Siem Jan Koopman

Vrije Universiteit Amsterdam - School of Business and Economics

Professor Econometrics

De Boelelaan 1105

Amsterdam, 1081 HV

Netherlands

http://sjkoopman.net

Tinbergen Institute

Gustav Mahlerplein 117

1082 MS Amsterdam

Netherlands

http://personal.vu.nl/s.j.koopman

Aarhus University - CREATES

School of Economics and Management

Building 1322, Bartholins Alle 10

DK-8000 Aarhus C

Denmark

SCHOLARLY PAPERS

105

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17,006

SSRN CITATIONS
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Top 1,990

in Total Papers Citations

191

CROSSREF CITATIONS

329

Scholarly Papers (105)

1.

Forecasting Daily Variability of the S&P 100 Stock Index Using Historical, Realised and Implied Volatility Measurements

Tinbergen Institute Working Paper No. TI 04-016/4
Number of pages: 32 Posted: 13 Feb 2004
Siem Jan Koopman, Borus Jungbacker and Eugenie Hol Uspensky
Vrije Universiteit Amsterdam - School of Business and Economics, VU University Amsterdam - Department of Economics and University of Birmingham - Department of Accounting and Finance
Downloads 1,001 (21,810)
Citation 36

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Generalised autoregressive conditional heteroskedasticity model, Long memory model, Realised volatility, Stochastic volatility model, Superior predictive ability, Unobserved components

2.

Analyzing the Term Structure of Interest Rates Using the Dynamic Nelson-Siegel Model with Time-Varying Parameters

Tinbergen Institute Discussion Paper No. 07-095/4, Journal of Business and Economic Statistics, Vol. 28, No. 3, pp. 329-343, 2010
Number of pages: 31 Posted: 10 Dec 2007 Last Revised: 15 Aug 2011
Siem Jan Koopman, Max Mallee and Michel van der Wel
Vrije Universiteit Amsterdam - School of Business and Economics, Vrije Universiteit Amsterdam, School of Business and Economics and Erasmus University Rotterdam
Downloads 954 (23,405)
Citation 9

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Generalized Autoregressive Conditional Heteroskedasticity model, Extended Kalman filter, Time-Varying Volatility, Yield Curve

3.

Stock Index Volatility Forecasting with High Frequency Data

Tinbergen Institute Discussion Paper No. 2002-068/4
Number of pages: 25 Posted: 30 Jul 2002
Eugenie Hol Uspensky and Siem Jan Koopman
University of Birmingham - Department of Accounting and Finance and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 913 (24,972)

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ARFIMA, Financial market volatility, GARCH, Realised volatility, Stochastic volatility, Stock index returns, Unobserved ARMA component

4.

Business and Default Cycles for Credit Risk

Tinbergen Institute Discussion Paper No. 03-062/2
Number of pages: 23 Posted: 29 Sep 2003
Siem Jan Koopman and Andre Lucas
Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 910 (25,089)
Citation 9

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credit cycles, business cycles, defaults, credit risk, procyclicality, multivariate unobserved component models

Systemic Risk Diagnostics: Coincident Indicators and Early Warning Signals

ECB Working Paper No. 1327
Number of pages: 38 Posted: 19 Apr 2011
Bernd Schwaab, Siem Jan Koopman and Andre Lucas
European Central Bank (ECB) - Directorate General Research, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 467 (60,270)

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financial crisis, systemic risk, credit portfolio models, frailty-correlated defaults, state space methods

Systemic Risk Diagnostics: Coincident Indicators and Early Warning Signals

Tinbergen Institute Discussion Paper 10-104/DSF 2
Number of pages: 33 Posted: 03 Dec 2010
Bernd Schwaab, Siem Jan Koopman and Andre Lucas
European Central Bank (ECB) - Directorate General Research, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 191 (159,718)
Citation 9

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financial crisis, systemic risk, credit portfolio models, frailty-correlated defaults, state space methods

6.

Pro-Cyclicality, Empirical Credit Cycles, and Capital Buffer Formation

EFA 2003 Annual Conference Paper No. 211; Vrije University Finance Working Paper
Number of pages: 31 Posted: 27 Jul 2003
Siem Jan Koopman, Andre Lucas and Pieter Klaassen
Vrije Universiteit Amsterdam - School of Business and Economics, Vrije Universiteit Amsterdam - School of Business and Economics and UBS AG
Downloads 574 (46,949)
Citation 11

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credit risk, pro-cyclicality, capital requirements, dynamic models, common factors, credit cycles, time varying parameters

7.

Modeling Round-the-Clock Price Discovery for Cross-Listed Stocks Using State Space Methods

Journal of Business and Economic Statistics, Vol. 25, 2007
Number of pages: 33 Posted: 06 Aug 2003 Last Revised: 18 Jan 2012
Albert J. Menkveld, Siem Jan Koopman and Andre Lucas
VU Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 544 (50,210)
Citation 14

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8.

Maximum Likelihood Estimation for Score-Driven Models

Tinbergen Institute Discussion Paper 14-029/III
Number of pages: 52 Posted: 04 Mar 2014 Last Revised: 31 Oct 2017
Francisco Blasques, Siem Jan Koopman and Andre Lucas
VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 484 (58,295)
Citation 26

Abstract:

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score driven models, time-varying parameters,Markov processes, stationarity, invertibility, consistency, asymptotic normality

9.

A Dynamic Bivariate Poisson Model for Analysing and Forecasting Match Results in the English Premier League

Tinbergen Institute Discussion Paper 12-099/III
Number of pages: 32 Posted: 01 Oct 2012
Siem Jan Koopman and Rutger Lit
Vrije Universiteit Amsterdam - School of Business and Economics and VU University Amsterdam
Downloads 463 (61,589)
Citation 1

Abstract:

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betting, importance sampling, kalman filter smoother, Non-Gaussian multivariate time series models, sport statistics

10.

Credit Cycles and Macro Fundamentals

Journal of Empirical Finance, Vol. 16, No. 1, 2009
Number of pages: 20 Posted: 14 Mar 2006 Last Revised: 07 Apr 2011
Vrije Universiteit Amsterdam - School of Business and Economics, Luxembourg School of Finance, Vrije Universiteit Amsterdam - School of Business and Economics and Tinbergen Institute - Tinbergen Institute Amsterdam (TIA)
Downloads 413 (70,699)
Citation 1

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Credit cycles, Business cycles, Bank lending conditions, Unobserved component models, Intensity models

11.

Smooth Dynamic Factor Analysis with Application to the U.S. Term Structure of Interest Rates

Journal of Applied Econometrics, 29, p65-90, CREATES Research Paper 2009-39, Tinbergen Institute Discussion Paper 09-041/4
Number of pages: 56 Posted: 12 May 2009 Last Revised: 05 Aug 2014
Borus Jungbacker, Siem Jan Koopman and Michel van der Wel
VU University Amsterdam - Department of Economics, Vrije Universiteit Amsterdam - School of Business and Economics and Erasmus University Rotterdam
Downloads 402 (73,019)
Citation 2

Abstract:

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Fama-Bliss data set, Kalman filter, Maximum likelihood, Yield curve

12.

