Hot answers tagged r
5
Mh, well I am not sure about already implemented functions, sure, I think they will exist. I give you a solution, with the direct implementation of the EWMA, so it does not need a preimplemented function.
Here is the code:
# just simulating some values, not sensible ones, just for
# demonstration purposes
returnseries<-runif(1000, min=-0.2, max=0.2)
...
2
you need to use the forecast for both the mean and sigma. It should look something like this:
forecast = ugarchforecast(modelfit, n.ahead = 1, data = mydata);
sigma(forecast);
fitted(forecast)
Then plug these values into the equation:
\begin{align}
\hat{VaR}_{0.99,T|T-1}&=\hat{\mu}_{T|T-1} + \hat{\sigma}_{T|T-1} * q_{0.99}
\end{align}
where $T$ is ...
1
Now I have trouble interpreting the results of Q-Statistics? First of all to test the mean equation, we look at the standardized residuals. These standardized residuals should behave iid(0,1). Since the p-values is very small, we can conclude, that they are not independent, since there exist serial correlation. Is this right?
Yes, as you mention near ...
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