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I m doing my research on estimating Value at risk using different assumptions on volatility and then compare my results based on backtesting. I obtained results and just on question based on my results.

The different models estimates accurately in 5% confidence level rather than 1%.. Is it common result? Because the same model rejected in 1% but accepted in 5%..

Thanks in advance

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Seems reasonable to me. See Section 3.1.1 in thesis for how the confidence interval changes the frequency of expected exceptions. Also, your sample size will have some impact as well. –  chrisaycock Sep 3 '11 at 13:13
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1 Answer 1

It is common.

The smaller the tail area you are considering the harder it is to be right because the effect of the assumption on the distribution becomes more important. Think about it in the other direction: if your level is 50%, then pretty much any distributional assumption will do.

The other issue is the length of the time horizon. As the horizon expands practical amounts, there is even more sensitivity to the model. What I found in http://www.burns-stat.com/pages/Working/varunigar.pdf was that 10 day horizons demand exceptionally good models -- moving from 1 day to 10 days is much harder than moving from 5% to 1% tail areas.

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