Hi everybody,
This is the homework I am trying to solve.
Ex. Assume that you have a position of 144530 shares of Bill inc.. The
object Y2 contains an iid sample of the returns for these shares. Assume
that data follow a Student distribution.
1.
Compute the maximum likelihood estimate for the model.
2.
Compute the estimation of V aRα and of ESα for α = 0.99 based on the
obtained estimates, using a parametric formula or with the pure Monte Carlo
method
3. Obtain a bootstrap confidence interval for V aRα and of ESα for α = 0
.99 at a confidence level 0.90, using B = 1000 replications.
I solved point 1. (you can see the screenshot attached).
However in point 2, where I have to compute VaR and ES, based on the
estimates obtained in point 1. I typed this:
#POINT 2
q<-114530
n.val <- 10000
x <- rt(n=n.val, obj=mle.t)
loss.mc <- -Q*x
but, I obtain error. I am working with a student distribution. I need
particularly
the obj=mle.t since I need to work on the estimate I have obtained.
Can somebody, who is familiar with VaR and ES give me some hint through
this?
I would really appreciate this.
Best
Esmeralda
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