Robust and bias-corrected estimation of the coefficient of tail dependence

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<title>Robust and bias-corrected estimation of the coefficient of tail dependence</title>
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<namePart>Dutang, Christophe</namePart>
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<abstract displayLabel="Summary">We introduce a robust and asymptotically unbiased estimator for the coefficient of tail dependence in multivariate extreme value statistics. The estimator is obtained by fitting a second order model to the data by means of the minimum density power divergence criterion. The asymptotic properties of the estimator are investigated. The efficiency of our methodology is illustrated on a small simulation study and by a real dataset from the actuarial context.</abstract>
<note type="statement of responsibility">Christophe Dutang,  Yuri Goegebeur,  Armelle Guillou</note>
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<title>Insurance : mathematics and economics</title>
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<publisher>Oxford : Elsevier, 1990-</publisher>
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<identifier type="issn">0167-6687</identifier>
<identifier type="local">MAP20077100574</identifier>
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<text>07/07/2014 Volumen 57 Número 1 - julio 2014 </text>
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