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Frieder, Mokinski ; Frieder, Mokinski. (2017) A severity function approach to scenario selection.
In: Discussion Papers. RePEc:zbw:bubdps:342017.
Full description at Econpapers
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It is well known that for horizons greater than one period the predictive density of the Bayesian VAR described above is not available in closed form. Simulated draws can, however, be obtained by drawing a sequence of Σ and B (from equations A.3-A.4) and shocks (remembering εt ∼ N ( 0 , Σ )) and then assembling the implied draw of YT+h (see Carriero et al., 2015). In my application, for each draw of a total of 1,000 draws from the posterior of Σ and B, I draw ten paths of shocks (i.e. of εT+1, . . . , εT+h) and thus arrive at a total of 10,000 draws from the predictive density. To be able to apply the results of Appendix A.1 for the SFA, I assume that the predictive density comes from a multivariate normal distribution with mean and variance given by the respective statistics of the simulated draws. Note that the true predictive density is nonGaussian.
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