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Author: Jiri Witzany Publisher: ISBN: Category : Languages : en Pages : 28
Book Description
The paper analyzes a two-factor credit risk model allowing to capture default and recovery rate variation, their mutual correlation, and dependence on various explanatory variables. At the same time, it allows computing analytically the unexpected credit loss. We propose and empirically implement estimation of the model based on aggregate and exposure level Moody's default and recovery data. The results confirm existence of significantly positive default and recovery rate correlation. We empirically compare the unexpected loss estimates based on the reduced two-factor model with Monte Carlo simulation results, and with the current regulatory formula outputs. The results show a very good performance of the proposed analytical formula which could feasibly replace the current regulatory formula.
Author: Jiri Witzany Publisher: ISBN: Category : Languages : en Pages : 28
Book Description
The paper analyzes a two-factor credit risk model allowing to capture default and recovery rate variation, their mutual correlation, and dependence on various explanatory variables. At the same time, it allows computing analytically the unexpected credit loss. We propose and empirically implement estimation of the model based on aggregate and exposure level Moody's default and recovery data. The results confirm existence of significantly positive default and recovery rate correlation. We empirically compare the unexpected loss estimates based on the reduced two-factor model with Monte Carlo simulation results, and with the current regulatory formula outputs. The results show a very good performance of the proposed analytical formula which could feasibly replace the current regulatory formula.
Author: Benjamin Bade Publisher: ISBN: Category : Languages : en Pages : 36
Book Description
This paper provides evidence for the relationship between credit quality, recovery rate, and correlation. The paper finds that rating grade, rating shift, and macroeconomic factors provide a highly significant explanation for default risk and recovery risk of US bond issues. The empirical data suggest that default and recovery processes are highly correlated. Therefore, a joint approach is required for estimating time-varying default probabilities and recovery rates that are conditional on default. This paper develops and applies such a model.
Author: Klaus Duellmann Publisher: ISBN: Category : Languages : en Pages : 53
Book Description
This paper presents an analytical and empirical analysis of a parsimonious model framework that accounts for a dependence of bond and bank loan recoveries on systematic risk. We extend the single risk factor model by assuming that the recovery rates also depend on this risk factor and follow a logit?normal distribution. The results are compared with those of two related models, suggested in Frye (2000) and Pykhtin (2003), which pose the assumption of a normal and a log-normal distribution of recovery rates. We provide estimators of the parameters of the asset value process and their standard errors in closed form. For the parameters of the recovery rate distribution we also provide closed-form solutions of a feasible maximum-likelihood estimator for the three models. The model parameters are estimated from default frequencies and recovery rates that were extracted from a bond and loan database of Standard&Poor's. We estimate the correlation between recovery rates and the systematic risk factor and determine the impact on economic capital. Furthermore, the impact of measuring recovery rates from market prices at default and from prices at emergence from default is analysed. As a robustness check for the empirical results of the maximum-likelihood estimation method we also employ a method-of-moments. Our empirical results indicate that systematic risk is a major factor influencing recovery rates. The calculation of a default?weighted recovery rate without further consideration of this factor may lead to downward-biased estimates of economic capital. Recovery rates measured from market prices at default are generally lower and more sensitive to changes of the systematic risk factor than are recovery rates determined at emergence from default. The choice between these two measurement methods has a stronger impact on the expected recovery rates and the economic capital than introducing a dependency of recovery rates on systematic risk in the single risk factor model.
Author: Jennifer S. Conrad Publisher: ISBN: Category : Languages : en Pages : 56
Book Description
We propose a novel method of estimating default probabilities using equity option data. The resulting default probabilities are highly correlated with estimates of default probabilities extracted from CDS spreads, which assume constant recovery rates. Additionally, the option implied default probabilities are higher in bad economic times and for firms with poorer credit ratings and financial positions. An inferred recovery rate, after controlling for liquidity effects, is also related to underlying business and firm conditions, varies across sectors and predicts subsequent equity returns.
Author: Tobias Neumann Publisher: ISBN: Category : Languages : en Pages : 40
Book Description
Default correlation is a key driver of credit risk. In the Basel regulatory framework it is measured by the asset value correlation parameter. Though past studies suggest that the parameter is over-calibrated for mortgages -- generally the largest asset class on banks' balance sheets -- they do not take into account bias arising from small samples or non-Gaussian risk factors. Adjusting for these biases using a non-Gaussian, non-linear state space model I find that the Basel calibration is appropriate for UK and US mortgages. This model also forecasts mortgage default rates accurately and parsimoniously. The model generates value-at-risk estimates for future mortgage default rates, which can be used to inform stress-testing and macroprudential policy.
