A new set of improved value-at-risk backtests
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Date
2013-08-27
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Abstract
We propose a new set of formal backtests for VaR-forecasts that significantly improve upon existing backtesting
procedures. Our new test of unconditional coverage can be used for both directional and non-directional testing and
is thus able to test separately whether a VaR-model is too conservative or underestimates the actual risk exposure.
Second, we stress the importance of testing the property of independent and identically distributed (i.i.d.) VaRexceedances
and propose a simple approach that explicitly tests for the presence of clusters in VaR-violation processes.
Results from a simulation study indicate that our tests significantly outperform competing backtests in several distinct
settings. In addition, the empirical analysis of a unique data set consisting of asset returns of an asset manager’s
portfolios underline the usefulness of our new backtests especially in times of market turmoil.
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Keywords
backtesting, Monte Carlo simulation, Value-at-Risk