Oh sry, I forgot to add the R-help list.

Thanks a lot for your help Guarav!

2007/5/11, gyadav@ccilindia.co.in <gyadav@ccilindia.co.in>:
>
>
> Hi Saore
>
> ***Please always mark a copy to the R-help list, it may be helpfull to
> many, you have forgotten twice***
> *** Do Reply to all with history ***
>  :-) cheers
>
>
>
>
> YOU ARE THE BEST :)
>
> I have some problems understanding R, but R and I will be friends in the
> future hehe :)
>
> I have another problem with investing in one of this stockfonds.
> Lets say I would invest in the europe stockfonds on 2.5.2006 1000 dollar.
> What would be the 99%VaR/1 day under historical simulation? The same as
> above?
> @@@ So what do you think, -2.86 number means Lets investigate
>
> suppose you have invested 1000, one way to realize is
> 100*ln(Tommorow/Todays) = -2.86 (out return) where Todays = 1000
> hence Tommorow = 1000*exp(-2.86/100) = 971.8051 , therefore Loss = 1000 -
> 971.8051 = 28.19489
>
> I hope this would make your understanding much better and clear about VaR
> :-)
> HTH
>
> KR,
> Alin
>
> 2007/5/11, *gyadav@ccilindia.co.in * <gyadav@ccilindia.co.in><*
> gyadav@ccilindia.co.in* <gyadav@ccilindia.co.in>>:
>
> 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, *gyadav@ccilindia.co.in* <gyadav@ccilindia.co.in> <*
> gyadav@ccilindia.co.in* <gyadav@ccilindia.co.in>>:
>
> reply is inline
>
> -  Regards,
>
>        \\\|||||///
>     \\   -    -   //
>      (  o   o  )
> oOOo-(_)-oOOo--------
> |
> | Gaurav Yadav
> | Assistant Manager, CCIL, Mumbai (India)
> | Mob: +919821286118 Email: *emailtogauravyadav@gmail.com *<emailtogauravyadav@gmail.com>
> | Man is made by his belief, as He believes, so He is.
> |                                           --- Bhagavad Gita
> |_______Oooo________
>       oooO(      )
>       (      )   )   /
>        \   (    (_/
>          \_ )
>
>
> 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 *<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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