Intervention Time Series Analysis of Crime Rates

Tinbergen Institute Discussion Paper No. 2003-040/4
Number of pages: 35 Posted: 22 Jul 2003
Sanjeev Sridharan, Suncica Vujic and Siem Jan Koopman
Westat, Vrije Universiteit Amsterdam, School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 349 (86,006)
Citation 4

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ARIMA models, Intervention, Parole abolition, Regression models, Sentence reform, Structural time series models

13.

Regime Switches in the Volatility and Correlation of Financial Institutions

National Bank of Belgium Working Paper No. 227
Number of pages: 54 Posted: 13 Oct 2012
Kris Boudt, Jon Danielsson, Siem Jan Koopman and Andre Lucas
Ghent University, London School of Economics - Systemic Risk Centre, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 348 (86,294)
Citation 17

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14.

A General Framework for Observation Driven Time-Varying Parameter Models

Tinbergen Institute Discussion Paper No. 08-108/4
Number of pages: 54 Posted: 11 Nov 2008
Drew Creal, Siem Jan Koopman and Andre Lucas
University of Chicago - Booth School of Business - Econometrics and Statistics, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 331 (91,308)
Citation 14

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dynamic models, time-varying parameters, non-linearity, exponential family, marked point processes, copulas

15.

Maximum Likelihood Estimation for Dynamic Factor Models with Missing Data

Tinbergen Discussion Paper No. 09-010/4, Journal of Economic Dynamics and Control, Vol. 35, No. 8, pp. 1358-1368, 2011
Number of pages: 20 Posted: 12 Feb 2009 Last Revised: 15 Aug 2011
Borus Jungbacker, Siem Jan Koopman and Michel van der Wel
VU University Amsterdam - Department of Economics, Vrije Universiteit Amsterdam - School of Business and Economics and Erasmus University Rotterdam
Downloads 301 (101,306)

Abstract:

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High-dimensional vector series, Kalman filtering and smoothing, Unbalanced panels of time series

16.

Forecasting Interest Rates with Shifting Endpoints

Journal of Applied Econometrics, 29, p693-712, Tinbergen Institute Discussion Paper 12-076/4
Number of pages: 78 Posted: 27 Jul 2012 Last Revised: 05 Aug 2014
Erasmus University Rotterdam - Erasmus School of Economics - Econometric Institute, Vrije Universiteit Amsterdam - School of Business and Economics, Erasmus University Rotterdam and Johns Hopkins University - Department of Economics
Downloads 291 (105,113)
Citation 5

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Non-stationarity, survey forecasts, term structure of interest rates, forecasting, yield curve

17.

Convergence in European GDP Series

Tinbergen Institute Discussion Paper No. 2003-031/4
Number of pages: 31 Posted: 23 May 2003
Rob Luginbuhl and Siem Jan Koopman
Vrije Universiteit Amsterdam, School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 277 (110,830)
Citation 1

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Common trends and cycles, Dynamic factor model, Economic convergence, Kalman filter, Multivariate unobserved components time series models

18.

The Multi-State Latent Factor Intensity Model for Credit Rating Transitions

Tinbergen Institute Discussion Paper No. TI 05-071/4
Number of pages: 33 Posted: 07 Jul 2005
Siem Jan Koopman, Andre Lucas and Andre A. Monteiro
Vrije Universiteit Amsterdam - School of Business and Economics, Vrije Universiteit Amsterdam - School of Business and Economics and Tinbergen Institute - Tinbergen Institute Amsterdam (TIA)
Downloads 266 (115,629)
Citation 17

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Unobserved components, credit cycles, duration model, generator matrix, Monte Carlo likelihood

19.

Time Series Models with a Common Stochastic Variance for Analysing Economic Time Series

Tinbergen Institute Discussion Paper No. TI 02-113/4
Number of pages: 34 Posted: 06 Jan 2003
Siem Jan Koopman and Charles S. Bos
Vrije Universiteit Amsterdam - School of Business and Economics and VU University Amsterdam
Downloads 255 (120,835)

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Autoregressive integrated moving average, Importance sampling, Industrial production, Inflation, Kalman filter, Monte Carlo simulation, Simulation smoothing, State space, Stochastic volatility, Unobserved components time series

20.

Macro, Frailty, and Contagion Effects in Defaults: Lessons from the 2008 Credit Crisis

Tinbergen Institute Discussion Paper 10-004/2
Number of pages: 36 Posted: 27 Jan 2010 Last Revised: 05 Sep 2010
Siem Jan Koopman, Andre Lucas and Bernd Schwaab
Vrije Universiteit Amsterdam - School of Business and Economics, Vrije Universiteit Amsterdam - School of Business and Economics and European Central Bank (ECB) - Directorate General Research
Downloads 251 (122,759)
Citation 1

Abstract:

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financial crisis, default risk, credit portfolio models, frailty-correlated defaults, state space methods, doubly stochastic default times

21.

Periodic Heteroskedastic Regarfima Models for Daily Electricity Spot Prices

Tinbergen Institute Discussion Paper No. TI 03-071/4
Number of pages: 41 Posted: 22 Nov 2003
M. Angeles Carnero, Siem Jan Koopman and Marius Ooms
Universidad de Alicante - Department of Economic Analysis, Vrije Universiteit Amsterdam - School of Business and Economics and VU University Amsterdam - Department of Econometrics
Downloads 245 (125,857)
Citation 2

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Autoregressive fractionally integrated moving average model, Generalised autoregressive conditional heteroskedasticity model, Long memory process, Periodic autoregressive model, Volatility

22.

Model-Based Measurement of Actual Volatility in High-Frequency Data

Tinbergen Institute Discussion Paper No. 2005-002/4
Number of pages: 26 Posted: 10 Jan 2005
Borus Jungbacker and Siem Jan Koopman
VU University Amsterdam - Department of Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 243 (126,943)
Citation 4

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Importance sampling, Maximum likelihood estimation, Micro-structure noise, Realised variance, Stochastic volatility model

Time Varying Transition Probabilities for Markov Regime Switching Models

Tinbergen Institute Discussion Paper 14-072/III
Number of pages: 26 Posted: 20 Jun 2014
Marco Bazzi, Francisco Blasques, Siem Jan Koopman and Andre Lucas
University of Padua, VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 241 (127,445)
Citation 4

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Hidden Markov Models; observation driven models; generalized autoregressive score dynamics

Time‐Varying Transition Probabilities for Markov Regime Switching Models

Journal of Time Series Analysis, Vol. 38, Issue 3, pp. 458-478, 2017
Number of pages: 21 Posted: 05 Apr 2017
Marco Bazzi, Francisco Blasques, Siem Jan Koopman and Andre Lucas
University of Padua, VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 1 (689,894)
Citation 1
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Hidden Markov models, observation driven models, time varying parameter

24.

