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Nowcasting made easier : a toolbox for economists
Linzenich, Jan; Meunier, Baptiste - 2024
We provide a versatile nowcasting toolbox that supports three model classes (dynamic factor models, large Bayesian VAR, bridge equations) and offers methods to manage data selection and adjust for Covid-19 observations. The toolbox aims at simplifying two key tasks: creating new nowcasting...
Persistent link: https://www.econbiz.de/10015179785
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An alternative Bayesian approach to structural breaks in time series models
Hauwe, Sjoerd van den; Paap, Richard; Dijk, Dick van - 2011
We propose a new approach to deal with structural breaks in time series models. The key contribution is an alternative dynamic stochastic specification for the model parameters which describes potential breaks. After a break new parameter values are generated from a so-called baseline prior...
Persistent link: https://www.econbiz.de/10011383033
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Large mixed-frequency VARs with a parsimonious time-varying parameter structure
Götz, Thomas B.; Hauzenberger, Klemens - 2018
To simultaneously consider mixed-frequency time series, their joint dynamics, and possible structural changes, we introduce a time-varying parameter mixed-frequency VAR. To keep our approach from becoming too complex, we implement time variation parsimoniously: only the intercepts and a common...
Persistent link: https://www.econbiz.de/10011903709
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A Bayesian method of change-point estimation with recurrent regimes: Application to GARCH models
Bauwens, Luc; De Backer, Bruno; Dufays, Arnaud - In: Journal of Empirical Finance 29 (2014) C, pp. 207-229
We present an estimation and forecasting method, based on a differential evolution MCMC method, for inference in GARCH … nearly all series. Finally, we carry out a forecasting exercise to evaluate the usefulness of structural break models. …
Persistent link: https://www.econbiz.de/10011116269
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Large Mixed-Frequency Vars with a Parsimonious Time-Varying Parameter Structure
Götz, Thomas B. - 2019
To simultaneously consider mixed-frequency time series, their joint dynamics, and possible structural changes, we introduce a time-varying parameter mixed-frequency VAR. To keep our approach from becoming too complex, we implement time variation parsimoniously: only the intercepts and a common...
Persistent link: https://www.econbiz.de/10012897924
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Bayesian Nonparametric Graphical Models for Time-Varying Parameters VAR
Iacopini, Matteo - 2019
Over the last decade, big data have poured into econometrics, demanding new statistical methods for analysing high-dimensional data and complex non-linear relationships. A common approach for addressing dimensionality issues relies on the use of static graphical structures for extracting the...
Persistent link: https://www.econbiz.de/10012868987
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Bayesian VARs and prior calibration in times of COVID-19
Hartwig, Benny - 2022
COVID-19 observations and discusses their impact on prior calibration for inference and forecasting purposes. It shows that … volatility. For forecasting, the choice among outlier-robust error structures is less important, however, when a large cross …
Persistent link: https://www.econbiz.de/10013472790
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Financial Risk Management with Bayesian Estimation of GARCH Models : Theory and Applications
Ardia, David - 2009
This book presents in detail methodologies for the Bayesian estimation of single-regime and regime-switching GARCH … the Bayesian paradigm for inference. The next three chapters describe the estimation of the GARCH model with Normal … applications of the Bayesian estimation of GARCH models. We show how agents facing different risk perspectives can select their …
Persistent link: https://www.econbiz.de/10013156202
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Censored Posterior and Predictive Likelihood in Bayesian Left-Tail Prediction for Accurate Value at Risk Estimation
Gatarek, Lukasz T. - 2014
techniques in applications of Value-at-Risk prediction in GARCH models …
Persistent link: https://www.econbiz.de/10013064150
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Deep Bayesian Estimation of the Rough Path-Dependent Volatility Model for Forecasting Purposes
Parent, Léo - 2023
characteristic of volatility dynamics, making it a suitable choice for volatility forecasting. However, its complex structure … the RPDV model a competitive tool for volatility forecasting.To achieve this objective, the article proposes an innovative …
Persistent link: https://www.econbiz.de/10014354222