This paper studies survival measures in credit risk models. Survival measure, which was first introduced by Schonbucher [12] in the framework of defaultable LMM, has the advantage of eliminating default indicator variable directly from the expectation by absorbing it into Randon-Nikodym density process. Survival measure approach was further extended by Collin-Duresne[4] to avoid calculating a troublesome jump in IBPR reduced-form model. This paper considers survival measure in "HBPR" model, i.e. default time is characterized by Cox construction, and studies the relevant drift changes and martingale representations. This paper also takes advantage of survival measure to solve the looping default problem in interacting intensity model with st...
Lenders monitor their borrowers over time, allowing them to dynamically predict the probability of ...
In this paper we use an intensity-based framework to analyze and compute the correlated default prob...
Loss Given Default (LGD) is one of the key parameters needed in order to estimate expected and unexp...
This paper studies survival measures in credit risk models. Survival measure, which was first introd...
Thesis by publication.Includes bibliographic references1 Introduction -- 2 Literature Review -- 3 PA...
The Basel Accords, a set of recommendations for regulating the banking industry, have changed the st...
Survival analysis can be applied to build models for time of default on debt. In this paper we repor...
A thorough understanding of the joint default behavior of credit-risky securities is essential for c...
2011-07-07This thesis studies the modeling of default dependency in the reduced-form model and its a...
The most extensively studied form of credit risk is the default risk which is the risk that an oblig...
Credit risk models are used by financial companies to evaluate in advance the insolvency risk caused...
The prediction of the time of default in a credit risk setting via survival analysis needs to take a...
In this paper we model competing risks, default and early settlement events, in the presence of long...
We obtain a quasi-analytical approximation of the survival probability in the credit risk model prop...
In this article we describe the construction and implementation of a pricing model for a leading UK ...
Lenders monitor their borrowers over time, allowing them to dynamically predict the probability of ...
In this paper we use an intensity-based framework to analyze and compute the correlated default prob...
Loss Given Default (LGD) is one of the key parameters needed in order to estimate expected and unexp...
This paper studies survival measures in credit risk models. Survival measure, which was first introd...
Thesis by publication.Includes bibliographic references1 Introduction -- 2 Literature Review -- 3 PA...
The Basel Accords, a set of recommendations for regulating the banking industry, have changed the st...
Survival analysis can be applied to build models for time of default on debt. In this paper we repor...
A thorough understanding of the joint default behavior of credit-risky securities is essential for c...
2011-07-07This thesis studies the modeling of default dependency in the reduced-form model and its a...
The most extensively studied form of credit risk is the default risk which is the risk that an oblig...
Credit risk models are used by financial companies to evaluate in advance the insolvency risk caused...
The prediction of the time of default in a credit risk setting via survival analysis needs to take a...
In this paper we model competing risks, default and early settlement events, in the presence of long...
We obtain a quasi-analytical approximation of the survival probability in the credit risk model prop...
In this article we describe the construction and implementation of a pricing model for a leading UK ...
Lenders monitor their borrowers over time, allowing them to dynamically predict the probability of ...
In this paper we use an intensity-based framework to analyze and compute the correlated default prob...
Loss Given Default (LGD) is one of the key parameters needed in order to estimate expected and unexp...