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Research Output 2007 2019

  • 24 Article
  • 17 Working paper
  • 4 Chapter
  • 2 PhD Thesis - Research VU, graduation VU
2019

Forecast density combinations of dynamic models and data driven portfolio strategies

Baştürk, N., Borowska, A., Grassi, S., Hoogerheide, L. & van Dijk, H. K., 2019, (Accepted/In press) In : Journal of Econometrics.

Research output: Contribution to JournalArticleAcademicpeer-review

Portfolio strategy
Density forecasts
Diagnostics
Empirical results
Modeling
2018

Forecast Density Combinations of Dynamic Models and Data Driven Portfolio Strategies

Basturk, N., Borowska, A., Grassi, S., Hoogerheide, L. F. & van Dijk, H. H. K. ., 2018, Amsterdam: Tinbergen Institute, 53 p. (TI Discussion Paper Series; vol. 18-076/III).

Research output: Working paperAcademic

Learning to Average Predictively over Good and Bad: Comment on: Using Stacking to Average Bayesian Predictive Distributions

Hoogerheide, L. F. & van Dijk, H. H. K. ., 2018, Amsterdam: Tinbergen Institute, 9 p. (TI Discussion Paper Series; vol. 18-063/III).

Research output: Working paperAcademic

Methods for computing numerical standard errors: Review and application to value-at-risk estimation

Ardia, D., Bluteau, K. & Hoogerheide, L. F., 26 Jul 2018, In : Journal of Time Series Econometrics. 10, 2, 20170011.

Research output: Contribution to JournalArticleAcademicpeer-review

Autocorrelation
Value at risk
Standard error
Simulation
Estimator
2017

A new bootstrap test for multiple assets joint risk testing

Ardia, D., Gatarek, L. & Hoogerheide, L. F., 2017, In : Journal of Risk. 19, 4, p. 1-22 22 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Bootstrap test
Testing
Assets
Dependence structure
Value at risk

Bayesian Analysis of Boundary and Near-Boundary Evidence in Econometric Models with Reduced Rank

Basturk, N., Hoogerheide, L. F. & van Dijk, H. K., 2017, Amsterdam: Tinbergen Institute, 91 p. (TI Discussion Paper Series; vol. 17, no. 058/III).

Research output: Working paperProfessional

Bayesian Analysis of Boundary and Near-Boundary Evidence in Econometric Models with Reduced Rank

Basturk, N., Hoogerheide, L. F. & van Dijk, H. K., 2017, In : Bayesian Analysis. 12, 3, p. 879-917

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access

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

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

Research output: Contribution to JournalArticleAcademicpeer-review

metropolis
simulation
methodology
performance
evidence

The Econometrics of Financial Comovement

Silde, E., 2017, 691 ed. Amsterdam: Tinbergen Institute. 240 p.

Research output: PhD ThesisPhD Thesis - Research VU, graduation VUAcademic

Open Access
File

The R-package MitISEM: Efficient and Robust Simulation Procedures for Bayesian Inference

Basturk, N., Grassi, S., Hoogerheide, L. F., Opschoor, A. & van Dijk, H. K., 2017, In : Journal of Statistical Software. 79, 1, p. 1-40

Research output: Contribution to JournalArticleProfessional

Open Access
2016

Bayesian analysis of latent variable models in finance

Barra, I., 2016, Amsterdam: Tinbergen Institute. 164 p.

Research output: PhD ThesisPhD Thesis - Research VU, graduation VUAcademic

Open Access
File

Parallelization Experience with Four Canonical Econometric Models using ParMitISEM

Basturk, N., Grassi, S., Hoogerheide, L. F. & van Dijk, H. K., 2016, Amsterdam: Tinbergen Institute, 26 p. (TI Discussion Paper; no. 16-005/III).

