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Is CAViaR model really so good in Value at Risk forecasting? : evidence from evaluation of a quality of Value-at-Risk forecasts obtained based on the: GARCH(1,1), GARCH-t(1,1), GARCH-st(1,1), QML-GARCH(1,1), CAViaR and the historical simulation models depending on the stability of financial markets
Buczyński, Mateusz
;
Chlebus, Marcin
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Uniwersytet Warszawski / Wydział Nauk Ekonomicznych
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2017
Persistent link: https://www.econbiz.de/10011907622
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Old-fashioned parametric models are still the best : a comparison of Value-at-Risk approaches in several volatility states
Buczyński, Mateusz
;
Chlebus, Marcin
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Uniwersytet Warszawski / Wydział Nauk Ekonomicznych
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2019
Persistent link: https://www.econbiz.de/10012041611
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3
GARCHNet - Value-at-Risk forecasting with novel approach to GARCH models based on neural networks
Buczyński, Mateusz
;
Chlebus, Marcin
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2021
Persistent link: https://www.econbiz.de/10012795155
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4
Valuing externalities of outdoor advertising in an urban setting : the case of Warsaw
Czajkowski, Mikołaj
;
Bylicki, Michał
;
Budziński, Wiktor
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2020
Persistent link: https://www.econbiz.de/10012196656
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5
EWS-GARCH : new regime switching approach to forecast value-at-risk
Chlebus, Marcin
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Uniwersytet Warszawski / Wydział Nauk Ekonomicznych
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2016
Persistent link: https://www.econbiz.de/10011788233
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Novel multilayer stacking framework with weighted ensemble approach for multiclass credit scoring problem application
Stelmach, Marek
;
Chlebus, Marcin
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2020
Persistent link: https://www.econbiz.de/10012322114
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Size does matter : a study on the required window size for optimal quality market risk models
Buczyńsk, Mateusz
;
Chlebus, Marcin
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2020
Persistent link: https://www.econbiz.de/10012322119
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Comparison of tree-based models performance in prediction of marketing campaign results using Explainable Artificial Intelligence tools
Chlebus, Marcin
;
Osika, Zuzanna
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2020
Persistent link: https://www.econbiz.de/10012322146
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9
So close and so far : finding similar tendencies in econometrics and machine learning papers : topic models comparison
Świtała, Maciej Stefan
;
Chlebus, Marcin
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2020
Persistent link: https://www.econbiz.de/10012322168
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10
Towards better understanding of complex machine learning models using explainable Artificial Intelligence (XAI) : case of Credit Scoring modelling
Kłosok, Marta
;
Chlebus, Marcin
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2020
Persistent link: https://www.econbiz.de/10012322173
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