arXiv · arXiv q-fin · 2006
This paper generalizes Moody's correlated binomial default distribution for homogeneous (exchangeable) credit portfolio, which is introduced by Witt, to the case of inhomogeneous portfolios. As inhomogeneous portfolios, we consider two cases. In the first case, we treat a portfolio whose assets have uniform default correlation and non-uniform default probabilities. We obtain the default probability distribution and s…
S. Mori, K. Kitsukawa, M. Hisakado
arXiv · arXiv q-fin · 2019
In this paper, we propose a methodology based on piece-wise homogeneous Markov chain for credit ratings and a multivariate model of the credit spreads to evaluate the financial risk in European Union (EU). Two main aspects are considered: how the financial risk is distributed among the European countries and how large is the value of the total risk. The first aspect is evaluated by means of the expected value of a dy…
Guglielmo D'Amico, Filippo Petroni, Philippe Regnault, Stefania Scocchera, Loriano Storchi
arXiv · arXiv q-fin · 2015
The role of credit rating agencies has been under severe scrutiny after the subprime crisis. In this paper we explore the relationship between credit ratings and informational efficiency of a sample of thirty nine corporate bonds of US oil and energy companies from April 2008 to November 2012. For that purpose, we use a powerful statistical tool relatively new in the financial literature: the complexity-entropy causa…
Aurelio F. Bariviera, Luciano Zunino, M. Belen Guercio, Lisana B. Martinez, Osvaldo A. Rosso
arXiv · arXiv q-fin · 2012
While defaults are rare events, losses can be substantial even for credit portfolios with a large number of contracts. Therefore, not only a good evaluation of the probability of default is crucial, but also the severity of losses needs to be estimated. The recovery rate is often modeled independently with regard to the default probability, whereas the Merton model yields a functional dependence of both variables. We…
Alexander Becker, Alexander F. R. Koivusalo, Rudi Schäfer
arXiv · arXiv q-fin · 2011
There is empirical evidence that recovery rates tend to go down just when the number of defaults goes up in economic downturns. This has to be taken into account in estimation of the capital against credit risk required by Basel II to cover losses during the adverse economic downturns; the so-called "downturn LGD" requirement. This paper presents estimation of the LGD credit risk model with default and recovery depen…
Pavel V. Shevchenko, Xiaolin Luo
arXiv · arXiv q-fin · 2005
We propose a fast algorithm for computing the expected tranche loss in the Gaussian factor model. We test it on a 125 name portfolio with a single factor Gaussian model and show that the algorithm gives accurate results. We choose a 125 name portfolio for our tests because this is the size of the standard DJCDX.NA.HY portfolio. The algorithm proposed here is intended as an alternative to the much slower Moody's FT me…
Pavel Okunev
arXiv · arXiv q-fin · 2026
This paper develops an observed-data likelihood for applying moving-aggregate modified autoregressive (MAGMAR) copula time-series models to discrete sovereign rating-migration counts with time-varying exposure. An annual count identifies a probability-integral-transform interval rather than a unique latent point, so the likelihood integrates the latent process over the complete sequence of count intervals. A guided s…
Marina Palaisti
arXiv · arXiv q-fin · 2023
Knowing which factors are significant in credit rating assignment leads to better decision-making. However, the focus of the literature thus far has been mostly on structured data, and fewer studies have addressed unstructured or multi-modal datasets. In this paper, we present an analysis of the most effective architectures for the fusion of deep learning models for the prediction of company credit rating classes, by…
Mahsa Tavakoli, Rohitash Chandra, Fengrui Tian, Cristián Bravo
arXiv · arXiv q-fin · 2020
Credit ratings are one of the primary keys that reflect the level of riskiness and reliability of corporations to meet their financial obligations. Rating agencies tend to take extended periods of time to provide new ratings and update older ones. Therefore, credit scoring assessments using artificial intelligence has gained a lot of interest in recent years. Successful machine learning methods can provide rapid anal…
Parisa Golbayani, Ionuţ Florescu, Rupak Chatterjee
arXiv · arXiv q-fin · 2020
Credit capital requirements in Internal Rating Based approaches require the calibration of two key parameters: the probability of default and the loss-given-default. This letter considers the uncertainty about these two parameters and models this uncertainty in an elementary way: it shows how this estimation risk can be computed and properly taken into account in regulatory capital. We analyse two standard real datas…
Roberto Baviera
arXiv · arXiv q-fin · 2018
We present two methodologies on the estimation of rating transition probabilities within Markov and non-Markov frameworks. We first estimate a continuous-time Markov chain using discrete (missing) data and derive a simpler expression for the Fisher information matrix, reducing the computational time needed for the Wald confidence interval by a factor of a half. We provide an efficient procedure for transferring such …
Marius Pfeuffer, Goncalo dos Reis, Greig smith
arXiv · arXiv q-fin · 2016
Following widely used in visual recognition concept of relative attributes, the article establishes definition of the relative PCA attributes for a class of objects defined by vectors of their parameters. A new rating model (RELARM) is built using relative PCA attribute ranking functions for rating object description and k-means clustering algorithm. Rating assignment of each rating object to a rating category is der…
Elnura Irmatova
arXiv · arXiv q-fin · 2014
We introduce a simple approach for testing the reliability of homogeneous generators and the Markov property of the stochastic processes underlying empirical time series of credit ratings. We analyze open access data provided by Moody's and show that the validity of these assumptions - existence of a homogeneous generator and Markovianity - is not always guaranteed. Our analysis is based on a comparison between empir…
Pedro Lencastre, Frank Raischel, Pedro G. Lind, Tim Rogers
arXiv · arXiv q-fin · 2011
As part of Basel II's incremental risk charge (IRC) methodology, this paper summarizes our extensive investigations of constructing transition probability matrices (TPMs) for unsecuritized credit products in the trading book. The objective is to create monthly or quarterly TPMs with predefined sectors and ratings that are consistent with the bank's Basel PDs. Constructing a TPM is not a unique process. We highlight v…
Tzahi Yavin, Hu Zhang, Eugene Wang, Michael A. Clayton