Luca Margaritella
Personal Details
First Name: | Luca |
Middle Name: | |
Last Name: | Margaritella |
Suffix: | |
RePEc Short-ID: | pma2743 |
[This author has chosen not to make the email address public] | |
Affiliation
Vakgroep Kwantitatieve Economie
School of Business and Economics
Maastricht University
Maastricht, Netherlandshttp://www.maastrichtuniversity.nl/web/Faculties/SBE/Theme/Departments/QuantitativeEconomics.htm
RePEc:edi:dqmaanl (more details at EDIRC)
Research output
Jump to: Working papersWorking papers
- Alain Hecq & Luca Margaritella & Stephan Smeekes, 2019.
"Granger Causality Testing in High-Dimensional VARs: a Post-Double-Selection Procedure,"
Papers
1902.10991, arXiv.org, revised Dec 2020.
- Alain Hecq & Luca Margaritella & Stephan Smeekes, 2023. "Granger Causality Testing in High-Dimensional VARs: A Post-Double-Selection Procedure," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 21(3), pages 915-958.
Citations
Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.Working papers
- Alain Hecq & Luca Margaritella & Stephan Smeekes, 2019.
"Granger Causality Testing in High-Dimensional VARs: a Post-Double-Selection Procedure,"
Papers
1902.10991, arXiv.org, revised Dec 2020.
- Alain Hecq & Luca Margaritella & Stephan Smeekes, 2023. "Granger Causality Testing in High-Dimensional VARs: A Post-Double-Selection Procedure," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 21(3), pages 915-958.
Cited by:
- Miao, Ke & Phillips, Peter C.B. & Su, Liangjun, 2023.
"High-dimensional VARs with common factors,"
Journal of Econometrics, Elsevier, vol. 233(1), pages 155-183.
- Ke Miao & Peter C.B. Phillips & Liangjun Su, 2020. "High-Dimensional VARs with Common Factors," Cowles Foundation Discussion Papers 2252, Cowles Foundation for Research in Economics, Yale University.
- Gianluca Cubadda & Alain Hecq, 2022.
"Dimension Reduction for High Dimensional Vector Autoregressive Models,"
CEIS Research Paper
534, Tor Vergata University, CEIS, revised 24 Mar 2022.
- Gianluca Cubadda & Alain Hecq, 2020. "Dimension Reduction for High Dimensional Vector Autoregressive Models," Papers 2009.03361, arXiv.org, revised Feb 2022.
- Gianluca Cubadda & Alain Hecq, 2022. "Dimension Reduction for High‐Dimensional Vector Autoregressive Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(5), pages 1123-1152, October.
- Adam Jassem & Lenard Lieb & Rui Jorge Almeida & Nalan Bac{s}turk & Stephan Smeekes, 2021. "Min(d)ing the President: A text analytic approach to measuring tax news," Papers 2104.03261, arXiv.org, revised May 2022.
- Mansour-Ichrakieh, Layal, 2020. "The impact of Israeli Geopolitical Risks on the Lebanese Financial Market: A Destabilizer Multiplier," MPRA Paper 99376, University Library of Munich, Germany.
- Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2020.
"Machine Learning Advances for Time Series Forecasting,"
Papers
2012.12802, arXiv.org, revised Apr 2021.
- Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2023. "Machine learning advances for time series forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 76-111, February.
- Robert Adamek & Stephan Smeekes & Ines Wilms, 2020.
"Lasso Inference for High-Dimensional Time Series,"
Papers
2007.10952, arXiv.org, revised Sep 2022.
- Adamek, Robert & Smeekes, Stephan & Wilms, Ines, 2023. "Lasso inference for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 235(2), pages 1114-1143.
- Jonas Krampe & Luca Margaritella, 2021. "Factor Models with Sparse VAR Idiosyncratic Components," Papers 2112.07149, arXiv.org, revised May 2022.
- Alain Hecq & Marie Ternes & Ines Wilms, 2021. "Hierarchical Regularizers for Mixed-Frequency Vector Autoregressions," Papers 2102.11780, arXiv.org, revised Mar 2022.
More information
Research fields, statistics, top rankings, if available.Statistics
Access and download statistics for all items
Co-authorship network on CollEc
NEP Fields
NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 1 paper announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.- NEP-ECM: Econometrics (1) 2019-03-04. Author is listed
- NEP-ETS: Econometric Time Series (1) 2019-03-04. Author is listed
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.
To update listings or check citations waiting for approval, Luca Margaritella should log into the RePEc Author Service.
To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.
To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.
Please note that most corrections can take a couple of weeks to filter through the various RePEc services.