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Research Output 2007 2019

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

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, 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 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
2014

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
2013

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

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

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 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

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
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

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

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