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My question is what would be the better( in terms of estimation accuracy) method of VaR calculation among below two:, also any small code snippet will be great as a starting point for me.

1st method: I am trying to using a Generalized Pareto Distribution(GPD) there. I think R package POT or EVD might be of some help to fit my monthly historical return data to a GPD. Then using fExtremes package VaR might be calculated.

2nd Method : Another way is using PerformanceAnalytics package and trying calculate Modified Cornish-Fisher VaR.

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The results depend on your distribution of losses.

If there is lot of departure from Normality, Cornish-Fisher VaR results will not be as accurate as GPD. But again to estimate block maxima effectively you need a large amount of data.

So it is difficult to say much without looking at the data.

Also, I would use the QRM package that accompanies the book, "Quantitative Risk Management".

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  • $\begingroup$ is it the book "Quantitative Risk Management: Concepts, Techniques, and Tools Alexander J. McNeil, Rüdiger Frey, & Paul Embrechts"..?.btw how i can reach you ? my email: purnendumaity@gmail.com $\endgroup$ – pmr Jun 21 '15 at 17:50

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