Research output: Working paperProfessional

Time-varying Combinations of Bayesian Dynamic Models and Equity Momentum Strategies

Basturk, N., Grassi, S., Hoogerheide, L. F. & van Dijk, H. K., 2016, Amsterdam: Tinbergen Institute, 44 p. (TI Discussion Papers; no. 99/III).

Research output: Working paperProfessional

2015

The R-package MitISEM: Efficient and Robust Simulation Procedures for Bayesian Inference

Basturk, N., Grassi, S., Hoogerheide, L. F., Opschoor, A. & van Dijk, H. K., 2015, Amsterdam: Tinbergen Institute, 42 p. (TI Discussion Paper; no. 15-042/III).

Research output: Working paperProfessional

2014

Analysis of historical time series with messy features: the case of commodity prices in Babylonia

Koopman, S. J. & Hoogerheide, L. F., 2014, A History of Market Performance: From Ancient Babylonia to the Modern World. van der Spek, R. J., Luiten van Zanden, J. & van Leeuwen, B. (eds.). New York: Routledge, p. 45-67 592 p.

Research output: Chapter in Book / Report / Conference proceedingChapterAcademic

A New Bootstrap Test for the Validity of a Set of Marginal Models for Multiple Dependent Time Series: An Application to Risk Analysis

Ardia, D., Gatarek, L. & Hoogerheide, L. F., 2014, Amsterdam: Tinbergen Institute, 27 p. (TI Discussion Paper; no. 14-028/III).

Research output: Working paperProfessional

Bayesian Analysis of Instrumental Variable Models: Acceptance-Rejection within Direct Monte Carlo

Zellner, A., Ando, T., Basturk, N., Hoogerheide, L. F. & van Dijk, H. K., 2014, In : Econometric Reviews. 33, 1-4, p. 3-35

Research output: Contribution to JournalArticleAcademicpeer-review

Acceptance
Instrumental variables
Bayesian analysis
Evaluation
Endogenous regressors

GARCH models for daily stock returns: Impact of estimation frequency on Value-at-Risk and Expected Shortfall forecasts

Ardia, D. & Hoogerheide, L. F., 2014, In : Economics Letters. 123, 2, p. 187-190

Research output: Contribution to JournalArticleAcademicpeer-review

GARCH model
Value at risk
Stock returns
Expected shortfall
Methodology

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

Barra, I., Hoogerheide, L. F., Koopman, S. J. & Lucas, A., 2014, Amsterdam: Tinbergen Institute, 36 p. (TI Discussion Paper; no. 14-118/III).

Research output: Working paperProfessional

Netherlands
finance
school

Return and Risk of Pairs Trading using a Simulation-based Bayesian Procedure for Predicting Stable Ratios of Stock Prices

Gatarek, L., Hoogerheide, L. F. & van Dijk, H. K., 2014, Amsterdam: Tinbergen Institute, 39 p. (TI Discussion Paper; no. 14-39/III).

Research output: Working paperProfessional

2013

Censored Posterior and Predictive Likelihood in Bayesian Left-Tail Prediction for Accurate Value at Risk Estimation

Gatarek, L., Hoogerheide, L. F., Hooning, K. & van Dijk, H. K., 2013, Amsterdam: Tinbergen Institute, 27 p. (TI Discussion Paper; no. 13-060/III).

Research output: Working paperProfessional

Education and entrepreneurial choice: An instrumental variables analysis

Block, J. H., Hoogerheide, L. F. & Thurik, A. R., 2013, In : International Small Business Journal. 31, 1, p. 23-33

Research output: Contribution to JournalArticleAcademicpeer-review

GARCH Models for Daily Stock Returns: Impact of Estimation Frequency on Value-at-Risk and Expected Shortfall Forecasts

Ardia, D. & Hoogerheide, L. F., 2013, Amsterdam: Tinbergen Institute, 18 p. (TI Discussion Paper; no. 13-047/III).