Forecasting the U.S. Term Structure of Interest Rates Using a Macroeconomic Smooth Dynamic Factor Model

International Journal of Forecasting, 29, p676-694
Number of pages: 38 Posted: 12 Apr 2011 Last Revised: 05 Aug 2014
Siem Jan Koopman and Michel van der Wel
Vrije Universiteit Amsterdam - School of Business and Economics and Erasmus University Rotterdam
Downloads 208 (147,548)
Citation 4

Abstract:

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Fama-Bliss data set, Kalman filter, Maximum likelihood, Yield curve

25.

An Hourly Periodic State Space Model for Modelling French National Electricity Load

Tinbergen Institute Discussion Paper No. 2008-008/4
Number of pages: 38 Posted: 23 Jan 2008
VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics, VU University Amsterdam - Department of Econometrics, Electricité de France and Electricité de France
Downloads 203 (151,003)

Abstract:

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Kalman filter, Maximum likelihood estimation, Seemingly Unrelated Regression Equations, Unobserved Components, Time varying parameters, Heating effect

26.

A Non-Gaussian Panel Time Series Model for Estimating and Decomposing Default Risk

Tinbergen Institute Discussion Paper No. TI 05-060/4
Number of pages: 32 Posted: 17 Jun 2005
Siem Jan Koopman, Andre Lucas and Robert Daniels
Vrije Universiteit Amsterdam - School of Business and Economics, Vrije Universiteit Amsterdam - School of Business and Economics and Bank of the Netherlands
Downloads 198 (154,625)
Citation 9

Abstract:

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Credit risk, multivariate unobserved component models, importance sampling, non-Gaussian state space models

27.

A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations

Tinbergen Institute Discussion Paper 10-032/2
Number of pages: 32 Posted: 24 Mar 2010 Last Revised: 14 Oct 2010
Drew Creal, Siem Jan Koopman and Andre Lucas
University of Chicago - Booth School of Business - Econometrics and Statistics, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 185 (164,474)
Citation 5

Abstract:

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dynamic dependence, multivariate Student's t distribution, copula

28.

Testing for Parameter Instability in Competing Modeling Frameworks

Tinbergen Institute 14-010/IV/71
Number of pages: 40 Posted: 18 Jan 2014 Last Revised: 06 Feb 2014
Francesco Calvori, Drew Creal, Siem Jan Koopman and Andre Lucas
University of Florence - Dipartimento di Statistica, Informatica, Applicazioni (DiSIA), University of Chicago - Booth School of Business - Econometrics and Statistics, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 179 (169,449)
Citation 1

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time-varying parameters; observation driven models; parameter driven models; structural breaks; generalized autoregressive score model; regime switching; credit risk

29.

On Importance Sampling for State Space Models

Tinbergen Institute Discussion Paper No. 05-117
Number of pages: 28 Posted: 03 Jan 2006
Borus Jungbacker and Siem Jan Koopman
VU University Amsterdam - Department of Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 168 (179,186)
Citation 2

Abstract:

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Kalman filter, Likelihood function, Monte Carlo integration, Newton-Raphson, Posterior mode estimation, Simulation smoothing, Stochastic volatility model

30.

Realized Wishart-Garch: A Score-Driven Multi-Asset Volatility Model

Tinbergen Institute Discussion Paper 2016-061/III
Number of pages: 36 Posted: 19 Aug 2016
Peter Reinhard Hansen, Pawel Janus and Siem Jan Koopman
University of North Carolina (UNC) at Chapel Hill - Department of Economics, Independent and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 165 (181,954)
Citation 3

Abstract:

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high-frequency data, multivariate GARCH, multivariate volatility, realised covariance, score, Wishart density

31.
Downloads 165 (181,954)
Citation 3

Generalized autoregressive Method of Moments

Tinbergen Institute Discussion Paper 15-138/III
Number of pages: 45 Posted: 20 Jan 2016 Last Revised: 01 Jul 2018
Drew Creal, Siem Jan Koopman, Andre Lucas and Marcin Zamojski
University of Chicago - Booth School of Business - Econometrics and Statistics, Vrije Universiteit Amsterdam - School of Business and Economics, Vrije Universiteit Amsterdam - School of Business and Economics and
Downloads 133 (218,060)
Citation 2

Abstract:

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dynamic models, time-varying parameters, generalized method of moments, non-linearity, equity premium puzzle, CCAPM

Generalized Autoregressive Method of Moments

Tinbergen Institute Discussion Paper 15-138/III
Number of pages: 47 Posted: 27 Jul 2018
Drew Creal, Siem Jan Koopman, Andre Lucas and Marcin Zamojski
University of Chicago - Booth School of Business - Econometrics and Statistics, Vrije Universiteit Amsterdam - School of Business and Economics, Vrije Universiteit Amsterdam - School of Business and Economics and
Downloads 32 (473,647)
Citation 1

Abstract:

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dynamic models, time-varying parameters, generalized method of moments, non-linearity

32.

Model-Based Measurement of Latent Risk in Time Series with Applications

Tinbergen Institute Discussion Paper No. 05-118/4
Number of pages: 31 Posted: 03 Jan 2006
Institute for Road Safety Research (SWOV), Institute for Road Safety Research (SWOV), Free University of Amsterdam and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 150 (197,119)

Abstract:

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Actuarial statistics, Dynamic factor analysis

33.

Measuring Synchronisation and Convergence of Business Cycles

Tinbergen Institute Discussion Paper No. 03-052/4
Number of pages: 26 Posted: 23 Jul 2003
Siem Jan Koopman and João Valle e Azevedo
Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam, School of Business and Economics
Downloads 148 (199,351)
Citation 6

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Band-pass filter, Cyclical convergence, Kalman filter, Unobserved components time series models, Phase shifts

34.

Modeling Frailty-Correlated Defaults Using Many Macroeconomic Covariates

Number of pages: 37 Posted: 12 Feb 2009 Last Revised: 29 Aug 2010
Siem Jan Koopman, Andre Lucas and Bernd Schwaab
Vrije Universiteit Amsterdam - School of Business and Economics, Vrije Universiteit Amsterdam - School of Business and Economics and European Central Bank (ECB) - Directorate General Research
Downloads 145 (202,722)
Citation 12

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Non-Gaussian Panel Data, Common Factors, Unobserved Components, Forecasting

35.

Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models

Number of pages: 37 Posted: 06 Mar 2012
Siem Jan Koopman, Andre Lucas and Marcel Scharth
Vrije Universiteit Amsterdam - School of Business and Economics, Vrije Universiteit Amsterdam - School of Business and Economics and The University of Sydney
Downloads 139 (209,800)
Citation 13

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Generalised autoregressive score model, Importance sampling, Model confidence set, Nonlinear state space model, Weibull-gamma mixture

Observation Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk

Tinbergen Institute Discussion Paper 11-042/DSF 16
Number of pages: 43 Posted: 22 Feb 2011
Drew Creal, Bernd Schwaab, Siem Jan Koopman and Andre Lucas
University of Chicago - Booth School of Business - Econometrics and Statistics, European Central Bank (ECB) - Directorate General Research, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 106 (258,336)
Citation 11

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panel data, loss given default, default risk, dynamic beta density, dynamic ordered probit, dynamic factor model

Observation Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk

ECB Working Paper No. 1626
Number of pages: 43 Posted: 04 Jan 2014
Drew Creal, Bernd Schwaab, Siem Jan Koopman and Andre Lucas
University of Chicago - Booth School of Business - Econometrics and Statistics, European Central Bank (ECB) - Directorate General Research, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 33 (468,785)

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panel data; loss given default; default risk; dynamic beta density; dynamic ordered probit; dynamic factor model

37.

