[R-SIG-Finance] Time-scale of Value at risk
Данир Зулькарнаев
d@n|rzu| @end|ng |rom gm@||@com
Thu Mar 28 17:44:09 CET 2019
Terry, thank you for your help
чт, 28 мар. 2019 г., 19:28 Terry Leitch <tleitch1 using jhu.edu>:
> The rugarch package can do a simulated forward distribution that takes
> into account the GARCH model spec and the chosen error distribution. I
> would recommend, given the complexity of your approach, to do a forward sim
> and get the VaR from the resulting sim.
>
>
>
> > On Mar 28, 2019, at 3:56 AM, Данир Зулькарнаев <danirzul using gmail.com>
> wrote:
> >
> >
> > Hi guys!
> >
> > Could you please help me to understand some things about Value at risk?
> >
> > 1. How to time-scale nonnormal parametric Value at Risk?
> > I mean modified VaR, student VaR, skewed student VaR.
> > Is there any rule of thumb like square-root-of-time for normal
> > distribution?
> > Are there some packages to do it in R,
> >
> > 2. How does ugarchroll in rugarch estimate value-at-risk?
> > Does it compute the theoretical quantile of the particular distribution
> > which has been set in ugarchspec?
> >
> > 3. If I simulate 10000 paths by ugarchpath and find the X% of the worst
> > scenarios, is it be equivalent to Monte Carlo VaR?
> >
> > Thanks!
> >
> > [[alternative HTML version deleted]]
> >
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