Research output: Working paperProfessional

Genome-wide analysis of macrosatellite repeat copy number variation in worldwide populations: evidence for differences and commonalities in size distributions and size restrictions

Schaap, M., Lemmers, R. J. L. F., Maassen, R., van der Vliet, P. J., Hoogerheide, L. F., van Dijk, H. K., Basturk, N., de Knijff, P. & van der Maarel, S. M., 2013, In : BMC Genomics. 14, 143, p. 1-12

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access
Human Genome
Mutation Rate
Facioscapulohumeral Muscular Dystrophy
Genome
Central Asia

Joint Independent Metropolis-Hastings Methods for Nonlinear Non-Gaussian State Space Models

Barra, I., Hoogerheide, L. F., Koopman, S. J. & Lucas, A., 2013, Amsterdam: Tinbergen Institute, 35 p. (TI Dicsussion Paper; no. 13-050/III).

Research output: Working paperProfessional

Worldwide equity risk prediction

Ardia, D. & Hoogerheide, L. F., 2013, In : Applied Economics Letters. 20, 14, p. 1333-1339 7 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Value at risk
Prediction
Equity risk
Industry
Stock index
2012

A class of adaptive importance sampling weighted EM algorithms for efficient and robust posterior and predictive simulation

Hoogerheide, L. F., Opschoor, A. & van Dijk, H. K., 2012, In : Journal of Econometrics. 171, 2, p. 101-120 20 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Importance sampling
EM algorithm
Simulation
Mixture model
Approximation

A Class of Adaptive Importance Sampling Weighted EM Algorithms for Efficient and Robust Posterior and Predictive Simulation

Hoogerheide, L. F., Opschoor, A. & van Dijk, H. K., 2012, Amsterdam: Tinbergen Institute, 37 p. (TI Discussion Paper; no. 12-026/4).

Research output: Working paperProfessional

File

A Comparative Study of Monte Carlo Methods for Efficient Evaluation of marginal likelihood

Hoogerheide, L. F., Ardia, D. & van Dijk, H. K., 2012, In : Computational Statistics and Data Analysis. 56, 11, p. 3398-3414

Research output: Contribution to JournalArticleAcademicpeer-review

Are education and entrepreneurial income endogenous?

Block, J. H., Hoogerheide, L. F. & Thurik, A. R., 2012, In : Entrepreneurship Research Journal. 2, 3, p. 1-27

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access
File

Bayesian Analysis of Instrumental Variable Models: Acceptance-Rejection within Direct Monte Carlo

Zellner, A., Ando, T., Basturk, N., Hoogerheide, L. F. & van Dijk, H. K., 2012, Amsterdam: Tinbergen Institute, 35 p. (TI Discussion Paper; no. 12-098/III).

Research output: Working paperProfessional

File

Comment on Forecast Rationality Tests Based on Multi-Horizon Bounds

Hoogerheide, L. F., Ravazzolo, F. & van Dijk, H. K., 2012, In : Journal of Business and Economic Statistics. 30, 1, p. 30-33

Research output: Contribution to JournalArticleAcademicpeer-review

Family background variables as instruments for education in income regressions: a Bayesian analysis

Hoogerheide, L. F., Block, J. H. & Thurik, A. R., 2012, In : Economics of Education Review. 31, 5, p. 515-523

Research output: Contribution to JournalArticleAcademicpeer-review

income
regression
education
SOEP
exclusion

Stock index returns' density prediction using GARCH models: Frequentist or Bayesian estimation?

Hoogerheide, L. F., Ardia, D. & Corre, N., 2012, In : Economics Letters. 116, 3, p. 322-325 4 p.

Research output: Contribution to JournalArticleAcademicpeer-review

GARCH model
Bayesian estimation
Stock index
Density forecasts
Bayesian approach

The R Package MitISEM: Mixture of Student-t Distributions using Importance Sampling Weighted Expectation Maximization for Efficient and Robust Simulation

Basturk, N., Hoogerheide, L. F., Opschoor, A. & van Dijk, H. K., 2012, Amsterdam: Tinbergen Institute, 32 p. (TI Discussion Paper; no. 12-096/III).

