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On the determination of general scientific models
Gallant, A. Ronald (contributor);  … - 2004 - This draft September 2004
Persistent link: https://www.econbiz.de/10003770545
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Capturing unobserved consumer heterogeneity using the Bayesian heterogeneity model
Frühwirth-Schnatter, Sylvia; Tüchler, Regina; Otter, … - In: Adaptive information systems and modelling in economics …, (pp. 57-70). 2005
Persistent link: https://www.econbiz.de/10003319808
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Non-linear volatility modeling in classical and Bayesian frameworks with applications to risk management
Miazhynskaia, Tatiana; Dockner, Engelbert J.; … - In: Adaptive information systems and modelling in economics …, (pp. 73-98). 2005
Persistent link: https://www.econbiz.de/10003319811
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Bayesian estimation of the GARCH (1,1) model with student-t innovations
Ardia, David; Hoogerheide, Lennart F. - 2010
Persistent link: https://www.econbiz.de/10003974018
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Efficient Bayesian estimation and combination of GARCH-type models
Ardia, David; Hoogerheide, Lennart F. - 2010
Persistent link: https://www.econbiz.de/10003974028
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Stock index returns' density prediction using GARCH models : frequentist or Bayesian estimation?
Hoogerheide, Lennart F.; Ardia, David; Corré, Nienke - 2011
Persistent link: https://www.econbiz.de/10008824705
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A statistical inquiry into the plausibility of recursive utility
Gallant, A. Ronald; Hong, Han - In: Journal of financial econometrics : official journal of … 5 (2007) 4, pp. 523-559
Persistent link: https://www.econbiz.de/10003570720
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Bayesian estimation of single-regime and regime-switching GARCH models : applications to financial risk management
Ardia, David - 2008
Persistent link: https://www.econbiz.de/10003855637
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To bridge, to warp or to wrap? A comparative study of Monte Carlo methods for efficient evaluation of marginal likelihoods
Ardia, David; Hoogerheide, Lennart; Dijk, Herman K. van - 2009
Persistent link: https://www.econbiz.de/10003813789
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Large vector autoregressions with asymmetric priors
Carriero, Andrea; Clark, Todd E.; Marcellino, Massimiliano - 2015 - This draft: November 2015
We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors and time varying volatilities, even when the cross sectional dimension of the system N is particularly large. The algorithm is based on a simple triangularisation which allows to...
Persistent link: https://www.econbiz.de/10011389735