GARCHMVDCCGIBBS.RPF uses Independence Chain Metropolis to analyze the conditional correlations generated by a DCC model. The conditional correlations are a complicated function of the data and parameters so getting an estimate of their precision (and not just point estimates) isn't simple. This uses M-H to sample from the posterior of the model, saves the histories of the conditional correlations and generates graphs of upper and lower bounds. Over half the program is for dealing with the rather complicated structure required for saving and analyzing many draws of several complete (and long) time series.
Detailed Description
GARCHMVDCCGIBBS—DCC GARCH Model with Metropolis-Hastings
Re: DCC GARCH Model with Metropolis-Hastings
Hello,
I run the graph, but unfortunately, I cannot see any confidence bands in the graph.Thank you for the help.
I run the graph, but unfortunately, I cannot see any confidence bands in the graph.Thank you for the help.
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Re: DCC GARCH Model with Metropolis-Hastings
From the comments:
* Generate the median and 90% confidence band for the DCC correlations.
* For this data set, the period to period movement is large enough
* relative to the spread that the three lines basically end up on top of
* each other. If you graph over a shorter period, you can see at least
* some spread between the upper and lower bounds.
* Generate the median and 90% confidence band for the DCC correlations.
* For this data set, the period to period movement is large enough
* relative to the spread that the three lines basically end up on top of
* each other. If you graph over a shorter period, you can see at least
* some spread between the upper and lower bounds.
Last bumped by TomDoan on Tue Aug 13, 2024 9:29 am.