Research output: Working paperProfessional

File
2011
Open Access
File

Instrumental Variables, Errors in Variables, and Simultaneous Equations Models: Applicability and Limitations of Direct Monte Carlo

Zellner, A., Ando, T., Basturk, N., Hoogerheide, L. F. & van Dijk, H. K., 2011, Amsterdam: Tinbergen Institute, 38 p. (TI Discussion Papers; no. 11-137/4).

Research output: Working paperProfessional

File

Simulation Based Bayes Procedures for Model Structures with Non-Elliptical Posteriors

Hoogerheide, L. F. & van Dijk, H. K., 2011, International Encyclopedia of Statistical Science. Lovric, M. (ed.). Springer, p. 1332-1335

Research output: Chapter in Book / Report / Conference proceedingChapterAcademicpeer-review

2010

Bayesian estimation of the GARCH(1,1) model with student-t innovations

Ardia, D. & Hoogerheide, L. F., 2010, In : The R Journal. 2, 2, p. 41-47 7 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Generalized Autoregressive Conditional Heteroscedasticity
Bayesian Estimation
Exchange rate
Markov Chain Monte Carlo
Tuning

Bayesian Forecasting of Value at Risk and Expected Shortfall using Adaptive Importance Sampling

Hoogerheide, L. F. & van Dijk, H. K., 2010, In : International Journal of Forecasting. 26, 2, p. 231-247 17 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Importance sampling
Value at risk
Bayesian forecasting
Expected shortfall
Approximation

Efficient Bayesian Estimation and Combination of GARCH-type Models

Ardia, D. & Hoogerheide, L. F., 2010, Rethinking Risk Measurement and Reporting - Volume II: Examples and Applications from Finance. Bocker, K. (ed.). London: RiskBooks, p. 3-29

Research output: Chapter in Book / Report / Conference proceedingChapterAcademicpeer-review

Forecast Accuracy and Economic Gains from Bayesian Model Averaging using Time Varying Weights

Hoogerheide, L. F., Kleijn, R., Ravazzolo, F., van Dijk, H. K. & Verbeek, M., 2010, In : Journal of Forecasting. 29, p. 251-269 19 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Bayesian Model Averaging
Forecast
Time-varying
Economics
Business Cycles
2009

Adaptive mixture of Student-t distributions as a flexible candidate distribution for efficient simulation: the R package AdMit

Ardia, D., Hoogerheide, L. F. & van Dijk, H. K., 2009, In : Journal of Statistical Software. 29, 3, p. 1-32 32 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access
File

AdMit: Adaptive mixtures of student-t distributions

Ardia, D., Hoogerheide, L. F. & van Dijk, H. K., 2009, In : The R Journal. 1, 1, p. 25-30 6 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Simulation-Based Bayesian Econometric Inference: Principles and Some Recent Computational Advances

Hoogerheide, L. F., van Dijk, H. K. & van Oest, R. D., 2009, Handbook of Computational Econometrics. Belsley, D. A. & Kontoghiorghes, E. J. (eds.). John Wiley & Sons, Ltd, p. 215-280 66 p.

Research output: Chapter in Book / Report / Conference proceedingChapterAcademicpeer-review

2007

Natural conjugate priors for the instrumental variables regression model applied to the Angrist-Krueger data

Hoogerheide, L. F., Kleibergen, F. & van Dijk, H. K., 2007, In : Journal of Econometrics. 138, 1, p. 63-103 41 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Instrumental variables regression
Regression model
Structural parameters
Education
Maximum likelihood estimator

On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: an application of flexible sampling methods using neural networks

Hoogerheide, L. F., Kaashoek, J. F. & van Dijk, H. K., 2007, In : Journal of Econometrics. 139, 1, p. 154-180 27 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Instrumental variables regression
Regression model
Sampling methods
Neural networks
Endogeneity