[R] VaR and ES through MonteCarlo method

ESMERALDA PODA podaesmeralda at gmail.com
Mon Dec 22 14:17:52 CET 2014

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.


   Compute the maximum likelihood estimate for the model.

   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
    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:



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
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

I would really appreciate this.


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