[R-SIG-Finance] Time-scale of Value at risk

Terry Leitch t|e|tch1 @end|ng |rom jhu@edu
Thu Mar 28 17:28:30 CET 2019

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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