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We propose two structural models for stochastic losses given default which allow to model the credit losses of a portfolio of defaultable financial instruments. The credit losses are integrated into a structural model of default events…

Risk Management · Quantitative Finance 2015-03-20 Simone Farinelli , Mykhaylo Shkolnikov

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…

Risk Management · Quantitative Finance 2012-03-15 Alexander Becker , Alexander F. R. Koivusalo , Rudi Schäfer

Corporate defaults may be triggered by some major market news or events such as financial crises or collapses of major banks or financial institutions. With a view to develop a more realistic model for credit risk analysis, we introduce a…

Computational Finance · Quantitative Finance 2013-01-03 Jia-Wen Gu , Wai-Ki Ching , Tak-Kuen Siu , Harry Zheng

In this paper we propose a copula contagion mixture model for correlated default times. The model includes the well known factor, copula, and contagion models as its special cases. The key advantage of such a model is that we can study the…

Pricing of Securities · Quantitative Finance 2010-10-21 Harry Zheng

A new procedure is presented for the objective comparison and evaluation of default definitions. This allows the lender to find a default threshold at which the financial loss of a loan portfolio is minimised, in accordance with Basel II.…

Risk Management · Quantitative Finance 2021-03-01 Arno Botha , Conrad Beyers , Pieter de Villiers

We study the pricing of credit derivatives with asymmetric information. The managers have complete information on the value process of the firm and on the default threshold, while the investors on the market have only partial observations,…

Pricing of Securities · Quantitative Finance 2010-02-18 Caroline Hillairet , Ying Jiao

In this short paper, we study the simulation of a large system of stochastic processes subject to a common driving noise and fast mean-reverting stochastic volatilities. This model may be used to describe the firm values of a large pool of…

Numerical Analysis · Mathematics 2021-10-13 Andrei Cozma , Christoph Reisinger

Inspired by the phenomenon of catastrophic forgetting, we investigate the learning dynamics of neural networks as they train on single classification tasks. Our goal is to understand whether a related phenomenon occurs when data does not…

We study an optimal investment problem under contagion risk in a financial model subject to multiple jumps and defaults. The global market information is formulated as a progressive enlargement of a default-free Brownian filtration, and the…

Probability · Mathematics 2013-02-22 Ying Jiao , Idris Kharroubi , Huyên Pham

Conditional Density Estimation (CDE) models deal with estimating conditional distributions. The conditions imposed on the distribution are the inputs of the model. CDE is a challenging task as there is a fundamental trade-off between model…

Machine Learning · Statistics 2018-10-31 Vincent Dutordoir , Hugh Salimbeni , Marc Deisenroth , James Hensman

Our financial setting consists of a market model with two flows of information. The smallest flow F is the "public" flow of information which is available to all agents, while the larger flow G has additional information about the…

Mathematical Finance · Quantitative Finance 2022-11-16 Tahir Choulli , Ferdoos Alharbi

This work has the objective of estimating default probabilities and correlations of credit portfolios given default rate information through a Bayesian framework using Stan. We use Vasicek's single factor credit model to establish the…

Applications · Statistics 2024-01-23 Jesus A. Pinera-Esquivel

Modeling complex conditional distributions is critical in a variety of settings. Despite a long tradition of research into conditional density estimation, current methods employ either simple parametric forms or are difficult to learn in…

Machine Learning · Statistics 2018-02-15 Brian L Trippe , Richard E Turner

The Papangelou intensities of determinantal (or fermion) point processes are investigated. These exhibit a monotonicity property expressing the repulsive nature of the interaction, and satisfy a bound implying stochastic domination by a…

Probability · Mathematics 2010-03-16 Hans-Otto Georgii , Hyun Jae Yoo

Motivated by the interplay between structural and reduced form credit models, we propose to model the firm value process as a time-changed Brownian motion that may include jumps and stochastic volatility effects, and to study the first…

Pricing of Securities · Quantitative Finance 2009-04-16 T. R. Hurd

Stochastic resetting can be naturally understood as a renewal process governing the evolution of an underlying stochastic process. In this work, we formally derive well-known results of diffusion with resets from a renewal theory…

Statistical Mechanics · Physics 2022-10-05 Axel Masó-Puigdellosas , Daniel Campos , Vicenç Méndez

In this paper, we deal with an axiomatic approach to default risk. We introduce the notion of a default risk measure, which generalizes the classical probability of default (PD), and allows to incorporate model risk in various forms. We…

Mathematical Finance · Quantitative Finance 2023-09-21 Max Nendel , Jan Streicher

A stable-like process is a Feller process $(X_t)_{t\geq 0}$ taking values in $\mathbb{R}^d$ and whose generator behaves, locally, like an $\alpha$-stable L\'evy process, but the index $\alpha$ and all other characteristics may depend on the…

Probability · Mathematics 2020-05-19 V. Knopova , A. Kulik , R. Schilling

The dissipation of general convex entropies for continuous time Markov processes can be described in terms of backward martingales with respect to the tail filtration. The relative entropy is the expected value of a backward submartingale.…

Probability · Mathematics 2015-01-27 Joaquin Fontbona , Benjamin Jourdain

In this paper, we use the Hawkes process to model the sequence of failure, i.e., events of compressor station and conduct survival analysis on various failure events of the compressor station. However, until now, nearly all relevant…

Machine Learning · Computer Science 2021-12-28 Lu-ning Zhang , Jian-wei Liu , Xin Zuo
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