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Related papers: Graphical models for correlated defaults

200 papers

This article proposes a graphical model that handles mixed-type, multi-group data. The motivation for such a model originates from real-world observational data, which often contain groups of samples obtained under heterogeneous conditions…

Methodology · Statistics 2023-01-02 Sjoerd Hermes , Joost van Heerwaarden , Pariya Behrouzi

Most common parametric families of copulas are totally ordered, and in many cases they are also positively or negatively regression dependent and therefore they lead to monotone regression functions, which makes them not suitable for…

Methodology · Statistics 2017-02-28 Arturo Erdely

In conditional copula models, the copula parameter is deterministically linked to a covariate via the calibration function. The latter is of central interest for inference and is usually estimated nonparametrically. However, when a…

Methodology · Statistics 2014-03-19 Elif F. Acar , Radu V. Craiu , Fang Yao

The risk of a credit portfolio depends crucially on correlations between the probability of default (PD) in different economic sectors. Often, PD correlations have to be estimated from relatively short time series of default rates, and the…

Statistical Mechanics · Physics 2008-12-02 Bernd Rosenow , Rafael Weissbach , Frank Altrock

This paper develops a two-dimensional structural framework for valuing credit default swaps and corporate bonds in the presence of default contagion. Modelling the values of related firms as correlated geometric Brownian motions with…

Pricing of Securities · Quantitative Finance 2008-12-02 Helen Haworth , Christoph Reisinger , William Shaw

We study the problem of maximizing the probability that (i) an electric component or financial institution $X$ does not default before another component or institution $Y$ and (ii) that $X$ and $Y$ default jointly within the class of all…

Probability · Mathematics 2021-10-04 Thomas Mroz , Juan Fernández Sánchez , Sebastian Fuchs , Wolfgang Trutschnig

Gaussian graphical models play an important role in various areas such as genetics, finance, statistical physics and others. They are a powerful modelling tool which allows one to describe the relationships among the variables of interest.…

Methodology · Statistics 2020-04-21 Laurentiu Catalin Hinoveanu , Fabrizio Leisen , Cristiano Villa

The assumption of independence between observations (units) in a dataset is prevalent across various methodologies for learning causal graphical models. However, this assumption often finds itself in conflict with real-world data, posing…

Machine Learning · Computer Science 2024-12-31 Alex Chen , Qing Zhou

Diffusion in a linear potential in the presence of position-dependent killing is used to mimic a default process. Different assumptions regarding transport coefficients, initial conditions, and elasticity of the killing measure lead to…

Computational Finance · Quantitative Finance 2015-05-30 Yuri A. Katz

A frequent task in exploratory data analysis consists in examining pairwise dependencies between data variables. Popular approaches include visualizing correlation or scatter plot matrices. However, both methods can be misleading. The…

Applications · Statistics 2022-04-04 Arturo Erdely , Manuel Rubio-Sanchez

There is much interest in providing probabilistic semantics for defaults but most approaches seem to suffer from one of two problems: either they require numbers, a problem defaults were intended to avoid, or they generate peculiar side…

Artificial Intelligence · Computer Science 2013-04-10 Eric Neufeld , David L Poole

We analyze the fluctuation of the loss from default around its large portfolio limit in a class of reduced-form models of correlated firm-by-firm default timing. We prove a weak convergence result for the fluctuation process and use it for…

Probability · Mathematics 2015-02-20 Konstantinos Spiliopoulos , Justin A. Sirignano , Kay Giesecke

Graphical models can represent a multivariate distribution in a convenient and accessible form as a graph. Causal models can be viewed as a special class of graphical models that not only represent the distribution of the observed system…

Methodology · Statistics 2017-06-29 Christina Heinze-Deml , Marloes H. Maathuis , Nicolai Meinshausen

Thanks to their ability to capture complex dependence structures, copulas are frequently used to glue random variables into a joint model with arbitrary marginal distributions. More recently, they have been applied to solve statistical…

Methodology · Statistics 2022-08-22 Thomas Nagler , Thibault Vatter

We follow a long path for Credit Derivatives and Collateralized Debt Obligations (CDOs) in particular, from the introduction of the Gaussian copula model and the related implied correlations to the introduction of arbitrage-free dynamic…

Pricing of Securities · Quantitative Finance 2010-02-17 Damiano Brigo , Andrea Pallavicini , Roberto Torresetti

This paper describes a flexible and tractable bottom-up dynamic correlation modelling framework with a consistent stochastic recovery specification. The stochastic recovery specification only models the first two moments of the spot…

Pricing of Securities · Quantitative Finance 2010-04-22 Yadong Li

A new methodology for incorporating LGD correlation effects into the Basel II risk weight functions is introduced. This methodology is based on modelling of LGD and default event with a single loss variable. The resulting formulas for…

Other Condensed Matter · Physics 2008-12-02 Dirk Tasche

Decomposable dependency models and their graphical counterparts, i.e., chordal graphs, possess a number of interesting and useful properties. On the basis of two characterizations of decomposable models in terms of independence…

Artificial Intelligence · Computer Science 2013-02-08 Luis M. de Campos , Juan F. Huete

The impact of a stress scenario of default events on the loss distribution of a credit portfolio can be assessed by determining the loss distribution conditional on these events. While it is conceptually easy to estimate loss distributions…

Risk Management · Quantitative Finance 2016-01-11 Dirk Tasche

This paper addresses the problem of distributed coding of images whose correlation is driven by the motion of objects or positioning of the vision sensors. It concentrates on the problem where images are encoded with compressed linear…

Computer Vision and Pattern Recognition · Computer Science 2015-06-03 Vijayaraghavan Thirumalai , Pascal Frossard