Forecasting Cross-Sections of Frailty-Correlated Default

Tinbergen Institute Discussion Paper No. 08-029/4
Number of pages: 35 Posted: 25 Mar 2008
Siem Jan Koopman, Andre Lucas and Bernd Schwaab
Vrije Universiteit Amsterdam - School of Business and Economics, Vrije Universiteit Amsterdam - School of Business and Economics and European Central Bank (ECB) - Directorate General Research
Downloads 137 (212,319)
Citation 3

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Non-Gaussian Panel Data, Common Factors, Unobserved Components, Forecasting Conditional Default Probabilities

38.

Seasonality with Trend and Cycle Interactions in Unobserved Components Models

Tinbergen Institute Discussion Paper No. TI 08-028/4
Number of pages: 24 Posted: 28 Mar 2008
Siem Jan Koopman and Kai Ming Lee
Vrije Universiteit Amsterdam - School of Business and Economics and affiliation not provided to SSRN
Downloads 133 (217,368)
Citation 1

Abstract:

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Seasonal interaction; Unobserved components; Non-linear state space models

39.

Tracking Growth and the Business Cycle: A Stochastic Common Cycle Model for the Euro Area

Tinbergen Institute Discussion Paper No. 03-069/4
Number of pages: 24 Posted: 17 Nov 2003
João Valle e Azevedo, Siem Jan Koopman and Antonio Rua
Vrije Universiteit Amsterdam, School of Business and Economics, Vrije Universiteit Amsterdam - School of Business and Economics and Bank of Portugal - Economic Research Department
Downloads 133 (217,368)

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40.

The Dynamic Skellam Model with Applications

Tinbergen Institute Discussion Paper 14-032/IV/DSF73
Number of pages: 32 Posted: 11 Mar 2014
Siem Jan Koopman, Rutger Lit and Andre Lucas
Vrije Universiteit Amsterdam - School of Business and Economics, VU University Amsterdam and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 130 (221,262)
Citation 2

Abstract:

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dynamic count data models, non-Gaussian multivariate time series models, importance sampling, numerical integration, volatility models, sports data

41.

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

Tinbergen Institute Discussion Paper 16-051/IV
Number of pages: 19 Posted: 11 Jul 2016
Siem Jan Koopman, Rutger Lit and Andre Lucas
Vrije Universiteit Amsterdam - School of Business and Economics, VU University Amsterdam and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 129 (222,633)
Citation 11

Abstract:

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financial cycle, business cycle, phase shift, multivariate state space model, Kalman filtering, panel time series

42.

Modeling Trigonometric Seasonal Components for Monthly Economic Time Series

Tinbergen Institute Discussion Paper 10-018/4
Number of pages: 20 Posted: 06 Feb 2010
VU University Amsterdam, University of Warwick, Vrije Universiteit Amsterdam - School of Business and Economics and VU University Amsterdam - Department of Econometrics
Downloads 127 (225,221)

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Frequency-specific model, Kalman filter, model-based seasonal adjustment, unobserved components time series model

43.

Intraday Stock Price Dependence Using Dynamic Discrete Copula Distributions

Tinbergen Institute Discussion Paper 15-037/III/DSF90
Number of pages: 40 Posted: 21 Mar 2015
Siem Jan Koopman, Rutger Lit and Andre Lucas
Vrije Universiteit Amsterdam - School of Business and Economics, VU University Amsterdam and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 125 (228,022)
Citation 1

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time-varying copulas, dynamic discrete data, score driven models, Skellam distribution, dynamic dependence

44.

Measuring Asymmetric Stochastic Cycle Components

Tinbergen Institute Discussion Paper No. 05-081/4
Number of pages: 28 Posted: 25 Aug 2005
Siem Jan Koopman and Kai Ming Lee
Vrije Universiteit Amsterdam - School of Business and Economics and Free University of Amsterdam, Tinbergen Institute
Downloads 111 (248,727)

Abstract:

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Asymmetric business cycles, Unobserved Components, Nonlinear state space models, Monte Carlo likelihood, Importance sampling

Likelihood Functions for State Space Models with Diffuse Initial Conditions

Tinbergen Institute Discussion Paper No. TI 2008-040/4
Number of pages: 26 Posted: 16 Apr 2008
Marc Francke, Siem Jan Koopman and Aart F. de Vos
University of Amsterdam - Faculty of Economics and Business (FEB), Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam, School of Business and Economics
Downloads 108 (254,947)
Citation 4

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Diffuse likelihood, Kalman filter, Marginal likelihood, Multivariate time series models, Profile likelihood

Likelihood Functions for State Space Models with Diffuse Initial Conditions

Journal of Time Series Analysis, Vol. 31, Issue 6, pp. 407-414, November 2010
Number of pages: 8 Posted: 12 Oct 2010
Marc Francke, Siem Jan Koopman and Aart F. de Vos
University of Amsterdam - Faculty of Economics and Business (FEB), Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam, School of Business and Economics
Downloads 2 (675,863)
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46.

Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State Space Models

Number of pages: 39 Posted: 20 Mar 2011 Last Revised: 28 Jan 2012
Siem Jan Koopman, Andre Lucas and Marcel Scharth
Vrije Universiteit Amsterdam - School of Business and Economics, Vrije Universiteit Amsterdam - School of Business and Economics and The University of Sydney
Downloads 108 (253,590)
Citation 9

Abstract:

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Kalman filter, Monte Carlo maximum likelihood, numerical integration, stochastic copula, stochastic conditional duration, stochastic volatility

47.

Bayesian Dynamic Modeling of High-Frequency Integer Price Changes

Tinbergen Instituut 16-028/III
Number of pages: 47 Posted: 24 Apr 2016 Last Revised: 18 Feb 2018
Istvan Barra, Agnieszka Borowska and Siem Jan Koopman
VU University Amsterdam, VU University Amsterdam and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 105 (258,623)
Citation 2

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Bayesian inference, discrete distributions, high-frequency dynamics, Markov chain Monte Carlo, stochastic volatility

48.

The Analysis and Forecasting of ATP Tennis Matches Using a High-Dimensional Dynamic Model

Tinbergen Institute Discussion Paper 2018-009/III
Number of pages: 18 Posted: 04 Feb 2018
Paolo Gorgi, Siem Jan Koopman and Rutger Lit
VU University Amsterdam - Faculty of Economics and Business Administration, Vrije Universiteit Amsterdam - School of Business and Economics and VU University Amsterdam
Downloads 99 (269,166)

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Sports Statistics, Score-Driven Time Series Models, Rankings, Forecasting

49.

