reply is inline
Hello Gaurav,
The function:
> VaR(tstock[,2],alpha=0.01) # gives the same VaR as above with historical
simulation
VaR
-2.86
but i tried this function for normal distribution:
> VaR.norm (tstock[,2],p=0.99)$VaR
Error in VaR.norm(tstock[, 2], p = 0.99) :
Negative value in parameter 'ydat'
@@@ if you have seen the help manual then you mus have got that you dont
need to give the retun series.
R is trying to calucate the logarithm of a negative number which is why it
is throwing you error.
try this instead
> XXX<-VaR.norm(stock$ESPA.STOCK.EUROPE,p=0.01)
> XXX$VaR
[1] -3.11079
>
I dont understand the way with the normal distribution :( Maybe you can
help me a littble bit.
Cheers :-)
KR,
Alin Soare
2007/5/11, [EMAIL PROTECTED] <[EMAIL PROTECTED]>:
reply is inline
- Regards,
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|
| Gaurav Yadav
| Assistant Manager, CCIL, Mumbai (India)
| Mob: +919821286118 Email: [EMAIL PROTECTED]
| Man is made by his belief, as He believes, so He is.
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Hello Mr. Gaurav Yadav,
Hi Soare,
1. I want to calculate the 99%VaR/1 day for the stock fonds, after sorting
the values the 5th or 6th value is it?
In Historical simulation it is the 5th value...... because it tells you to
be more cautious that a higher loss 'may' be there, secondly VaR only
shows the possibility and not the maximum loss which you can incur :-)
cheers
2. How do I calculate it under normal distribution aproximation?
Well there is also a normal method or variance - covariance method which
assumes normal distribution :-)
if you want to incorporate recency effect then you can also see boudhouks
method
try this paper which will give you very good understanding of various
methods of VaR
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=51420#PaperDownload
++++++++++++++++++
apply(tstock,2,function(x) VaR(x,alpha=0.01)) # are these the right VaR's
for the stockfonds?
@@@ you can yourself see it, you have around 579 observation and 1% of it
mean 5.79th observation
Thus if you become risk averse then you take the 5th smallest value and
otherwise 6th value.
So just sort the returns in ascending order and then see the 5th and the
6th values
> sorted_espa_stock_europe<-sort(tstock[,2])
> sorted_espa_stock_europe[5]
[1] -2.86
> sorted_espa_stock_europe[6]
[1] -2.74
>
your code gives -2.86 thus you can get the rest :-) cheers
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