Kupiec, P.H. () Techniques for Verifying the Accuracy of Risk Measurement Models. The Journal of Derivatives, 3, This paper presents a comparative evaluation of the predictive performance of conventional univariate VaR models including unconditional normal distribution. Request PDF on ResearchGate | Techniques for Verifying the Accuracy of Risk Management Models | Risk Paul Kupiec at American Enterprise Institute.

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CiteULike: Techniques for Verifying the Accuracy of Risk Measurement Models

We have no references for this item. It also allows you to accept potential citations to this item that we are uncertain about. Only too many failures lead to model rejections. Home Citegeist Everyone’s Library.

This statistic is asymptotically distributed as a chi-square variable with 1 kkpiec of freedom. All material on this site has been provided by the respective publishers and authors.

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Techniques for Verifying the Accuracy of Risk Measurement Models | The Journal of Derivatives

By clicking “OK” you acknowledge that you have the right to distribute this file. You can combine this statistic with the frequency POF test to get a conditional coverage CC mixed test:. Januarypp. If you are a registered author of this item, you may also want to check the “citations” tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

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Read about how we use cookies. Profits and losses are expressed in monetary units and represent value changes in a portfolio. Check below whether another version of this item is available online. Christoffersen proposed a test to measure whether the probability of observing an exception on a particular day depends on whether an exception occurred. As a best practice, use more than one criterion to backtest the performance of VaR models, because all tests have strengths and weaknesses.

Unlike the unconditional probability of observing an exception, Christoffersen’s test measures the dependency between consecutive days only. For many portfolios, especially trading portfolios, VaR is computed daily. This statistic is asymptotically distributed as a chi-square with 1 degree of freedom.

Kupidc to you by AQnowledge ttechniques, precision products for scientists. When requesting a correction, please mention this item’s handle: The TUFF test is also based on a likelihood ratio, but the underlying distribution is a geometric distribution.

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Kupiec also proposed a second test called the time until first failure TUFF. If you have authored this item and are not yet registered cerifying RePEc, we encourage you to do it here.

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Checking only the first exception leaves much information out, specifically, whatever happened after kupkec first exception is ignored. You can use this daily data to assess the performance of VaR models, which is the goal of VaR backtesting. Download full text from publisher To our knowledge, this item is not available for download. Kupiec introduced a variation on the binomial test called the proportion of failures POF test.

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For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Find this article at Save current location: The POF test works with the binomial distribution approach.

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Techniques for Verifying the Accuracy of Risk Measurement Models

There are no reviews of this article. Search all the public and authenticated articles in CiteULike. If the data suggests that the probability of exceptions is different than pverifyiing VaR model is rejected.

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It is unlikely that too many exceptions come from a correct VaR model. Value-at-risk VaR tecniques one of the main measures of financial risk.