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Journal of Applied Statistics Volume 40, 2013 - Issue 6
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Original Articles

Modelling small and medium enterprise loan defaults as rare events: the generalized extreme value regression model

Raffaella Calabrese Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, ItalyCorrespondence[email protected]
&
Silvia Angela Osmetti Departement of Statistical Sciences, University Cattolica del Sacro Cuore, Milan, Italy
Pages 1172-1188 | Received 19 Dec 2011, Accepted 09 Mar 2013, Published online: 03 Apr 2013

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Han Lin Shang & Ruofan Xu. (2021) Functional time series forecasting of extreme values. Communications in Statistics: Case Studies, Data Analysis and Applications 7:2, pages 182-199.
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Anthony Medford & James W. Vaupel. (2019) An introduction to gevistic regression mortality models. Scandinavian Actuarial Journal 2019:7, pages 604-620.
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Raffaella Calabrese, Giampiero Marra & Silvia Angela Osmetti. (2016) Bankruptcy prediction of small and medium enterprises using a flexible binary generalized extreme value model. Journal of the Operational Research Society 67:4, pages 604-615.
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Raffaella Calabrese & Paolo Giudici. (2015) Estimating bank default with generalised extreme value regression models. Journal of the Operational Research Society 66:11, pages 1783-1792.
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Raffaella Calabrese. (2014) Optimal cut-off for rare events and unbalanced misclassification costs. Journal of Applied Statistics 41:8, pages 1678-1693.
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