1,721,071 research outputs found
Using Differential Evolution to improve the accuracy of bank rating systems
No full textCredit rating is the evaluation of the likelihood of an obligor to default on a loan. Each obligor in the bank’s credit portfolio isassigned to a certain rating class, or PD (probability of default) bucket; all obligors in a PD bucket then receive the same “pooled”PD, based on which a capital charge against credit risk must be computed. The only analytical approach to this problem is basedon k-means and has some limitations in practice. An error minimization approach to credit rating using differential evolution (DE)is introduced. The performances of DE and other common search heuristics are compared using credit rating data of a major Italianbank. Empirical results show that DE is clearly superior compared to a genetic algorithm (GA), particle swarm optimization (PSO),random search (RS) and two naïve partitioning approaches. Moreover, the proposed approach obtained better results than k-meansin much less runtime for a simplified instance of the problem where within-groups variances can be used for clustering
Default recovery rates in credit risk modelling: A review of the literature and empirical evidence
No full textEvidence from many countries in recent years suggests that collateral values and recovery rates (RRs) on corporate defaults can be volatile and, moreover, that they tend to go down just when the number of defaults goes up in economic downturns. This link between RRs and default rates has traditionally been neglected by credit risk models, as most of them focused on default risk and adopted static loss assumptions, treating the RR either as a constant parameter or as a stochastic variable independent from the probability of default (PD). This traditional focus on default analysis has been partly reversed by the recent significant increase in the number of studies dedicated to the subject of recovery-rate estimation and the relationship between default and RRs. This paper presents a detailed review of the way credit risk models, developed during the last 30 years, treat the RR and, more specifically, its relationship with the PD of an obligor. Recent empirical evidence concerning this issue is also presented and discussed. © Banca Monte dei Paschi di Siena SpA, 2004
The optimal structure of PD buckets
No full textIn designing credit rating systems under the new Basel Accord, considerable effort has been devoted to rating assignment and quantification,while the choice of the optimal bucket structure has received less attention. To fill this gap, we propose two ‘‘bucketing” strategiesbased on constrained optimisation, paying attention to the implications of rating buckets for loan-pricing and adverse selection phenomena. We compare them with some more naı ̈ve approaches, based on a sample of about 100,000 European companies. We also analyse the persistence of our performance measures over time, as well as the effect of large exposures being associated with low-PDobligors
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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