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

  • Vrije Universiteit Amsterdam - School of Business and Economics

    • Email
    • Tel: +31205986019

  • Tinbergen Institute

  • Aarhus University - CREATES

SCHOLARLY PAPERS

107

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278

CROSSREF CITATIONS

339

Scholarly Papers (107)

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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 1,012 (24,225)
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 982 (25,289)
Citation 12

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

3.

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 934 (27,142)
Citation 11

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

4.

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 930 (27,331)

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

5.

Systemic Risk Diagnostics: Coincident Indicators and Early Warning Signals

Downloads 691 ( 41,202)
Citation 9

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 497 (62,398)

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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 194 (174,260)
Citation 10

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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 576 (52,401)
Citation 13

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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 554 (54,965)
Citation 16

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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 535 (57,492)
Citation 34

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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 499 (62,743)
Citation 2

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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
Siem Jan Koopman, Roman Kräussl, Andre Lucas and Andre A. Monteiro
Vrije Universiteit Amsterdam - School of Business and Economics, Luxembourg School of Finance, Vrije Universiteit Amsterdam - School of Business and Economics and Tinbergen Institute
Downloads 419 (77,583)
Citation 2

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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 410 (79,594)
Citation 2

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

12.

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 365 (91,040)
Citation 16

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13.

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 361 (92,224)
Citation 6

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

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 353 (94,661)
Citation 20

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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 306 (110,855)

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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
Dick J. C. van Dijk, Siem Jan Koopman, Michel van der Wel and Jonathan H. Wright
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 299 (113,675)
Citation 10

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

17.

Time Varying Transition Probabilities for Markov Regime Switching Models

Downloads 279 (122,277)
Citation 6

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 Padova, VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 278 (122,099)
Citation 5

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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 Padova, VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 1 (755,609)
Citation 2
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Hidden Markov models, observation driven models, time varying parameter

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
Downloads 279 (122,277)
Citation 18

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

19.

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 278 (122,759)
Citation 1

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

20.

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 256 (133,783)

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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

21.

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 254 (134,843)
Citation 1

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

22.

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 247 (138,719)
Citation 2

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

23.

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 245 (139,857)
Citation 4

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

24.

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 220 (155,044)
Citation 4

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

25.

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 214 (159,034)
Citation 4

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

26.

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
V. Dordonnat, Siem Jan Koopman, Marius Ooms, A. Dessertaine and Jérôme Collet
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 211 (161,123)

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

27.

Generalized autoregressive Method of Moments

Downloads 206 (164,835)
Citation 4

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 168 (198,173)
Citation 2

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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 38 (489,349)
Citation 2

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

28.

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 200 (169,540)
Citation 11

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

29.

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 194 (174,401)
Citation 16

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dynamic dependence, multivariate Student's t distribution, copula

30.

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 187 (180,277)
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

31.

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 175 (191,136)
Citation 2

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

32.

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 155 (212,009)
Citation 8

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

33.

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
Frits Bijleveld, Jacques Commandeur, Phillip Gould and Siem Jan Koopman
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 152 (215,456)

Abstract:

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Actuarial statistics, Dynamic factor analysis

34.

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

Downloads 150 (217,873)
Citation 14

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 108 (281,099)
Citation 13

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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 42 (470,958)

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

35.

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 148 (220,158)
Citation 14

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

36.

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 143 (226,417)
Citation 3

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

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 142 (227,610)
Citation 1

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

38.

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 141 (228,886)
Citation 1

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

39.

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 141 (228,886)
Citation 15

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

40.

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 140 (230,218)
Citation 27

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

41.

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 135 (237,065)
Citation 1

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

42.

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 (239,845)

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43.

Modeling Trigonometric Seasonal Components for Monthly Economic Time Series

Tinbergen Institute Discussion Paper 10-018/4
Number of pages: 20 Posted: 06 Feb 2010
Irma Hindrayanto, John A.D. Aston, Siem Jan Koopman and Marius Ooms
VU University Amsterdam, University of Warwick, Vrije Universiteit Amsterdam - School of Business and Economics and VU University Amsterdam - Department of Econometrics
Downloads 130 (244,061)

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

44.