Bayesian Risk Forecasting for Long Horizons

Tinbergen Institute Discussion Paper 2019-018/III
Number of pages: 40 Posted: 13 Mar 2019
VU University Amsterdam, VU University Amsterdam and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 96 (274,676)

Abstract:

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Bayesian inference, forecasting, importance sampling, numerical accuracy, long run risk, Value-at-Risk, Expected Shortfall

50.

Long Memory Modelling of Inflation with Stochastic Variance and Structural Breaks

Tinbergen Institute Discussion Paper No. 2007-099/4, CREATES Research Paper No. 2007-44
Number of pages: 29 Posted: 11 Jan 2008
Charles S. Bos, Siem Jan Koopman and Marius Ooms
VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics and VU University Amsterdam - Department of Econometrics
Downloads 93 (280,314)
Citation 16

Abstract:

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Time varying parameters, Importance sampling, Monte Carlo simulation, Stochastic Volatility, Fractional Integration

51.

Spillover Dynamics for Systemic Risk Measurement Using Spatial Financial Time Series Models

Tinbergen Institute Discussion Paper 14-107/III
Number of pages: 48 Posted: 15 Aug 2014 Last Revised: 18 Aug 2014
VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics, Vrije Universiteit Amsterdam - School of Business and Economics and Tinbergen Institute
Downloads 91 (284,267)
Citation 5

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Spatial correlation, time-varying parameters, systemic risk, European debt crisis, generalized autoregressive score

52.

Fast Efficient Importance Sampling by State Space Methods

Tinbergen Institute Discussion Paper No. 12-008/4
Number of pages: 30 Posted: 01 Feb 2012 Last Revised: 17 Oct 2014
Siem Jan Koopman, Rutger Lit and Thuy Minh Nguyen
Vrije Universiteit Amsterdam - School of Business and Economics, VU University Amsterdam and Deutsche Bank AG (London)
Downloads 91 (284,267)
Citation 1

Abstract:

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Kalman filter, Monte Carlo maximum likelihood, simulation smoothing

53.

Structural Intervention Time Series Analysis of Crime Rates: The Impact of Sentence Reform in Virginia

Tinbergen Institute Discussion Paper No. 12-007/4
Number of pages: 33 Posted: 01 Feb 2012
Suncica Vujic, Jacques Commandeur and Siem Jan Koopman
Vrije Universiteit Amsterdam, School of Business and Economics, Institute for Road Safety Research (SWOV) and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 90 (286,230)
Citation 1

Abstract:

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Kalman filter, Monte Carlo maximum likelihood, simulation smoothing

54.

Models with Time-Varying Mean and Variance: A Robust Analysis of U.S. Industrial Production

Tinbergen Institute Discussion Paper 10-017/4
Number of pages: 22 Posted: 06 Feb 2010
Charles S. Bos and Siem Jan Koopman
VU University Amsterdam and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 89 (288,299)

Abstract:

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Common stochastic variance, Kalman filter, State space model, unobserved components time series model

55.

Stationarity and Ergodicity of Univariate Generalized Autoregressive Score Processes

Tinbergen Institute Discussion Paper No. 12-059/2
Number of pages: 31 Posted: 22 Jun 2012 Last Revised: 20 Mar 2014
Francisco Blasques, Siem Jan Koopman and Andre Lucas
VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 87 (292,491)
Citation 10

Abstract:

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Dudley integral, Durations, Higher-order models, Nonlinear dynamics, Time-varying parameters, Volatility

56.

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

Tinbergen Institute Discussion Paper 11-090/4
Number of pages: 31 Posted: 27 Jun 2011
Geert Mesters, Siem Jan Koopman and Marius Ooms
affiliation not provided to SSRN, Vrije Universiteit Amsterdam - School of Business and Economics and VU University Amsterdam - Department of Econometrics
Downloads 87 (292,491)
Citation 1

Abstract:

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fractional integration, importance sampling, kalman filter, latent factors, stochastic volatility

57.

Spot Variance Path Estimation and Its Application to High Frequency Jump Testing

Tinbergen Institute Discussion Paper 09-110/4
Number of pages: 35 Posted: 07 Dec 2009
Charles S. Bos, Pawel Janus and Siem Jan Koopman
VU University Amsterdam, VU University Amsterdam and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 87 (292,491)
Citation 3

Abstract:

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high frequency, intraday periodicity, jump testing, leverage effect, microstructure noise, pre-averaged bipower variation, spot variance

58.

The Analysis of Stochastic Volatility in the Presence of Daily Realised Measures

Number of pages: 48 Posted: 20 Sep 2011 Last Revised: 10 Sep 2012
Siem Jan Koopman and Marcel Scharth
Vrije Universiteit Amsterdam - School of Business and Economics and The University of Sydney
Downloads 86 (294,564)
Citation 5

Abstract:

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Kalman filter, leverage, realised volatility, simulated maximum likelihood

59.

A Dynamic Yield Curve Model with Stochastic Volatility and Non-Gaussian Interactions: An Empirical Study of Non-Standard Monetary Policy in the Euro Area

Tinbergen Institute Discussion Paper 14-071/III
Number of pages: 44 Posted: 21 Jun 2014
Geert Mesters, Bernd Schwaab and Siem Jan Koopman
Vrije Universiteit Amsterdam, School of Business and Economics, European Central Bank (ECB) - Directorate General Research and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 85 (296,683)
Citation 5

Abstract:

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dynamic Nelson-Siegel models, Central bank asset purchases, non-Gaussian, state space methods, importance sampling, European Central Bank

60.
Downloads 83 (301,088)
Citation 12

The Information in Systemic Risk Rankings

Tinbergen Institute Discussion Paper 15-070/III/94
Number of pages: 24 Posted: 03 Jun 2015
Federico Nucera, Bernd Schwaab, Siem Jan Koopman and Andre Lucas
Bank of Italy, European Central Bank (ECB) - Directorate General Research, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 47 (409,273)
Citation 5

Abstract:

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systemic risk contribution, risk rankings, forecast combination, financial regulation, banking supervision

The Information in Systemic Risk Rankings

ECB Working Paper No. 1875
Number of pages: 34 Posted: 21 Jan 2016
Federico Nucera, Bernd Schwaab, Siem Jan Koopman and Andre Lucas
Bank of Italy, European Central Bank (ECB) - Directorate General Research, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 36 (454,768)
Citation 3

Abstract:

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systemic risk contribution, risk rankings, forecast combination, financial regulation, banking supervision

61.

Long Memory Dynamics for Multivariate Dependence Under Heavy Tails

Tinbergen Institute Discussion Paper 11-175/5/DSF28
Number of pages: 43 Posted: 14 Dec 2011
Pawel Janus, Siem Jan Koopman and Andre Lucas
VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 83 (301,088)
Citation 4

Abstract:

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fractional integration, correlation, student's t copula, time-varying dependence, multivariate volatility

62.

