Add to ORKGOne difficulty in implementing structural credit spread models is that the underlying asset value cannot be directly observed. Models require the unobserved asset value and the unknown parameter(s) as inputs; for example, asset value and volatility are in practice unknown when the model of Merton (1974) is applied. This paper applies the maximum likelihood principle to the estimation of structural credit spread models. The maximum likelihood estimator for parameter(s), asset value, credit spread and default probability are derived for models with deterministic and stochastic interest rates. Monte Carlo studies are conducted to examine the performance of the maximum likelihood method in finite samples specifically for the structural models o...
Empirical findings are mixed about the performance of structural models for term structure of credit...
Empirical findings are mixed about the performance of structural models for term structure of credit...
In this paper we apply Cheyette's Markov representation of the Heath-Jarrow-Morton framework to the ...
One critical difficulty in implementing structural credit risk models is that the underlying asset v...
One critical di#culty in implementing Merton's (1974) credit risk model is that the underlying ...
Moody’s KMV method is a popular commercial implementation of the structural credit risk model pionee...
The transformed-data maximum likelihood estimation (MLE) method for structural credit risk models de...
In the context of increasing competition in the banking market, increasing regulatory requirements f...
In the context of increasing competition in the banking market, increasing regulatory requirements f...
This paper describes how structural bond pricing models can be estimated using a Simulated Maximum L...
This thesis is an empirical investigation of various estimation methods for the analysis of the dyna...
This paper describes how structural bond pricing models can be es-timated using a Simulated Maximum ...
A difficulty that arises when implementing structural bond pricing models is the estimation of the v...
This paper develops a maximum likelihood estimation method for the deposit insurance pricing model o...
The aim of this paper is to throw light on the relationship between credit spread changes and past c...
Empirical findings are mixed about the performance of structural models for term structure of credit...
Empirical findings are mixed about the performance of structural models for term structure of credit...
In this paper we apply Cheyette's Markov representation of the Heath-Jarrow-Morton framework to the ...
One critical difficulty in implementing structural credit risk models is that the underlying asset v...
One critical di#culty in implementing Merton's (1974) credit risk model is that the underlying ...
Moody’s KMV method is a popular commercial implementation of the structural credit risk model pionee...
The transformed-data maximum likelihood estimation (MLE) method for structural credit risk models de...
In the context of increasing competition in the banking market, increasing regulatory requirements f...
In the context of increasing competition in the banking market, increasing regulatory requirements f...
This paper describes how structural bond pricing models can be estimated using a Simulated Maximum L...
This thesis is an empirical investigation of various estimation methods for the analysis of the dyna...
This paper describes how structural bond pricing models can be es-timated using a Simulated Maximum ...
A difficulty that arises when implementing structural bond pricing models is the estimation of the v...
This paper develops a maximum likelihood estimation method for the deposit insurance pricing model o...
The aim of this paper is to throw light on the relationship between credit spread changes and past c...
Empirical findings are mixed about the performance of structural models for term structure of credit...
Empirical findings are mixed about the performance of structural models for term structure of credit...
In this paper we apply Cheyette's Markov representation of the Heath-Jarrow-Morton framework to the ...