelihood for Dynamic Factor Analysis and Forecasting with Mixed Frequency Data

Blasques Albergaria Amaral, F., Koopman, S. J., Mallee, M. I. P. & Zhang, Z., 2016, In : Journal of Econometrics. 193, 2, p. 405-417

Research output: Contribution to JournalArticleAcademicpeer-review

2015

Advances in Econometrics - Conference on Dynamic Factor Models

Hillebrand, E. (ed.) & Koopman, S. J. (ed.), 2015, Bingley: Emerald Group. (Advances in Econometrics; no. Vol. 35)

Research output: Book / ReportBook editingAcademic

A Note on "Continuous Invertibility and Stable QML Estimation of the EGARCH(1,1) Model"

Blasques, F., Gorgi, P. G., Koopman, S. J. & Wintenberger, O., 2015, Amsterdam: Tinbergen Institute, 10 p. (TI Discussion Paper; no. 15-131/III).

Research output: Working paperProfessional