Bayesian Risk Forecasting for Long Horizons

Tinbergen Institute Discussion Paper 2019-018/III
Number of pages: 40 Posted: 13 Mar 2019
Agnieszka Borowska, Lennart F. Hoogerheide and Siem Jan Koopman
VU University Amsterdam, VU University Amsterdam and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 125 (251,446)

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

45.

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 124 (253,004)
Citation 1

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

46.

Likelihood Functions for State Space Models with Diffuse Initial Conditions

Downloads 113 (270,778)
Citation 4

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 111 (275,627)
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 (741,372)
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47.

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 112 (272,486)

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

48.

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 110 (275,935)
Citation 11

Abstract:

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

49.

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 109 (277,695)
Citation 2

Abstract:

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

50.

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
Francisco Blasques, Siem Jan Koopman, Andre Lucas and Julia Schaumburg
VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics, Vrije Universiteit Amsterdam - School of Business and Economics and Tinbergen Institute
Downloads 96 (302,474)
Citation 7

Abstract:

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

51.

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 95 (304,484)
Citation 1

Abstract:

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Kalman filter, Monte Carlo maximum likelihood, simulation smoothing

52.

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 (308,722)
Citation 16

Abstract:

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

53.

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 92 (310,856)
Citation 11

Abstract:

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

54.

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 91 (312,969)
Citation 4

Abstract:

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

55.

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 91 (312,969)
Citation 1

Abstract:

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Kalman filter, Monte Carlo maximum likelihood, simulation smoothing

56.

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 91 (312,969)

Abstract:

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

57.

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 89 (317,315)
Citation 7

Abstract:

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

58.

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 89 (317,315)
Citation 1

Abstract:

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

59.

The Information in Systemic Risk Rankings

Downloads 88 (319,591)
Citation 13

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 48 (445,348)
Citation 4

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 40 (480,116)
Citation 4

Abstract:

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

60.

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 88 (319,591)
Citation 4

Abstract:

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Kalman filter, leverage, realised volatility, simulated maximum likelihood

61.

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 (321,884)
Citation 3

Abstract:

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

62.

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 85 (326,534)
Citation 5

Abstract:

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

63.

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 85 (326,534)
Citation 1

Abstract:

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

64.

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 80 (338,607)

Abstract:

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

65.

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 79 (341,166)
Citation 2

Abstract:

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

66.

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 77 (346,278)

Abstract:

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

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 71 (362,347)

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 (379,701)
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.

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 63 (385,863)
Citation 2

Abstract:

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

70.

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 (385,863)

Abstract:

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

71.

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 60 (395,301)
Citation 1

Abstract:

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

72.

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
Istvan Barra, Lennart F. Hoogerheide, Siem Jan Koopman and Andre Lucas
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 (395,301)

Abstract:

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

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 59 (398,626)
Citation 21

Abstract:

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

74.

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
Jasper de Winter, Siem Jan Koopman, Irma Hindrayanto and Anjali Chouhan
De Nederlandsche Bank, Vrije Universiteit Amsterdam - School of Business and Economics, De Nederlandsche Bank and Independent
Downloads 54 (415,702)
Citation 1

Abstract:

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

75.

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
Gabriele Galati, Irma Hindrayanto, Siem Jan Koopman and Marente Vlekke
De Nederlandsche Bank, De Nederlandsche Bank, Vrije Universiteit Amsterdam - School of Business and Economics and CPB Netherlands Bureau of Economic Policy Analysis
Downloads 54 (415,702)
Citation 16

Abstract:

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

76.

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 53 (419,240)
Citation 1

Abstract:

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

77.

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 (433,769)

Abstract:

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

78.

