Improved duration-based backtesting of value-at-risk

Haas, Markus

doi:10.21314/jor.2006.128

Cited by 52 publications

(43 citation statements)

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“…Christoffersen and Pelletier (2004) and Haas (2005) propose twin tests of (4) and (5) these procedures by looking at squared durations, which are better able to detect various nonparametric deviation from the null. In this paper we propose another nonparametric improvement which is focused on condition (5).…”

Section: A New Test For Independent Var-violationsmentioning

confidence: 99%

“…(2015) for recent contributions), and various tests of (1) have also been around for quite a while, testing the condition (2) or (3) has received less methodological attention. Below we build upon Christoffersen (1998), Christoffersen and Pelletier (2004), Haas (2005), Candelon et al (2011) and Ziggel et al (2014) to construct a simple procedure to test this independence requirement which has high power to detect violations which occur in…”

Section: Introductionmentioning

confidence: 99%

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A simple and focused backtest of value at risk

Krämer

Wied

2015

Economics Letters

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Section: A New Test For Independent Var-violationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A simple and focused backtest of value at risk

Krämer

Wied

2015

Economics Letters

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“…As shown by Haas (2006), however, tests based on a discrete analogue of the continuous Weibull nesting the geometric (24) have (often considerably) more power to detect violation clustering, and, therefore, we employ the discrete Weibull distribution of Nakagawa and Osaki (1975), given by the probability density function…”

Section: Backtesting Value-at-risk Measuresmentioning

confidence: 99%

Asymmetric multivariate normal mixture GARCH

Haas¹,

Mittnik

Paolella

2009

Computational Statistics & Data Analysis

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“…Recently, an integrated framework for VaR-backtesting that includes the previously mentioned tests was proposed 1 1 by Berkowitz et al (2011). Further examples of the few backtests for VaR that are available to regulators are due to Berkowitz (2001), Engle and Manganelli (2004), Haas (2005) and Candelon et al (2011), although the test of unconditional coverage continues to be the industry standard mostly due to the fact that it is implicitly incorporated in the framework for backtesting internal models…”

Section: Introductionmentioning

confidence: 99%

“…Nevertheless, we will only consider the Weibull test in our simulation study as it yields considerably better results than the gamma test (see Haas, 2005). In addition to the mentioned tests, the literature on VaR backtesting also includes the standard Ljung-Box test, the CAViaR test of Engle and Manganelli (2004) and spectral density tests.…”

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confidence: 99%

A new set of improved Value-at-Risk backtests

Ziggel

Berens²,

Weiß

et al. 2014

Journal of Banking & Finance

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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.Keywords: Value-at-Risk, backtesting, Monte Carlo simulation.JEL Classification: C52, C53, C58. * We thank Harald Rosenthal of RobinNova GmbH for providing the data set for our empirical application and helpful comments on an earlier version of this paper. Judith Lameyer and Janina Mühlnickel provided outstanding research assistance. A New Set of Improved Value-at-Risk Backtests ABSTRACTWe 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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Improved duration-based backtesting of value-at-risk

Cited by 52 publications

References 0 publications

A simple and focused backtest of value at risk

A simple and focused backtest of value at risk

Asymmetric multivariate normal mixture GARCH

A new set of improved Value-at-Risk backtests

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