Zobrazeno 1 - 10
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pro vyhledávání: '"Stevanovic, Dalibor"'
Autor:
Stevanović, Dalibor
Tableau d'honneur de la Faculté des études supérieures et postdoctorales, 2006-2007
L'objectif de ce mémoire est d'appliquer la méthodologie du modèle logit mixte dans le cadre de l'estimation de la demande de transport. L'idée de base es
L'objectif de ce mémoire est d'appliquer la méthodologie du modèle logit mixte dans le cadre de l'estimation de la demande de transport. L'idée de base es
Externí odkaz:
https://hdl.handle.net/20.500.11794/18510
Based on evidence gathered from a newly built large macroeconomic data set for the UK, labeled UK-MD and comparable to similar datasets for the US and Canada, it seems the most promising avenue for forecasting during the pandemic is to allow for gene
Externí odkaz:
http://arxiv.org/abs/2103.01201
We move beyond "Is Machine Learning Useful for Macroeconomic Forecasting?" by adding the "how". The current forecasting literature has focused on matching specific variables and horizons with a particularly successful algorithm. In contrast, we study
Externí odkaz:
http://arxiv.org/abs/2008.12477
In a low-dimensional linear regression setup, considering linear transformations/combinations of predictors does not alter predictions. However, when the forecasting technology either uses shrinkage or is nonlinear, it does. This is precisely the fab
Externí odkaz:
http://arxiv.org/abs/2008.01714
Publikováno v:
In International Journal of Forecasting April-June 2022 38(2):596-612
Publikováno v:
In International Journal of Forecasting October-December 2021 37(4):1338-1354
Autor:
Stevanovic, Dalibor
Avec les avancements de la technologie de l'information, les données temporelles économiques et financières sont de plus en plus disponibles. Par contre, si les techniques standard de l'analyse des séries temporelles sont utilisées, une grande q
Externí odkaz:
http://hdl.handle.net/1866/5392
Publikováno v:
In Journal of Corporate Finance February 2020 60
Autor:
Bedock, Nathan, Stevanović, Dalibor
Publikováno v:
The Canadian Journal of Economics / Revue canadienne d'Economique, 2017 May 01. 50(2), 541-570.
Externí odkaz:
https://www.jstor.org/stable/45172440
Publikováno v:
Journal of Applied Econometrics. 37:920-964
We move beyond "Is Machine Learning Useful for Macroeconomic Forecasting?" by adding the "how". The current forecasting literature has focused on matching specific variables and horizons with a particularly successful algorithm. In contrast, we study
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f00d3c7ab58e82cc07ecbfd21c3d2c07
https://doi.org/10.1002/jae.2910
https://doi.org/10.1002/jae.2910