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  • Search: subject:"dynamic model selection"
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Year of publication
Subject
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Forecasting model 5 Prognoseverfahren 5 Dynamic Model Averaging 4 Dynamic Model Selection 4 Forecasting 4 Realized Variance 4 Self-Perturbed Kalman Filter 4 TVP models 4 Volatility 4 Volatilität 4 dynamic model selection 4 Dynamische Wirtschaftstheorie 3 Economic dynamics 3 Analysis of variance 2 Bitcoin 2 State space model 2 Time series analysis 2 Varianzanalyse 2 Zeitreihenanalyse 2 Zustandsraummodell 2 cryptocurrency 2 density forecast 2 density predictions 2 dynamic model averaging 2 forecasting 2 forgetting factors 2 hierarchical modeling 2 point forecast 2 stochastic volatility 2 Bayes-Statistik 1 Bayesian inference 1 Estimation theory 1 Forecast 1 Global-local shrinkage priors 1 Prognose 1 Schätztheorie 1 Theorie 1 Theory 1 VAR model 1 VAR-Modell 1
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Online availability
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Free 8
Type of publication
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Book / Working Paper 5 Article 3
Type of publication (narrower categories)
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Working Paper 4 Arbeitspapier 3 Graue Literatur 3 Non-commercial literature 3 Article in journal 2 Aufsatz in Zeitschrift 2 Article 1
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Language
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English 7 Undetermined 1
Author
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Grassi, Stefano 6 Nonejad, Nima 4 Santucci de Magistris, Paolo 3 Feldkircher, Martin 2 Huber, Florian 2 Kastner, Gregor 2 Muglia, Camilla 2 Santabarbara, Luca 2 Gruber, Luis 1 Magistris, Paolo Santucci de 1
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Institution
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School of Economics and Management, University of Aarhus 1
Published in...
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CREATES Research Papers 1 CREATES research paper 1 Department of Economics working paper 1 Discussion papers / University of Kent, School of Economics 1 Journal of Risk and Financial Management 1 Journal of forecasting 1 Journal of risk and financial management : JRFM 1 School of Economics Discussion Papers 1
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Source
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ECONIS (ZBW) 5 EconStor 2 RePEc 1
Showing 1 - 8 of 8
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Sophisticated and small versus simple and sizeable : when does it pay off to introduce drifting coefficients in Bayesian vector autoregressions?
Feldkircher, Martin; Gruber, Luis; Huber, Florian; … - In: Journal of forecasting 43 (2024) 6, pp. 2126-2145
Persistent link: https://www.econbiz.de/10015110374
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Is Bitcoin a relevant predictor of standard & poor's 500?
Muglia, Camilla; Santabarbara, Luca; Grassi, Stefano - In: Journal of Risk and Financial Management 12 (2019) 2, pp. 1-10
Model Selection (DMS). According to our results, Bitcoin does not show any direct impact on the predictability of Standard … we compare alternative models using a point and density forecast relying on Dynamic Model Averaging (DMA) and Dynamic …
Persistent link: https://www.econbiz.de/10012611105
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Is Bitcoin a relevant predictor of standard & poor's 500?
Muglia, Camilla; Santabarbara, Luca; Grassi, Stefano - In: Journal of risk and financial management : JRFM 12 (2019) 2/93, pp. 1-10
Model Selection (DMS). According to our results, Bitcoin does not show any direct impact on the predictability of Standard … we compare alternative models using a point and density forecast relying on Dynamic Model Averaging (DMA) and Dynamic …
Persistent link: https://www.econbiz.de/10012022045
Saved in:
Cover Image
Sophisticated and small versus simple and sizeable : when does it pay off to introduce drifting coefficients
Feldkircher, Martin; Huber, Florian; Kastner, Gregor - 2018
Persistent link: https://www.econbiz.de/10011799559
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Forecasting with the Standardized Self-Perturbed Kalman Filter
Grassi, Stefano; Nonejad, Nima; Santucci de Magistris, Paolo - 2014
A modification of the self-perturbed Kalman filter of Park and Jun (1992) is proposed for the on-line estimation of models subject to parameter instability. The perturbation term in the updating equation of the state covariance matrix is weighted by the measurement error variance, thus avoiding...
Persistent link: https://www.econbiz.de/10010456954
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Cover Image
Forecasting with the Standardized Self-Perturbed Kalman Filter
Grassi, Stefano; Nonejad, Nima; Magistris, Paolo Santucci de - School of Economics and Management, University of Aarhus - 2014
A modification of the self-perturbed Kalman filter of Park and Jun (1992) is proposed for the on-line estimation of models subject to parameter instability. The perturbationterm in the updating equation of the state covariance matrix is weighted by the measurement error variance, thus avoiding...
Persistent link: https://www.econbiz.de/10010851262
Saved in:
Cover Image
Forecasting with the standardized self-perturbed kalman filter
Grassi, Stefano; Nonejad, Nima; Santucci de Magistris, Paolo - 2014
Persistent link: https://www.econbiz.de/10010339076
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Cover Image
Forecasting with the standardized self-perturbed Kalman filter
Grassi, Stefano; Nonejad, Nima; Santucci de Magistris, Paolo - 2014
A modification of the self-perturbed Kalman filter of Park and Jun (1992) is proposed for the on-line estimation of models subject to parameter in stability. The perturbation term in the updating equation of the state covariance matrix is weighted by the measurement error variance, thus avoiding...
Persistent link: https://www.econbiz.de/10010402289
Saved in:
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