Modelling Round-the-Clock Price Discovery for Cross-Listed Stocks Using State Space Methods

NYU Working Paper No. SC-CFE-04-03
Number of pages: 30 Posted: 07 Nov 2008 Last Revised: 14 Oct 2010
Albert J. Menkveld, Siem Jan Koopman and Andre Lucas
VU Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 82 (303,357)
Citation 1

Abstract:

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Efficient price;, Financial markets, High-frequency data, Kalman filter, Unobserved components time series models

63.

Extracting Business Cycles Using Semi-Parametric Time-Varying Spectra with Applications to Us Macroeconomic Time Series

Tinbergen Institute Discussion Paper No. 06-105/4
Number of pages: 35 Posted: 01 Dec 2006
Siem Jan Koopman and Soon Y. Wong
Vrije Universiteit Amsterdam - School of Business and Economics and VU University Amsterdam
Downloads 79 (310,022)

Abstract:

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Frequency domain estimation, frequency domain bootstrap, time-varying parameters, unobserved components models

64.

Generalized Dynamic Panel Data Models with Random Effects for Cross-Section and Time

Tinbergen Institute Discussion Paper No. 12-009/4
Number of pages: 54 Posted: 07 Feb 2012
Geert Mesters and Siem Jan Koopman
Vrije Universiteit Amsterdam, School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 77 (314,747)
Citation 2

Abstract:

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panel data, non-Gaussian, importance sampling, random effects, Student's t, economic growth

65.

Periodic Unobserved Cycles in Seasonal Time Series with an Application to Us Unemployment

Tinbergen Institute Discussion Paper No. 06-101/4
Number of pages: 41 Posted: 25 Nov 2006
Siem Jan Koopman, Marius Ooms and Irma Hindrayanto
Vrije Universiteit Amsterdam - School of Business and Economics, VU University Amsterdam - Department of Econometrics and VU University Amsterdam
Downloads 75 (319,632)

Abstract:

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Unobserved component models, state space methods, seasonal adjustment, time-varying parameters, forecasting

66.

Forecasting Macroeconomic Variables Using Collapsed Dynamic Factor Analysis

Tinbergen Institute Discussion Paper No. 12-042/4
Number of pages: 33 Posted: 25 Apr 2012 Last Revised: 05 Jul 2012
Falk Bräuning and Siem Jan Koopman
Federal Reserve Banks - Federal Reserve Bank of Boston and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 68 (337,343)
Citation 4

Abstract:

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Kalman filter, Mixed frequency, Nowcasting, Principal components, State space model, Unobserved Components Time Series Model

67.

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

FRB of Boston Working Paper No. 16-13
Number of pages: 45 Posted: 23 Nov 2016
Falk Bräuning and Siem Jan Koopman
Federal Reserve Banks - Federal Reserve Bank of Boston and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 65 (345,455)

Abstract:

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network analysis, dynamic factor models, blockmodels, credit-risk spillovers

68.

Estimating Systematic Continuous-Time Trends in Recidivism Using a Non-Gaussian Panel Data Model

TI 07-027/4
Number of pages: 31 Posted: 13 Mar 2007
Siem Jan Koopman, Andre Lucas, Marius Ooms and Kees van Montfort
Vrije Universiteit Amsterdam - School of Business and Economics, Vrije Universiteit Amsterdam - School of Business and Economics, VU University Amsterdam - Department of Econometrics and Nyenrode University
Downloads 65 (345,455)
Citation 2

Abstract:

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non-Gaussian state space modeling, nonlinear panel data model, binomial time series, recidivism behavior, continuous time modelling

69.

The Effect of the Great Moderation on the U.S. Business Cycle in a Time-Varying Multivariate Trend-Cycle Model

Tinbergen Institute Discussion Paper 08-069/4
Number of pages: 30 Posted: 31 Jul 2008
Drew Creal and Siem Jan Koopman
University of Chicago - Booth School of Business - Econometrics and Statistics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 63 (351,076)

Abstract:

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Bandpass filter, Markov chain Monte Carlo, Stochastic volatility, Trend-cycle decomposition, Unobserved components time series model

70.

Dynamic Factor Models with Macro, Frailty and Industry Effects for US Default Counts: The Credit Crisis of 2008

ECB Working Paper No. 1459
Number of pages: 45 Posted: 20 Aug 2012
Siem Jan Koopman, Andre Lucas and Bernd Schwaab
Vrije Universiteit Amsterdam - School of Business and Economics, Vrije Universiteit Amsterdam - School of Business and Economics and European Central Bank (ECB) - Directorate General Research
Downloads 61 (356,856)
Citation 2

Abstract:

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financial crisis, default risk, credit portfolio models, frailty-correlated defaults, state space methods

71.

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

Tinbergen Institute Discussion Paper 14-118/III
Number of pages: 35 Posted: 02 Sep 2014 Last Revised: 31 Mar 2016
VU University Amsterdam, VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 60 (359,792)

Abstract:

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Bayesian inference, importance sampling, Monte Carlo estimation, Metropolis-Hastings algorithm, mixture of student's t-distributions

72.

Global Credit Risk: World, Country and Industry Factors

ECB Working Paper No. 1922
Number of pages: 55 Posted: 19 Jun 2016
Bernd Schwaab, Siem Jan Koopman and Andre Lucas
European Central Bank (ECB) - Directorate General Research, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 58 (365,772)
Citation 1

Abstract:

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systematic default risk, credit portfolio models, frailty-correlated defaults, international default risk cycles, state-space methods

73.

Common Business and Housing Market Cycles in the Euro Area from a Multivariate Decomposition

Banque de France Working Paper No. 275
Number of pages: 33 Posted: 03 Jun 2010
Laurent Ferrara and Siem Jan Koopman
Banque de France and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 58 (365,772)
Citation 18

Abstract:

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House Prices, Business Cycles, Euro Area, Unobserved Components Model

74.

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

De Nederlandsche Bank Working Paper No. 495
Number of pages: 27 Posted: 27 Jan 2016
De Nederlandsche Bank, De Nederlandsche Bank, Vrije Universiteit Amsterdam - School of Business and Economics and CPB Netherlands Bureau of Economic Policy Analysis
Downloads 52 (384,936)
Citation 8

Abstract:

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unobserved component models, state space method, maximum likelihood, bandpass filter, short and medium term cycles

75.

Spline Smoothing Over Difficult Regions

Tinbergen Institute Discussion Paper No. 08-114/4
Number of pages: 32 Posted: 24 Nov 2008
Siem Jan Koopman and Soon Y. Wong
Vrije Universiteit Amsterdam - School of Business and Economics and VU University Amsterdam
Downloads 49 (395,206)

Abstract:

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Bivariate smoothing, Geo-statistics, Missing observations, Smoothing spline model, State space methods

76.

