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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), pp. 207-229
Persistent link: https://www.econbiz.de/10011300484
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Bayesian estimation of the GARCH(1,1) model with student-t innovations
Ardia, David; Hoogerheide, Lennart F. - 2010
parsimonious and effective GARCH(1,1) model with Student-t innovations. The estimation procedure is fully automatic and thus avoids …
Persistent link: https://www.econbiz.de/10011380176
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Modeling the volatility of returns on commodities: an application and empirical comparison of GARCH and SV models
Fernández Prada Saucedo, Jean Pierre; Rodriguez, Gabriel - 2020
Persistent link: https://www.econbiz.de/10012435636
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Regime changes in Bitcoin GARCH volatility dynamics
Ardia, David; Bluteau, Keven; Rüede, Maxime - In: Finance research letters 29 (2019), pp. 266-271
Persistent link: https://www.econbiz.de/10012419095
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Importance sampling from posterior distributions using copula-like approximations
Dellaportas, Petros; Tsionas, Efthymios G. - In: Journal of econometrics 210 (2019) 1, pp. 45-57
Persistent link: https://www.econbiz.de/10012303370
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Financial risk management with bayesian estimation of GARCH models : theory and applications
Ardia, David - 2008
Persistent link: https://www.econbiz.de/10013278094
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Financial Risk Management with Bayesian Estimation of GARCH Models : Theory and Applications
Ardia, David (contributor) - 2008
This book presents methodologies for the Bayesian estimation of GARCH models and their application to financial risk … paradigm for inference. The next three chapters describe the estimation of the GARCH model with Normal innovations and the …
Persistent link: https://www.econbiz.de/10013520959
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Volatility estimation using a rational GARCH model
Takaishi, Tetsuya - In: Quantitative finance and economics 2 (2018) 1, pp. 127-136
Persistent link: https://www.econbiz.de/10012137901
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Quantile stochastic frontiers
Tsionas, Efthymios G. - In: European journal of operational research : EJOR 282 (2020) 3, pp. 1177-1184
Persistent link: https://www.econbiz.de/10012161889
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Data-driven particle filters for Particle Markov Chain Monte Carlo
Leung, Patrick; Forbes, Catherine Scipione; Martin, Gael M. - 2016
Persistent link: https://www.econbiz.de/10011781784