Why do (or did?) banks securitize their loans? Evidence from Italy

This paper investigates the ex-ante determinants of bank loan securitization by using different econometric methods on Italian individual bank data from 2000 to 2006. Our results show that bank loan securitization is a composite decision. Banks that are less capitalized, less profitable, less liquid and burdened with troubled loans are more likely to perform securitization, for a larger amount and earlier.securitization, credit risk transfer, capital requirements, liquidity needs

Wide Field Imaging. I. Applications of Neural Networks to object detection and star/galaxy classification

[Abriged] Astronomical Wide Field Imaging performed with new large format CCD detectors poses data reduction problems of unprecedented scale which are difficult to deal with traditional interactive tools. We present here NExt (Neural Extractor): a new Neural Network (NN) based package capable to detect objects and to perform both deblending and star/galaxy classification in an automatic way. Traditionally, in astronomical images, objects are first discriminated from the noisy background by searching for sets of connected pixels having brightnesses above a given threshold and then they are classified as stars or as galaxies through diagnostic diagrams having variables choosen accordingly to the astronomer's taste and experience. In the extraction step, assuming that images are well sampled, NExt requires only the simplest a priori definition of "what an object is" (id est, it keeps all structures composed by more than one pixels) and performs the detection via an unsupervised NN approaching detection as a clustering problem which has been thoroughly studied in the artificial intelligence literature. In order to obtain an objective and reliable classification, instead of using an arbitrarily defined set of features, we use a NN to select the most significant features among the large number of measured ones, and then we use their selected features to perform the classification task. In order to optimise the performances of the system we implemented and tested several different models of NN. The comparison of the NExt performances with those of the best detection and classification package known to the authors (SExtractor) shows that NExt is at least as effective as the best traditional packages.Comment: MNRAS, in press. Paper with higher resolution images is available at http://www.na.astro.it/~andreon/listapub.htm

Hybrid Neural Networks for Frequency Estimation of Unevenly Sampled Data

In this paper we present a hybrid system composed by a neural network based estimator system and genetic algorithms. It uses an unsupervised Hebbian nonlinear neural algorithm to extract the principal components which, in turn, are used by the MUSIC frequency estimator algorithm to extract the frequencies. We generalize this method to avoid an interpolation preprocessing step and to improve the performance by using a new stop criterion to avoid overfitting. Furthermore, genetic algorithms are used to optimize the neural net weight initialization. The experimental results are obtained comparing our methodology with the others known in literature on a Cepheid star light curve.Comment: 5 pages, to appear in the proceedings of IJCNN 99, IEEE Press, 199

VAT tax gap prediction: a 2-steps Gradient Boosting approach

Tax evasion is the illegal evasion of taxes by individuals, corporations, and trusts. The revenue loss from tax avoidance can undermine the effectiveness and equity of the government policies. A standard measure of tax evasion is the tax gap, that can be estimated as the difference between the total amounts of tax theoretically collectable and the total amounts of tax actually collected in a given period. This paper presents an original contribution to bottom-up approach, based on results from fiscal audits, through the use of Machine Learning. The major disadvantage of bottom-up approaches is represented by selection bias when audited taxpayers are not randomly selected, as in the case of audits performed by the Italian Revenue Agency. Our proposal, based on a 2-steps Gradient Boosting model, produces a robust tax gap estimate and, embeds a solution to correct for the selection bias which do not require any assumptions on the underlying data distribution. The 2-steps Gradient Boosting approach is used to estimate the Italian Value-added tax (VAT) gap on individual firms on the basis of fiscal and administrative data income tax returns gathered from Tax Administration Data Base, for the fiscal year 2011. The proposed method significantly boost the performance in predicting with respect to the classical parametric approaches.Comment: 27 pages, 4 figures, 8 tables Presented at NTTS 2019 conference Under review at another peer-reviewed journa

Synchrotron and Compton Components and their Variability in BL Lac Objects

BL Lacertae objects are extreme extragalactic sources characterized by the emission of strong and rapidly variable nonthermal radiation over the entire electromagnetic spectrum. Synchrotron emission followed by inverse Compton scattering in a relativistic beaming scenario is generally thought to be the mechanism powering these objects. ...Comment: 4 pages, TeX plus 3 figures. Proceedings of the conference "X-ray Astronomy 1999", September 6-10,1999, Bologn

"Diventare storici anche del tempo presente": la crisi del '56 e la storiografia marxista britannica

1. Il ’56 e i «caratteri originali» della storiografia anglo-marxista. 2. Alla vigilia del ’56: revisioni storiografiche e fondazione di «Past and Present». 3. Alla vigilia del ’56: la persistenza del «modo di pensare stalinista». 4. Gli storici comunisti britannici durante la crisi del ’56. 5. All’indomani del ’56: revisioni teoriche

La crisi dei profughi nella prospettiva della storia globale

Testo dell'Intervento tenuto da Teodoro Tagliaferri alla presentazione di Profughi, a cura di Stefano Gallo, numero monografico di «Meridiana. Rivista di storia e scienze sociali», XVII (2016), 86, pp. 21-188, svoltasi il 12 maggio 2017 all’Istituto di studi sulle società del Mediterraneo nell’ambito della Giornata di studi Nuove ricerche sulle migrazioni organizzata dal Master di I livello in Immigrazione e politiche pubbliche di accoglienza ed integrazione del Dipartimento di Scienze politiche dell’Università di Napoli Federico II. Il testo, pubblicato sul sito web della rivista «Ricerche di storia politica» (il Mulino), è accessibile on-line all’indirizzo: http://www.ricerchedistoriapolitica.it/tavole-rotonde-e-convegni/il-profugato-contemporaneo-nella-prospettiva-della-storia-globale/#more-87