Modeling the Business and Financial Cycle in a Multivariate Structural Time Series Model

De Nederlandsche Bank Working Paper No. 573
Number of pages: 44 Posted: 24 Oct 2017
De Nederlandsche Bank, Vrije Universiteit Amsterdam - School of Business and Economics, De Nederlandsche Bank and Independent
Downloads 48 (398,601)
Citation 1

Abstract:

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Unobserved Component Time Series Model, Kalman Filter, Maximum Likelihood Estimation, Short-Term And Medium-Term Cycles

77.

Empirical Bayes Methods for Dynamic Factor Models

Tinbergen Institute Discussion Paper 14-061/III
Number of pages: 45 Posted: 25 May 2014
Siem Jan Koopman and Geert Mesters
Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam, School of Business and Economics
Downloads 47 (401,954)
Citation 1

Abstract:

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Importance sampling, Kalman filtering, Likelihood-based analysis, Posterior modes, Rao-Blackwellization, Shrinkage

Nowcasting and Forecasting Economic Growth in the Euro Area Using Principal Components

Tinbergen Institute Discussion Paper 14-113/III
Number of pages: 29 Posted: 24 Aug 2014
Irma Hindrayanto, Siem Jan Koopman and Jasper de Winter
De Nederlandsche Bank, Vrije Universiteit Amsterdam - School of Business and Economics and De Nederlandsche Bank
Downloads 30 (483,849)

Abstract:

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Factor models, Principal component analysis, Forecasting, Kalman filter, State space method, Publication lag, Mixed frequency

Nowcasting and Forecasting Economic Growth in the Euro Area Using Principal Components

De Nederlandsche Bank Working Paper No. 415
Number of pages: 31 Posted: 20 Feb 2014
Irma Hindrayanto, Siem Jan Koopman and Jasper de Winter
De Nederlandsche Bank, Vrije Universiteit Amsterdam - School of Business and Economics and De Nederlandsche Bank
Downloads 16 (570,979)
Citation 2

Abstract:

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Factor models, Principal component analysis, Forecasting, Kalman filter, State space method, Publication lag, Mixed frequency

79.

Forecasting Economic Time Series Using Score-Driven Dynamic Models with Mixed-Data Sampling

Tinbergen Institute Discussion Paper 2018-026/III
Number of pages: 25 Posted: 26 Mar 2018
Paolo Gorgi, Siem Jan Koopman and Mengheng Li
VU University Amsterdam - Faculty of Economics and Business Administration, Vrije Universiteit Amsterdam - School of Business and Economics and VU University Amsterdam
Downloads 37 (440,367)

Abstract:

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Factor model, GAS model, Inflation forecasting, MIDAS, Score-driven model, Weighted maximum likelihood

80.

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

Tinbergen Institute Discussion Paper 16-105/III
Number of pages: 47 Posted: 30 Nov 2016
Falk Bräuning and Siem Jan Koopman
Federal Reserve Banks - Federal Reserve Bank of Boston and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 36 (444,534)
Citation 1

Abstract:

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Network Analysis, Dynamic Factor Models, Blockmodels, Credit-Risk Spillovers

81.

Optimal Formulations for Nonlinear Autoregressive Processes

Tinbergen Institute Discussion Paper 14-103/III
Number of pages: 54 Posted: 11 Aug 2014
Francisco Blasques, Siem Jan Koopman and Andre Lucas
VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 34 (453,103)
Citation 10

Abstract:

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Asymptotic theory; Dynamic models; Observation driven time series models; Smooth-transition model; Time-Varying Parameters; Treshold autoregressive model

82.

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

Tinbergen Institute Discussion Paper 15-083/III
Number of pages: 34 Posted: 11 Jul 2015
VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics, VU Amsterdam and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 33 (457,504)
Citation 3

Abstract:

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autoregressive conditional duration, delta-method, generalized autoregressive conditional heteroskedasticity, score driven models, time-varying mean

83.

Information Theoretic Optimality of Observation Driven Time Series Models

Tinbergen Institute Discussion Paper 14-046/III
Number of pages: 33 Posted: 12 Apr 2014
Francisco Blasques, Siem Jan Koopman and Andre Lucas
VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 32 (461,953)
Citation 21

Abstract:

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generalized autoregressive models, information theory, optimality, Kullback-Leibler distance, volatility models

84.

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

Tinbergen Institute Discussion Paper 16-029/III
Number of pages: 10 Posted: 25 Apr 2016
De Nederlandsche Bank, De Nederlandsche Bank, Vrije Universiteit Amsterdam - School of Business and Economics and CPB Netherlands Bureau of Economic Policy Analysis
Downloads 28 (481,457)

Abstract:

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unobserved components time series model, Kalman filter, maximum likelihood estimation, band-pass filter, medium-term cycles

85.

Temporal, Spatial, Economic and Crime Factors in Illicit Drug Usage Across European Cities

Tinbergen Institute Discussion Paper 14-135/III
Number of pages: 23 Posted: 18 Oct 2014
Institute for Road Safety Research (SWOV), Vrije Universiteit Amsterdam, School of Business and Economics, Vrije Universiteit Amsterdam - School of Business and Economics and University of Bath
Downloads 27 (486,658)

Abstract:

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Sewage biomarker analysis, ANOVA, Linear mixed models, Wastewater-based epidemiology

86.

Constructing Seasonally Adjusted Data with Time-Varying Confidence Intervals

Oxford Bulletin of Economics and Statistics, Vol. 64, pp. 509-526, 2002
Number of pages: 18 Posted: 10 Feb 2003
Siem Jan Koopman and Philip Hans Franses
Vrije Universiteit Amsterdam - School of Business and Economics and Erasmus University Rotterdam (EUR) - Department of Econometrics
Downloads 26 (492,116)
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87.

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

Tinbergen Institute Discussion Paper 2018-027/III
Number of pages: 37 Posted: 26 Mar 2018
Mengheng Li and Siem Jan Koopman
VU University Amsterdam and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 24 (503,275)

Abstract:

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Importance Sampling, Kalman Filter, Monte Carlo Simulation, Stochastic Volatility, Unobserved Components Time Series Model, Inflation

88.

Low Frequency and Weighted Likelihood Solutions for Mixed Frequency Dynamic Factor Models

Tinbergen Institute Discussion Paper 14-105/III
Number of pages: 51 Posted: 12 Aug 2014
Francisco Blasques, Siem Jan Koopman and Max Mallee
VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam, School of Business and Economics
Downloads 23 (508,878)
Citation 1

Abstract:

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Asymptotic theory, Forecasting, Kalman filter, Nowcasting, State space

89.

Missing Observations in Observation-Driven Time Series Models

Tinbergen Institute Discussion Paper 2018-013/III
Number of pages: 39 Posted: 23 Feb 2018
Francisco Blasques, Paolo Gorgi and Siem Jan Koopman
VU University Amsterdam, VU University Amsterdam - Faculty of Economics and Business Administration and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 22 (514,836)

Abstract:

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missing data, observation-driven models, consistency, indirect inference, volatility

90.

