A credit portfolio framework under dependent risk parameters: probability of default, loss given default and exposure at default

2016 ◽  
Vol 12 (1) ◽  
pp. 97-119 ◽  
Author(s):  
Johanna Eckert ◽  
Kevin Jakob ◽  
Matthias Fischer
Keyword(s):  
Probability Of Default ◽  
Loss Given Default ◽  
Risk Parameters ◽  
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.

IFRS9 e le sfide di contesto

2021 ◽  
Author(s):  
Giuseppe Torluccio ◽  
◽  
Paolo Palliola ◽  
Paola Brighi ◽  
Lorenzo Dal Maso ◽  
...  
Keyword(s):  
Financial Institutions ◽  
Expected Loss ◽  
Economic Cycle ◽  
Support Measures ◽  
Historical Series ◽  
Risk Parameters ◽  
Credit Portfolio ◽  
The Relationship ◽  
Credit Losses ◽  
Forward Looking

Under IFRS9, Financial Institutions are required to implement impairment frameworks to determine the expected losses on their credit portfolio taking into account the current (so called “point in time”) and the prospective (so called “forward looking”) economic cycle. The Covid-19 pandemic, which began in early 2020, has posed significant challenges for Financial Institutions in their ability to manage credit risk. Despite numerous guidelines given by regulators, estimating IFRS9 expected loss continues to be a considerable challenge. The challenge partly stems from the relationship between macro-economic scenarios and credit losses, the treatment of moratoriums inside the historical series for development and calibration of IFRS9 risk parameters, and the management of support measures defined at National and European levels (e.g. Next Generation EU) for the forward looking estimations.

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.

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