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I am having a bit of trouble disseminating the true meaning behind VaR.

Say you have two V Values, prior to taking ABS value. Both values are negative, the first value being -10 and the second value being -20. After taking the ABS Value, the Var answer becomes 10 and 20, respectively. Both values have an 99% Confidence interval.

What value is better? Convention would say, prior to taking ABS, -20 is better, since its further from zero, hence less loss. But after you take the ABS Value, you are now have a higher degree of loss?

What am I missing?

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closed as off-topic by emcor, Bob Jansen Dec 12 '15 at 17:48

This question appears to be off-topic. The users who voted to close gave this specific reason:

  • "Basic financial questions are off-topic as they are assumed to be common knowledge for those studying or working in the field of quantitative finance." – Bob Jansen
If this question can be reworded to fit the rules in the help center, please edit the question.

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    $\begingroup$ I suggest you read some basic theory before posting. From your question I dont think you know enough about the subejct... I recommend Market Risk Analysis series by Carol Alexander. $\endgroup$ – UmaN Dec 12 '15 at 14:43
  • $\begingroup$ The question is indeed a bit unclear and basic. I advise you follow up on the suggestions made. $\endgroup$ – Bob Jansen Dec 12 '15 at 17:48
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I won't base my answer on your example as i couldn't understand what you mean.

Firstly, when you ask a question "what is better?" you should address this question to the model and not the output values.

Secondly, model is good only when it as accurately as possible explains the reality (with a degree of confidence). The model is useless if it overestimates the risk i.e. there are no overshoots - actual losses never exceed VaR levels. The model is still useless if it underestimates the risk i.e. too many overshoots - actually losses frequently exceed VaR levels. Reasonable model is expected to produce a limited number of overshoots (consistent with a degree of confidence).

Tool used to analyse the performance of VaR model is called backtesting.

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