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

Tinbergen Institute Discussion Paper 16-082/III
Number of pages: 34 Posted: 07 Oct 2016
VU University Amsterdam, VU University Amsterdam - Faculty of Economics and Business Administration, Vrije Universiteit Amsterdam - School of Business and Economics and University of Copenhagen
Downloads 20 (526,580)
Citation 4

Abstract:

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consistency, invertibility, maximum likelihood estimation, observation-driven models, stochastic recurrence equations

91.

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

Tinbergen Institute Discussion Paper 15-131/III, 2015
Number of pages: 10 Posted: 14 Dec 2015
VU University Amsterdam, VU University Amsterdam - Faculty of Economics and Business Administration, Vrije Universiteit Amsterdam - School of Business and Economics and University of Copenhagen
Downloads 18 (538,379)
Citation 1

Abstract:

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invertibility, quasi-maximum likelihood estimator, volatility models

92.

In-Sample Bounds for Time-Varying Parameters of Observation Driven Models

Tinbergen Institute Discussion Paper 15-027/III
Number of pages: 31 Posted: 24 Feb 2015
VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics, VU Amsterdam and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 18 (538,379)

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autoregressive conditional duration, delta-method, generalized autoregressive conditional heteroskedasticity, score driven models, time-varying mean

93.

Filtering and Smoothing of State Vector for Diffuse State-Space Models

Journal of Time Series Analysis, Vol. 24, pp. 85-98, 2003
Number of pages: 14 Posted: 03 Jun 2003
Siem Jan Koopman and J. Durbin
Vrije Universiteit Amsterdam - School of Business and Economics and London School of Economics & Political Science (LSE)
Downloads 15 (556,076)
Citation 1
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94.

A Time-Varying Parameter Model for Local Explosions

Tinbergen Institute Discussion Paper 2018-088/III
Number of pages: 39 Posted: 10 Dec 2018
Francisco Blasques, Siem Jan Koopman and Marc Nientker
VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics and VU University Amsterdam
Downloads 14 (562,278)

Abstract:

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bubbles, observation driven models, noncausal models, stationary, ergodic, consistency, asymptotic normality, exchange rates

95.

Measuring Synchronization and Convergence of Business Cycles for the Euro Area, UK and US

Oxford Bulletin of Economics and Statistics, Vol. 70, Issue 1, pp. 23-51, February 2008
Number of pages: 29 Posted: 18 Jan 2008
Siem Jan Koopman and João Valle E. Azevedo
Vrije Universiteit Amsterdam - School of Business and Economics and affiliation not provided to SSRN
Downloads 14 (562,278)
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96.

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

Tinbergen Institute Discussion Paper, TI 2017-062/III
Number of pages: 42 Posted: 21 Jul 2017
Siem Jan Koopman and Rutger Lit
Vrije Universiteit Amsterdam - School of Business and Economics and VU University Amsterdam
Downloads 13 (568,440)
Citation 1

Abstract:

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Football, Forecasting, Score-driven models, Bivariate Poisson, Skellam, Ordered probit, Probabilistic loss function

97.

Accelerating GARCH and Score-Driven Models: Optimality, Estimation and Forecasting

Number of pages: 39 Posted: 21 Jul 2017
Francisco Blasques, Paolo Gorgi and Siem Jan Koopman
VU University Amsterdam, VU University Amsterdam - Faculty of Economics and Business Administration and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 10 (587,567)

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GARCH models, Kullback-Leibler divergence, score-driven models, S&P 500 stocks, time-varying parameters, US inflation

98.

Partially Censored Posterior for Robust and Efficient Risk Evaluation

Tinbergen Institute Discussion Paper 2019-057/III
Number of pages: 33 Posted: 22 Aug 2019
VU University Amsterdam, VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics and Tinbergen Institute
Downloads 4 (627,407)

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Bayesian Inference, Censored Likelihood, Censored Posterior, Partially Censored Posterior, Misspecification, Density Forecasting, Markov Chain Monte Carlo, Importance Sampling, Mixture of Student's T, Value-At-Risk, Expected Shortfall

99.

*Periodic Unobserved Cycles in Seasonal Time Series with an Application to Us Unemployment

Oxford Bulletin of Economics and Statistics, Vol. 71, Issue 5, pp. 683-713, October 2009
Number of pages: 31 Posted: 13 Oct 2009
Siem Jan Koopman, Marius Ooms and Irma Hindrayanto
Vrije Universiteit Amsterdam - School of Business and Economics, VU University Amsterdam - Department of Econometrics and VU University Amsterdam
Downloads 2 (644,900)
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100.

Likelihood‐Based Dynamic Factor Analysis for Measurement and Forecasting

The Econometrics Journal, Vol. 18, Issue 2, pp. C1-C21, 2015
Number of pages: 21 Posted: 15 Jul 2015
Borus Jungbacker and Siem Jan Koopman
VU University Amsterdam - Department of Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 1 (657,017)
Citation 3
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EM algorithm, Kalman filter, Latent factors, Maximum likelihood, State space form

101.

Periodic Seasonal REG-ARFIMA-GARCH Models for Daily Electricity Spot Prices

Journal of the American Statistical Association, Vol. 102, No. 477, pp. 16-27, March 2007
Posted: 09 Jul 2007
Siem Jan Koopman, Marius Ooms and M. Angeles Carnero
Vrije Universiteit Amsterdam - School of Business and Economics, VU University Amsterdam - Department of Econometrics and Universidad de Alicante - Department of Economic Analysis

Abstract:

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Autoregressive fractionally integrated moving average model, Generalised autoregressive conditional heteroskedasticity model, Long memory process, Periodic autoregressive model, Volatility

102.

Testing the Assumptions Behind the Use of Importance Sampling

Nuffield College, Oxford, Economics Working Paper No. 2002-W17
Posted: 13 Aug 2002
Siem Jan Koopman and Neil Shephard
Vrije Universiteit Amsterdam - School of Business and Economics and Harvard University

Abstract:

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Extreme value theory, Importance sampling, Simulation, Stochastic Volatility

103.

Signal Extraction and the Formulation of Unobserved Components Models

CentER Discussion Paper Series No. 1999-44
Posted: 18 Feb 2000
A. Harvey and Siem Jan Koopman
Tilburg University, CentER and Vrije Universiteit Amsterdam - School of Business and Economics

Abstract:

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104.

Time Series Analysis of Non-Gaussian Observations Based on State Space Models from Both Classical and Bayesian Perspectives

Tilburg University, CentER Working Paper No. 1998-142
Posted: 10 Aug 1999
J. Durbin and Siem Jan Koopman
Tilburg University, CentER and Vrije Universiteit Amsterdam - School of Business and Economics

Abstract:

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105.

Fast Filtering and Smoothing for Multivariate State Space Models

Tilburg University, Center for Economic Research Discussion Paper Series No. 1998-18
Posted: 18 Nov 1998
Siem Jan Koopman and J. Durbin
Vrije Universiteit Amsterdam - School of Business and Economics and London School of Economics & Political Science (LSE)

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