Hermite approximations in credit portfolio modeling with probability of default–loss given default correlation

2015 ◽  
Vol 11 (3) ◽  
pp. 1-20 ◽  
Author(s):  
Anthony Owen ◽  
James Bryers ◽  
Francois Buet-Golfouse
Keyword(s):  
Probability Of Default ◽  
Default Correlation ◽  
Loss Given Default ◽  
Credit Portfolio

scholarly journals Non-Performing Loans for Italian Companies: When Time Matters. An Empirical Research on Estimating Probability to Default and Loss Given Default

2020 ◽  
Vol 8 (4) ◽  
pp. 68
Author(s):  
Giuseppe Orlando ◽  
Roberta Pelosi
Keyword(s):  
Risk Taking ◽  
Economic Losses ◽  
Probability Of Default ◽  
Legal Environment ◽  
Loss Given Default ◽  
Recovery System ◽  
Main Driver ◽  
Long Time ◽  
The Subject ◽  
Time Required

Within bank activities, which is normally defined as the joint exercise of savings collection and credit supply, risk-taking is natural, as in many human activities. Among risks related to credit intermediation, credit risk assumes particular importance. It is most simply defined as the potential that a bank borrower or counterparty fails to fulfil correctly at maturity the pecuniary obligations assumed as principal and interest. Whenever this happens, a loan is non-performing. Among the main risk components, the Probability of Default (PD) and the Loss Given Default (LGD) have been the subject of greater interest for research. In this paper, logit model is used to predict both components. Financial ratios are used to estimate the PD. Time of recovery and presence of collateral are used as covariates of the LGD. Here, we confirm that the main driver of economic losses is the bureaucratically encumbered recovery system and the related legal environment. The long time required by Italian bureaucratic procedures, simply put, seems to lower dramatically the chance of recovery from defaulting counterparties.

scholarly journals Econometric model to estimate the Probability of Default and Loss Given Default in the EBA stress test in 2016

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Salvador Climent-Serrano
Keyword(s):  
Panel Data ◽  
Econometric Model ◽  
Stress Test ◽  
A Priori ◽  
Ordinary Least Squares ◽  
Probability Of Default ◽  
Macroeconomic Factors ◽  
Factors Affecting ◽  
Loss Given Default ◽  
Test Methodology

In this research, an econometric with panel data using Ordinary least squares OLS model is constructed following the guidelines recommended by the EBA stress test methodology for 2016. The findings indicate that macroeconomic factors affecting defaults are the expected ones in the Spanish credit institutions. However, loan impairments do not follow the patterns that a priori would be normal. Divergent is outcomes in defaults and impairments: the Non-Performing Loans (NPL) is pro-cyclical and impairment losses are counter-cyclical.

scholarly journals Aggregation of Incidence and Intensity Risk Variables to Achieve Reconciliation

Risks ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 107
Author(s):  
Clive Hunt ◽  
Ross Taplin
Keyword(s):  
Intensity Ratio ◽  
Important Task ◽  
Utilization Rate ◽  
Probability Of Default ◽  
Aggregate Level ◽  
Expected Loss ◽  
Total Risk ◽  
Loss Given Default ◽  
The Individual ◽  
Ratio Variables

The aggregation of individual risks into total risk using a weighting variable multiplied by two ratio variables representing incidence and intensity is an important task for risk professionals. For example, expected loss (EL) of a loan is the product of exposure at default (EAD), probability of default (PD), and loss given default (LGD) of the loan. Simple weighted (by EAD) means of PD and LGD are intuitive summaries however they do not satisfy a reconciliation property whereby their product with the total EAD equals the sum of the individual expected losses. This makes their interpretation problematic, especially when trying to ascertain whether changes in EAD, PD, or LGD are responsible for a change in EL. We propose means for PD and LGD that have the property of reconciling at the aggregate level. Properties of the new means are explored, including how changes in EL can be attributed to changes in EAD, PD, and LGD. Other applications such as insurance where the incidence ratio is utilization rate (UR) and the intensity ratio is an average benefit (AB) are discussed and the generalization to products of more than two ratio variables provided.

scholarly journals Asset correlation, portfolio diversification and regulatory capital in the Basel Capital Accord

2011 ◽  
Vol 1 (3) ◽  
pp. 31-39 ◽  
Author(s):  
Sylvia Gottschalk
Keyword(s):  
Basel Ii ◽  
Capital Adequacy ◽  
Probability Of Default ◽  
Regulatory Capital ◽  
Kmv Model ◽  
High Quantiles ◽  
Portfolio Loss Distribution ◽  
Credit Portfolio ◽  
Portfolio Loss ◽  
Asset Correlation

In this paper, we analyze the properties of the KMV model of credit portfolio loss. This theoretical model constitutes the cornerstone of Basel II’s Internal Ratings Based(IRB) approach to regulatory capital. Our results show that this model tends to overestimate the probability of portfolio loss when the probability of default of a single firm and the firms’ asset correlations are low. On the contrary, probabilities of portfolio loss are underestimated when the probability of default of a single firm and asset correlations are high. Moreover, the relationship between asset correlation and probability of loan portfolio loss is only consistent at very high quantiles of the portfolio loss distribution. These are precisely those adopted by the Basel II Capital Accord for the calculations of capital adequacy provisions. So, although the counterintuitive properties of the KMV model do not extend to Basel II, they do restrict its generality as a model of credit portfolio loss.

Part II Commercial Banking, 10 The Internal Ratings-Based Approach

2018 ◽  
Author(s):  
Gleeson Simon
Keyword(s):  
Internal Models ◽  
Commercial Banking ◽  
Probability Of Default ◽  
Expected Loss ◽  
Loss Given Default ◽  
Total Capital ◽  
Regulatory Standard ◽  
Model Probability ◽  
Irb Approach

This chapter discusses the internal ratings-based approach (IRB). The IRB permits a bank to use its internal models to derive risk weights for particular exposures. There are two available bases for the IRB: foundation (F-IRB), which permits the bank to model Probability of Default (PD), but relies on regulatory standard figures to determine Loss Given Default (LGD) and Exposure at Default (EAD); and advanced (A-IRB), in which all three of these are modelled. The A-IRB IRB approach models PD, LGD, EAD, and M. Both IRB approaches model both expected loss (EL) and unexpected loss (UL), and IRB banks are expected to recognise the EL derived from their models in their capital calculations. Consequently, a bank using an IRB approach will generally have a different total capital level from that which it would have if it were an SA bank.

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