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

Downloads 48 (437,529)
Citation 2

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 (531,194)

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 18 (611,885)
Citation 2

Abstract:

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

79.

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
Francisco Blasques, Siem Jan Koopman, Katarzyna Lasak and Andre Lucas
VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics, VU Amsterdam and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 46 (445,329)
Citation 6

Abstract:

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

80.

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 45 (449,308)
Citation 2

Abstract:

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

81.

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 43 (457,517)
Citation 1

Abstract:

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

82.

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 42 (461,633)
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

83.

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 40 (470,225)

Abstract:

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

84.

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 36 (487,967)
Citation 25

Abstract:

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

85.

Beta Observation-Driven Models With Exogenous Regressors: A Joint Analysis of Realized Correlation and Leverage Effects

Tinbergen Institute Discussion Paper 20-004/III
Number of pages: 38 Posted: 24 Feb 2020
Paolo Gorgi and Siem Jan Koopman
VU University Amsterdam - Faculty of Economics and Business Administration and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 33 (502,310)

Abstract:

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Double bounded time series, financial econometrics, leverage effects, observation- driven models, realized correlation

86.

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
Gabriele Galati, Irma Hindrayanto, Siem Jan Koopman and Marente Vlekke
De Nederlandsche Bank, De Nederlandsche Bank, Vrije Universiteit Amsterdam - School of Business and Economics and CPB Netherlands Bureau of Economic Policy Analysis
Downloads 29 (523,003)
Citation 5

Abstract:

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

87.

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 27 (534,274)
Citation 1

Abstract:

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

88.

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
Jacques Commandeur, Suncica Vujic, Siem Jan Koopman and Barbara Kasprzyk-Hordern
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 (534,274)

Abstract:

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

89.

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 26 (540,093)

Abstract:

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

90.

Constructing Seasonally Adjusted Data with Time-Varying Confidence Intervals

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 (540,093)
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91.

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 25 (546,206)
Citation 1

Abstract:

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

92.

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
Francisco Blasques, Paolo Gorgi, Siem Jan Koopman and Olivier Wintenberger
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 22 (565,019)
Citation 1

Abstract:

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invertibility, quasi-maximum likelihood estimator, volatility models

93.

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
Francisco Blasques, Paolo Gorgi, Siem Jan Koopman and Olivier Wintenberger
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 (577,910)
Citation 6

Abstract:

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

94.

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
Francisco Blasques, Siem Jan Koopman, Katarzyna Lasak and Andre Lucas
VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics, VU Amsterdam and Vrije Universiteit Amsterdam - School of Business and Economics
Downloads 18 (591,100)

Abstract:

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

95.

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 17 (597,622)
Citation 2

Abstract:

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

96.

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 15 (611,013)

Abstract:

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

97.

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

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 (611,013)
Citation 2
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98.

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 (617,936)
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99.

Partially Censored Posterior for Robust and Efficient Risk Evaluation

Tinbergen Institute Discussion Paper 2019-057/III
Number of pages: 33 Posted: 22 Aug 2019
Agnieszka Borowska, Lennart F. Hoogerheide, Siem Jan Koopman and Herman van Dijk
VU University Amsterdam, VU University Amsterdam, Vrije Universiteit Amsterdam - School of Business and Economics and Tinbergen Institute
Downloads 8 (660,752)

Abstract:

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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

100.

Estimation of Final Standings in Football Competitions with Premature Ending: The Case of COVID-19

Tinbergen Institute Discussion Paper 2020-070/III
Number of pages: 23 Posted: 14 Oct 2020 Last Revised: 15 Oct 2020
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 6 (675,386)

Abstract:

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Bivariate Poisson, COVID-19, paired-comparison models, sport statistics

101.

*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 (708,603)
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102.

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
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EM algorithm, Kalman filter, Latent factors, Maximum likelihood, State space form

103.

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

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

104.

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

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Extreme value theory, Importance sampling, Simulation, Stochastic Volatility

105.

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

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106.

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

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107.

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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