Raffaella Calabrese
Raffaella Calabrese
Professor of Statistics and Data Science, University of Edinburgh
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Citata da
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Bank loan recovery rates: Measuring and nonparametric density estimation
R Calabrese, M Zenga
Journal of Banking & Finance 34 (5), 903-911, 2010
Enhancing credit scoring with alternative data
VB Djeundje, J Crook, R Calabrese, M Hamid
Expert Systems with Applications 163, 113766, 2021
SMEs’ growth under financing constraints and banking markets integration in the euro area
M Moscalu, C Girardone, R Calabrese
Journal of Small Business Management 58 (4), 707-746, 2020
Modelling small and medium enterprise loan defaults as rare events: the generalized extreme value regression model
R Calabrese, SA Osmetti
Journal of Applied Statistics 40 (6), 1172-1188, 2013
Bankruptcy prediction of small and medium enterprises using a flexible binary generalized extreme value model
R Calabrese, G Marra, SA Osmetti
Journal of the Operational Research Society 67 (4), 604-615, 2015
Estimating bank default with generalised extreme value regression models
R Calabrese, P Giudici
Journal of the Operational Research society 66, 1783-1792, 2015
Estimators of binary spatial autoregressive models: A Monte Carlo study
R Calabrese, JA Elkink
Journal of Regional Science 54 (4), 664-687, 2014
Downturn loss given default: Mixture distribution estimation
R Calabrese
European Journal of Operational Research 237 (1), 271-277, 2014
Predicting bank loan recovery rates with a mixed continuous‐discrete model
R Calabrese
Applied stochastic models in business and industry 30 (2), 99-114, 2014
Understanding the dynamics of UK Covid‐19 SME financing
R Calabrese, M Cowling, W Liu
British Journal of Management 33 (2), 657-677, 2022
A comparative analysis of the UK and Italian small businesses using Generalised Extreme Value models
G Andreeva, R Calabrese, SA Osmetti
European Journal of Operational Research 249 (2), 506-516, 2016
“Birds of a feather” fail together: exploring the nature of dependency in SME defaults
R Calabrese, G Andreeva, J Ansell
Risk Analysis 39 (1), 71-84, 2019
The effectiveness of TARP-CPP on the US banking industry: A new copula-based approach
R Calabrese, M Degl’Innocenti, SA Osmetti
European Journal of Operational Research 256 (3), 1029-1037, 2017
A new approach to measure systemic risk: A bivariate copula model for dependent censored data
R Calabrese, SA Osmetti
European Journal of Operational Research 279 (3), 1053-1064, 2019
Financial fragmentation and SMEs’ access to finance
R Calabrese, C Girardone, A Sclip
Small Business Economics 57 (4), 2041-2065, 2021
Spatial dependence in microfinance credit default
V Medina-Olivares, R Calabrese, Y Dong, B Shi
International Journal of Forecasting 38 (3), 1071-1085, 2022
Measuring bank contagion in Europe using binary spatial regression models
R Calabrese, JA Elkink, PS Giudici
Journal of the Operational Research Society 68, 1503-1511, 2017
Interpretable machine learning for imbalanced credit scoring datasets
Y Chen, R Calabrese, B Martin-Barragan
European Journal of Operational Research 312 (1), 357-372, 2024
Estimating bank loans loss given default by generalized additive models
R Calabrese
UCD Geary Institute Discussion Paper Series, WP2012/24, 2012
Generalized extreme value regression for binary rare events data: an application to credit defaults
R Calabrese, SA Osmetti
Bulletin of the International Statistical Institute LXII, 58th Session of…, 2011
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