Welcome to the website of Jeroen V.K. Rombouts 

Associate professor at HEC-Montreal

My CV (pdf)

Email: jeroen.rombouts@hec.ca

Phone:    1-514-340-6466

Address:    3000, chemin de la Côte Sainte-Catherine

Montréal (Québec), Canada

                  H3T 2A7                 

Research interests: Finance, Econometrics and Statistics.

Publications

1. Bauwens, L., Preminger, A., Rombouts, J.V.K., (2010), Theory and Inference for a Markov Switching GARCH Model, forthcoming in Econometrics Journal.

2. Bouezmarni, T., Rombouts, J.V.K., (2010), Nonparametric Density Estimation for Multivariate Bounded Data, Journal of Statistical Planning and Inference, 140, 139-152.

3. Bouezmarni, T., Rombouts, J.V.K., Taamouti, A., (2010), Asymptotic Properties of the Bernstein Density Copula for Dependent Data, Journal of Multivariate Analysis, 101, 1-10.

4. Bouezmarni, T., Rombouts, J.V.K., (2009), Nonparametric Density Estimation for Positive Time Series, Computational Statistics and Data Analysis, 53, 2040-2054.

5. Bouaddi, M., Rombouts, J.V.K., (2009), Mixed Exponential Power Asymmetric Conditional Heteroskedasticity, Studies on Nonlinear Dynamics and Econometrics, 13, 1-30.

6. Verbeek, M., Rombouts, J.V.K., (2009), Evaluating Portfolio Value-at-Risk using Semi-parametric GARCH Models, Quantitative Finance, 9, 737-745.

7. Bouezmarni, T., Rombouts, J.V.K., (2008), Nonparametric Density and Hazard Function Estimation for Censored Positive Time Series, Journal of Nonparametric statistics, 7, 627-643.

8. Bouezmarni, T., Rombouts, J.V.K., (2008), Semiparametric Multivariate Density Estimation for Positive Data Using Copulas, Computational Statistics and Data Analysis, 53, 2040-2054.

9. Bauwens, L., Rombouts, J.V.K., (2007), Bayesian Inference for the Mixed Conditional Heteroskedasticity Model. Econometrics Journal, 10, 408-425.

10. Bauwens, L., Hafner, C.M., Rombouts, J.V.K., (2007), Mixed Normal Multivariate Conditional Heteroskedasticity. Computational Statistics and Data Analysis, 51, 3551-3566.

11. Bauwens, L., Rombouts, J.V.K., (2007), Bayesian Clustering of Many GARCH Models. Econometric Reviews. 26, 365-386.

12. Hafner, C.M., Rombouts, J.V.K., (2007), Semiparametric Multivariate Volatility Models. Econometric Theory, 23, 251-280.

13. Hafner, C.M., Rombouts, J.V.K., (2007), Estimation of Temporally Aggregated Multivariate GARCH Models, Journal of Statistical Computation and Simulation, 77, 629-650.

14. Bauwens, L., Laurent, S., Rombouts, J.V.K., (2006), multivariate GARCH models: A survey, Journal of Applied Econometrics, 21, 79-109.

15. Mouchart, M., Rombouts, J.V.K., (2005), Clustered Panel data models: An efficient approach for nowcasting from poor data, International Journal of Forecasting, 21, 577-594.

16.  Bauwens, L., Rombouts, J.V.K., (2004), Econometrics, Handbook of Computational Statistics, Springer-Verlag, Berlin.

Working papers

1. Bauwens, L., Bauwens, J.V.K., (2009), On Marginal Likelihood Computation in Change-Point Models, CIRPEE and CORE discussion paper (submitted).

2. Bouezmarni, T., Rombouts, J.V.K., Taamouti, A., (2009), A Nonparametric Copula Based Test for Conditional Independence with Applications to Granger Causality, CIRANO, CIRPEE and CORE discussion paper. Revised version (submitted)

3. Rombouts, J.V.K., Stentoft, L., (2008), Bayesian Option Pricing Using Mixed Normal Heteroskedasticity Models, CORE discussion paper (submitted).

4. Laurent, S., Rombouts, J.V.K., Violante, F., (2009), On Loss Functions and Ranking Forecasting Performances of Multivariate Volatility Models, CIRANO and CIRPEE discussion paper (submitted). Previously circulated as “Consistent Ranking of Multivariate Volatility Models”.

5. Meier, I, Rombouts, J.V.K. (2008), Style Rotation and Performance Persistence of Mutual Funds (submitted)

Work in progress

1. Rombouts, J.V.K., (20XX), Inference for Multivariate Stochastic Volatility Models.

2. Laurent, S., Rombouts, J.V.K., Violante, F., (2009), How to choose a multivariate GARCH model? A model confidence set approach.

3. Bauwens, L., Rombouts, J.V.K., (2009), Multiple State Markov Switching Models.