Author: Edward I. Altman Publisher: ISBN: Category : Languages : en Pages : 46
Book Description
This paper analyzes the impact of various assumptions about the association between aggregate default probabilities and the loss given default on bank loans and corporate bonds, and seeks to empirically explain this critical relationship. Moreover, it simulates the effects on mandatory capital requirements like those proposed in 2001 by the Basel Committee on Banking Supervision. We present the analysis and results in four distinct sections. The first section examines the literature of the last three decades of the various structural-form, closed-form and other credit risk and portfolio credit value-at-risk (VaR) models and the way they explicitly or implicitly treat the recovery rate variable. Section 2 presents simulation results under three different recovery rate scenarios and examines the impact of these scenarios on the resulting risk measures: our results show a significant increase in both expected and unexpected losses when recovery rates are stochastic and negatively correlated with default probabilities. In Section 3, we empirically examine the recovery rates on corporate bond defaults, over the period 1982-2000. We attempt to explain recovery rates by specifying a rather straightforward statistical least squares regression model. The central thesis is that aggregate recovery rates are basically a function of supply and demand for the securities. Our econometric univariate and multivariate time series models explain a significant portion of the variance in bond recovery rates aggregated across all seniority and collateral levels. Finally, in Section 4 we analyze how the link between default probability and recovery risk would affect the procyclicality effects of the New Basel Capital Accord, due to be released in 2002. We see that, if banks use their own estimates of LGD (as in the quot;advancedquot; IRB approach), an increase in the sensitivity of banks' LGD due to the variation in PD over economic cycles is likely to follow. Our results have important implications for just about all portfolio credit risk models, for markets which depend on recovery rates as a key variable (e.g., securitizations, credit derivatives, etc.), for the current debate on the revised BIS guidelines for capital requirements on bank credit assets, and for investors in corporate bonds of all credit qualities.
Author: Andrea Sironi Publisher: ISBN: Category : Languages : en Pages : 44
Book Description
This paper analyzes the impact of various assumptions about the association between aggregate default probabilities and the loss given default on bank loans and corporate bonds, and seeks to empirically explain this critical relationship. Moreover, it simulates the effects on mandatory capital requirements like those proposed in 2001 by the Basel Committee on Banking Supervision. We present the analysis and results in four distinct sections. The first section examines the literature of the last three decades of the various structural-form, closed-form and other credit risk and portfolio credit value-at-risk (VaR) models and the way they explicitly or implicitly treat the recovery rate variable. Section 2 presents simulation results under three different recovery rate scenarios and examines the impact of these scenarios on the resulting risk measures: our results show a significant increase in both expected and unexpected losses when recovery rates are stochastic and negatively correlated with default probabilities. In Section 3, we empirically examine the recovery rates on corporate bond defaults, over the period 1982-2000. We attempt to explain recovery rates by specifying a rather straightforward statistical least squares regression model. The central thesis is that aggregate recovery rates are basically a function of supply and demand for the securities. Our econometric univariate and multivariate time series models explain a significant portion of the variance in bond recovery rates aggregated across all seniority and collateral levels. Finally, in Section 4 we analyze how the link between default probability and recovery risk would affect the procyclicality effects of the New Basel Capital Accord, due to be released in 2002. We see that, if banks use their own estimates of LGD (as in the quot;advancedquot; IRB approach), an increase in the sensitivity of banks' LGD due to the variation in PD over economic cycles is likely to follow. Our results have important implications for just about all portfolio credit risk models, for markets which depend on recovery rates as a key variable (e.g., securitizations, credit derivatives, etc.), for the current debate on the revised BIS guidelines for capital requirements on bank credit assets, and for investors in corporate bonds of all credit qualities.
Author: Edward I. Altman Publisher: Bloomberg Press ISBN: 9781904339502 Category : Business & Economics Languages : en Pages : 364
Book Description
In this ground-breaking new title, Risk Books brings together three prominent editors to provide a timely reference text on loss given default (LGD) measurement and management and the requirements of the Basel II Capital Accord.
Author: Leopold Sögner Publisher: ISBN: Category : Languages : en Pages : 15
Book Description
This article covers the implicit estimation of the parameters in the Jarrow/Turnbull (1995) default risk model. We demonstrate by means of a simulation analysis that joint estimation of the default intensity and the recovery rate by non-linear least squares is numerically unstable. Therefore, we suggest a stepwise estimation procedure. We fix the recovery rate and estimate the default intensity conditional on the recovery rate. This can be done for various recovery rates. We show that if data - either real world data or simulated data - does not deviate too much from the Jarrow/Turnbull model, the recovery rate can be estimated by an analysis of the pricing errors (observed prices vs. model prices) resulting from the alternative combinations of default intensities (estimated conditionally on the recovery rate) and recovery rates (). Applying this technique to German AA bank bond data shows that empirical bond prices deviate too much from the Jarrow/Turnbull model to apply our stepwise procedure. Insofar, the recovery rate cannot be estimated from market prices. Therefore, it has to be withdrawn from exogenous sources, such as estimates based on observed recoveries when defaults occur. Taking such values from related literature and conditionally on them estimating default intensities from market prices provides a method easy to implement.
Author: Jiri Witzany
Author: Jiri Witzany
Author: Benjamin Bade
Author: Klaus Duellmann
Author: Jennifer S. Conrad
Author: Tobias Neumann
Author: Edward I. Altman
Author: Edward I. Altman
Author: Andrea Sironi
Author: Edward I. Altman
Author: Leopold Sögner