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A new goodness-of-fit test for event forecasting and its application to credit defaults / Andreas Blöchlinger in Management science, Vol. 57 N° 3 (Mars 2011) 

Public ISBD [article]  in Management science > Vol. 57 N° 3 (Mars 2011) . - pp. 487-505 Titre : A new goodness-of-fit test for event forecasting and its application to credit defaults Type de document : texte imprimé Auteurs : Andreas Blöchlinger, Auteur ; Markus Leippold, Auteur Année de publication : 2011 Article en page(s) : pp. 487-505 Note générale : Management Langues : Anglais (eng) Mots-clés : Out-of-sample  validation  Probability  calibration  Hosmer–Lemeshow  statistic  Bernoulli  mixture  models  Credit  risk Index. décimale : 658 Organisation des entreprises. Techniques du commerce Résumé : We develop a new goodness-of-fit test for validating the performance of probability forecasts. Our test statistic is particularly powerful under sparseness and dependence in the observed data. To build our test statistic, we start from a formal definition of calibrated forecasts, which we operationalize by introducing two components. The first component tests the level of the estimated probabilities; the second validates the shape, measuring the differentiation between high and low probability events. After constructing test statistics for both level and shape, we provide a global goodness-of-fit statistic, which is asymptotically {chi}2 distributed. In a simulation exercise, we find that our approach is correctly sized and more powerful than alternative statistics. In particular, our shape statistic is significantly more powerful than the Kolmogorov–Smirnov test. Under independence, our global test has significantly greater power than the popular Hosmer–Lemeshow's {chi}2 test. Moreover, even under dependence, our global test remains correctly sized and consistent. As a timely and important empirical application of our method, we study the validation of a forecasting model for credit default events. DEWEY : 658 ISSN : 0025-1909 En ligne : http://mansci.journal.informs.org/cgi/content/abstract/57/3/487 [article] A new goodness-of-fit test for event forecasting and its application to credit defaults [texte imprimé] / Andreas Blöchlinger, Auteur ; Markus Leippold, Auteur . - 2011 . - pp. 487-505. Management Langues : Anglais (eng) in Management science > Vol. 57 N° 3 (Mars 2011) . - pp. 487-505 Mots-clés : Out-of-sample  validation  Probability  calibration  Hosmer–Lemeshow  statistic  Bernoulli  mixture  models  Credit  risk Index. décimale : 658 Organisation des entreprises. Techniques du commerce Résumé : We develop a new goodness-of-fit test for validating the performance of probability forecasts. Our test statistic is particularly powerful under sparseness and dependence in the observed data. To build our test statistic, we start from a formal definition of calibrated forecasts, which we operationalize by introducing two components. The first component tests the level of the estimated probabilities; the second validates the shape, measuring the differentiation between high and low probability events. After constructing test statistics for both level and shape, we provide a global goodness-of-fit statistic, which is asymptotically {chi}2 distributed. In a simulation exercise, we find that our approach is correctly sized and more powerful than alternative statistics. In particular, our shape statistic is significantly more powerful than the Kolmogorov–Smirnov test. Under independence, our global test has significantly greater power than the popular Hosmer–Lemeshow's {chi}2 test. Moreover, even under dependence, our global test remains correctly sized and consistent. As a timely and important empirical application of our method, we study the validation of a forecasting model for credit default events. DEWEY : 658 ISSN : 0025-1909 En ligne : http://mansci.journal.informs.org/cgi/content/abstract/57/3/487