Unexpected Recovery Risk and LGD Discount Rate Determination

Witzany, Jiří

doi:10.18267/j.efaj.63

Cited by 6 publications

(3 citation statements)

References 6 publications

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“…Witzany (2009) initially presents a capital asset pricing model, which results in a WACC model for the discount rate and computes (iteratively) the spread as the capital risk charge times the regulatory capital for market risk.11 Prudential regulators have increased the focus on consistency between the various regulations (see Basel Committee on Banking Supervision 2014).www.risk.net/journalsJournal of Risk Model Validation…”

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confidence: 99%

Benchmarking loss given default discount rates

Scheule¹,

Jortzik²

2020

JRMV

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This paper provides a theoretical and empirical analysis of alternative discount rate concepts for computing loss given default (LGD) rates using historical bank workout data. It benchmarks five discount rate concepts for workout recovery cashflows in order to derive observed LGDs in terms of economic robustness and empirical implications: contract rate at origination, loan-weighted average cost of capital, return on equity (ROE), market return on defaulted debt and market equilibrium return. The paper develops guiding principles for LGD discount rates and argues that the weighted average cost of capital and market equilibrium return dominate the popular contract rate method. The empirical analysis of data provided by Global Credit Data (GCD) shows that declining risk-free rates are in part offset by increasing market risk premiums. Common empirical discount rates lie between the risk-free rate and the ROE. The variation in empirical LGDs is moderate for the various discount rate approaches. Further, a simple correction technique for resolution bias is developed and increases observed LGDs for all periods, particularly recent periods.

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confidence: 99%

Benchmarking loss given default discount rates

Scheule¹,

Jortzik²

2020

JRMV

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“…The relationship between the two ex ante notions is an analogy between the fundamental value and the market value of a stock. Hence the discount rate can be based on a measure of the RR systematic risk and a general price of risk (see Witzany, 2009). Since the market recovery rate is never negative and can be hardly larger than 1 we normally assume that RR as well as LGD = 1 -RR lie in the interval [0,1].…”

Section: Recovery Rates and Loss Given Defaultmentioning

confidence: 99%

Survival Analysis in LGD Modeling

Witzany¹,

Rychnovský²,

Charamza³

2012

EFAJ

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“…The unexpected recovery risk is also important for determination of the recovery cash flows discount rate in line with the regulatory requirements. Witzany (2009c) proposes a methodology to estimate the discount rate and the unexpected recovery risk but the empirical study uses just an expertly set correlation at the level of 10% corresponding to an average Basel II regulatory PD correlation.…”

Section: Introductionmentioning

confidence: 99%

Estimating LGD Correlation

Witzany

2009

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract: The paper proposes a new method to estimate correlation of account level Basle II Loss Given Default (LGD). The correlation determines the probability distribution of portfolio level LGD in the context of a copula model which is used to stress the LGD parameter as well as to estimate the LGD discount rate and other parameters. Given historical LGD observations we apply the maximum likelihood method to estimate the best correlation parameter. The method is applied and analyzed on a real large data set of unsecured retail account level LGDs and the corresponding monthly series of the average LGDs. The correlation estimate comes relatively close to the PD regulatory correlation. It is also tested for stability using the bootstrapping method and used in an efficient formula to estimate ex ante one-year stressed LGD, i.e. one-year LGD quantiles on any reasonable probability level. Terms of use: Documents in

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Unexpected Recovery Risk and LGD Discount Rate Determination

Cited by 6 publications

References 6 publications

Benchmarking loss given default discount rates

Benchmarking loss given default discount rates

Survival Analysis in LGD Modeling

Estimating LGD Correlation

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